{"after":"WzE3ODg0NjA1MDU0NzYsNy40NzI0NjU1LDMsIjgyZWE5MzBjLWE1NTItNDM0NS1iZGNjLWFkYjNhNGQwNjhjOCJd","results":[{"_score":4.7409124,"_sort":[1788635655831,4.7409124,6,"758dae5e-8c89-42b1-851d-05081ea2a8fe"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","contactPoint":{"@type":"vcard:Contact","fn":"Iowa Data Hub Administrators","hasEmail":"mailto:data@iowa.gov"},"description":"This dataset provides the geographic names data for Iowa. All names data products are extracted from the Geographic Names Information System (GNIS), the Federal Government's repository of official geographic names.  The GNIS contains the federally recognized name of each feature and defines its location by State, county, USGS topographic map, and geographic coordinates. GNIS also lists variant names, which are non-official names by which a feature is or was known. Other attributes include unique Feature ID and feature class. Feature classes under the purview of the U.S. Board on Geographic Names include natural features, unincorporated populated places, canals, channels, reservoirs, and more.  GNIS does not include roads, highways, administrative, or cultural features. In 2021, the following geographic features referred to as administrative (cultural or man-made) were removed from GNIS: airport, bridge, building, cemetery, church, dam, forest, harbor, hospital, mine, oilfield, park, post office, reserve, school, tower, trail, tunnel, and well. Some administrative feature data are maintained in other The National Map data themes.","distribution":[{"@type":"dcat:Distribution","describedBy":"https://idh-be.iowa.gov/api/v1/datasets/650/columns.json","describedByType":"application/json","downloadURL":"https://idh-be.iowa.gov/api/v1/datasets/650/rows.json","mediaType":"application/json"},{"@type":"dcat:Distribution","downloadURL":"https://idh-be.iowa.gov/api/v1/datasets/650/rows.csv","mediaType":"text/csv"}],"identifier":"https://data.iowa.gov/catalog/dataset/650","issued":"2025-08-25T21:04:51.062051+00:00","keyword":["geographic names","natural features"],"landingPage":"https://data.iowa.gov/catalog/dataset/650","license":"https://creativecommons.org/publicdomain/zero/1.0/","modified":"2026-08-31T16:51:40.030732+00:00","publisher":{"@type":"org:Organization","name":"Data Hub Administration"},"theme":["Infrastructure & Environment"],"title":"Iowa Geographic Names"},"description":"This dataset provides the geographic names data for Iowa. All names data products are extracted from the Geographic Names Information System (GNIS), the Federal Government's repository of official geographic names.  The GNIS contains the federally recognized name of each feature and defines its location by State, county, USGS topographic map, and geographic coordinates. GNIS also lists variant names, which are non-official names by which a feature is or was known. Other attributes include unique Feature ID and feature class. Feature classes under the purview of the U.S. Board on Geographic Names include natural features, unincorporated populated places, canals, channels, reservoirs, and more.  GNIS does not include roads, highways, administrative, or cultural features. In 2021, the following geographic features referred to as administrative (cultural or man-made) were removed from GNIS: airport, bridge, building, cemetery, church, dam, forest, harbor, hospital, mine, oilfield, park, post office, reserve, school, tower, trail, tunnel, and well. Some administrative feature data are maintained in other The National Map data themes.","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/58912e85-25c9-4824-ada6-135a1418c7b2","harvest_record_raw":"https://catalog.data.gov/harvest_record/58912e85-25c9-4824-ada6-135a1418c7b2/raw","has_download":true,"has_spatial":false,"identifier":"https://data.iowa.gov/catalog/dataset/650","keyword":["geographic names","natural features"],"last_harvested_date":"2026-09-05T19:14:15.831119","organization":{"aliases":["ia"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"2efac508-2a39-46d4-8d0c-e034d17e928f","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/state_IA.png","name":"State of Iowa","organization_type":"State Government","slug":"iowa"},"parent_identifier":null,"popularity":6,"publisher":"Data Hub Administration","slug":"iowa-geographic-names","spatial_centroid":null,"spatial_shape":null,"theme":["Infrastructure & Environment"],"title":"Iowa Geographic Names","type":"dataset"},{"_score":10.269945,"_sort":[1788635427562,10.269945,2,"3e06019b-49df-4465-826b-e2cdfd526c08"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Ryan F. Thompson","hasEmail":"mailto:rcthomps@usgs.gov"},"description":"This data set contains land surface elevations on dry and wadeable portions of transects for \npre-construction hydrographic surveys on the Missouri River below Gavins Point Dam for the \nEmergent Sandbar Habitat construction project near River Mile 761.4.  Data tie- ins to local \nbenchmarks also are included","distribution":[{"@type":"dcat:Distribution","accessURL":"https://water.usgs.gov/GIS/dsdl/dn_pre_gps.zip","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.ef9f62e5-57fc-4735-a1eb-52ee4c12dab1.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_ef9f62e5-57fc-4735-a1eb-52ee4c12dab1","keyword":["Hydrographic Survey","USGS:ef9f62e5-57fc-4735-a1eb-52ee4c12dab1","environment","geoscientificInformation","inlandWaters"],"modified":"2020-11-17T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-97.230886, 42.651279, -96.582338, 42.966037","theme":["geospatial"],"title":"GPS data collected for preconstruction hydrographic surveys of Missouri River downstream from Gavins Point Dam near river mile 761.4"},"description":"This data set contains land surface elevations on dry and wadeable portions of transects for \npre-construction hydrographic surveys on the Missouri River below Gavins Point Dam for the \nEmergent Sandbar Habitat construction project near River Mile 761.4.  Data tie- ins to local \nbenchmarks also are included","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/f89fbe27-1068-4911-84b3-b20a34a3d1bb","harvest_record_raw":"https://catalog.data.gov/harvest_record/f89fbe27-1068-4911-84b3-b20a34a3d1bb/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_ef9f62e5-57fc-4735-a1eb-52ee4c12dab1","keyword":["Hydrographic Survey","USGS:ef9f62e5-57fc-4735-a1eb-52ee4c12dab1","environment","geoscientificInformation","inlandWaters"],"last_harvested_date":"2026-09-05T19:10:27.562290","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":2,"publisher":"U.S. Geological Survey","slug":"gps-data-collected-for-preconstruction-hydrographic-surveys-of-missouri-river-downstream-f","spatial_centroid":{"lat":42.777182200000006,"lon":-96.9714668},"spatial_shape":{"coordinates":[[[-97.230886,42.651279],[-97.230886,42.966037],[-96.582338,42.966037],[-96.582338,42.651279],[-97.230886,42.651279]]],"type":"Polygon"},"theme":["geospatial"],"title":"GPS data collected for preconstruction hydrographic surveys of Missouri River downstream from Gavins Point Dam near river mile 761.4","type":"dataset"},{"_score":12.243286,"_sort":[1788635372877,12.243286,0,"610744f6-e148-447a-ae3c-220f4452d0d5"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Kenneth G. Boykin","hasEmail":"mailto:kboykin@nmsu.edu"},"description":"This dataset contains the result of the bioclimatic-envelope modeling of the two reptile species -- Rio Grande Cooter (Pseudemys gorzugi) and Gray-Checkered Whiptail (Aspidoscelis dixoni) -- in the South Central US using the downscaled data provided by WorldClim.  We used five species distribution models (SDM) including Generalized Linear Model, Random Forest, Boosted Regression Tree, Maxent, and Multivariate Adaptive Regression Splines (MARS) and ensembles to develop the present day distributions of the species based on climate-driven models alone.  We then projected future distributions of the species using data from four climate models: Community Climate System Model version 4 (CCSM4), Hadley Centre Global Environment Model version 2-Earth System (HadGEM2-ES), Model for Interdisciplinary Research on Climate version 5 (MIROC5), and Max Planck Institute Earth System Model, low resolution (MPI-ESM-LR).  We ran the climate models according to two greenhouse gas concentration pathways (RCP2.6 and RCP8.5).  Datasets in this file are the results for models RCP2.6 and RCP8.5 for the years 2050 and 2070.  It shows a comparison of ensembles of suitable bioclimatic conditions between present day and future day.  The dataset shows areas where ensembles agree and suitable conditions are stable (stable represented in green), future ensemble projects new suitable conditions (gain represented in yellow), present ensemble may be converted to unsuitable in the future (loss represented in red), and areas where conditions are unsuitable in the future (non represented in gray).","distribution":[{"@type":"dcat:Distribution","accessURL":"http://doi.org/10.5066/F7XS5SJH","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.583324a0e4b046f05f211a7d.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_583324a0e4b046f05f211a7d","keyword":["Aspidoscelis dixoni","Gray-Checkered Whiptail","Pseudemys gorzugi","Rio Grande Cooter","USGS:583324a0e4b046f05f211a7d","bioclimatic-envelope","biota","climatologyMeteorologyAtmosphere","geospatial datasets","herpetofauna","modeling"],"modified":"2026-09-03T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-112.586128217, 31.332172208, -106.486128241, 35.4988388585","theme":["geospatial"],"title":"Projected future bioclimate-envelope suitability for reptile species in South Central USA"},"description":"This dataset contains the result of the bioclimatic-envelope modeling of the two reptile species -- Rio Grande Cooter (Pseudemys gorzugi) and Gray-Checkered Whiptail (Aspidoscelis dixoni) -- in the South Central US using the downscaled data provided by WorldClim.  We used five species distribution models (SDM) including Generalized Linear Model, Random Forest, Boosted Regression Tree, Maxent, and Multivariate Adaptive Regression Splines (MARS) and ensembles to develop the present day distributions of the species based on climate-driven models alone.  We then projected future distributions of the species using data from four climate models: Community Climate System Model version 4 (CCSM4), Hadley Centre Global Environment Model version 2-Earth System (HadGEM2-ES), Model for Interdisciplinary Research on Climate version 5 (MIROC5), and Max Planck Institute Earth System Model, low resolution (MPI-ESM-LR).  We ran the climate models according to two greenhouse gas concentration pathways (RCP2.6 and RCP8.5).  Datasets in this file are the results for models RCP2.6 and RCP8.5 for the years 2050 and 2070.  It shows a comparison of ensembles of suitable bioclimatic conditions between present day and future day.  The dataset shows areas where ensembles agree and suitable conditions are stable (stable represented in green), future ensemble projects new suitable conditions (gain represented in yellow), present ensemble may be converted to unsuitable in the future (loss represented in red), and areas where conditions are unsuitable in the future (non represented in gray).","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/3b46a8f6-e3ee-47b3-a24e-ce90d4093d13","harvest_record_raw":"https://catalog.data.gov/harvest_record/3b46a8f6-e3ee-47b3-a24e-ce90d4093d13/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_583324a0e4b046f05f211a7d","keyword":["Aspidoscelis dixoni","Gray-Checkered Whiptail","Pseudemys gorzugi","Rio Grande Cooter","USGS:583324a0e4b046f05f211a7d","bioclimatic-envelope","biota","climatologyMeteorologyAtmosphere","geospatial datasets","herpetofauna","modeling"],"last_harvested_date":"2026-09-05T19:09:32.877056","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":0,"publisher":"U.S. Geological Survey","slug":"projected-future-bioclimate-envelope-suitability-for-reptile-species-in-south-central-usa","spatial_centroid":{"lat":32.9988388682,"lon":-110.14612822659998},"spatial_shape":{"coordinates":[[[-112.586128217,31.332172208],[-112.586128217,35.4988388585],[-106.486128241,35.4988388585],[-106.486128241,31.332172208],[-112.586128217,31.332172208]]],"type":"Polygon"},"theme":["geospatial"],"title":"Projected future bioclimate-envelope suitability for reptile species in South Central USA","type":"dataset"},{"_score":7.9205317,"_sort":[1788635297963,7.9205317,4,"57a06078-3313-49c0-8385-250e691c3ae8"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Philp T. Harte","hasEmail":"mailto:ptharte@usgs.gov"},"description":"The U.S. Geological Survey, in cooperation with the U.S. Environmental Protection Agency and\nthe New Hampshire Department of Environmental Services, developed a model for used with \nMODFLOW-2005 and MODPATH5 to evaluate groundwater flow and advective transport under\npre- and post-remediation conditions in the crystalline-rock aquifer in the vicinity of the Savage\nMunicipal Water-Supply Well Superfund site Milford, New Hampshire. In addition, a previously\ndeveloped model (https://doi.org/10.3133/sir20045176 and https://doi.org/10.3133/ofr20121079)\nwas used with MOC3D to evaluate the solute-transport of tetrachloroethylene (PCE). In 2010 \nPCE, a chlorinated volatile organic compound, was detected in groundwater from monitoring \nwells tapping the deep (more than 300 feet below land surface) fractures in a crystalline-rock \naquifer. The crystalline-rock aquifer underlies the Milford-Souhegan glacial-drift (MSGD) aquifer\n(a high water-producing aquifer) and the Savage Municipal Water-Supply Well Superfund site. \nResidential water-supply wells are within one-quarter of a mile of the PCE-contaminated \nmonitoring wells and many are likely installed in similar rock types and formations as those of\nthe monitoring wells. The need to understand and quantify flow and transport in the crystalline-\nrock aquifer is crucial in assessing strategies for remediation. The current, area-wide model \nsimulates flow in the crystalline-rock aquifer and covers a much larger area than previous models\nwith the goal of improving the computation of groundwater flow from distal locations to the \nresidential wells and the area. This USGS data release contains all of the input and output files\n for the simulations described in the associated model documentation report \n(https://doi.org/10.3133/sir20205137).","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/F7J102FK","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.226705a8-2a0e-4dda-8e36-84d2074d94c5.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_226705a8-2a0e-4dda-8e36-84d2074d94c5","keyword":["Groundwater","Groundwater Model","InlandWaters","MOC3D","MODFLOW-2005","MODPATH","Milford","Milford-Souhegan River Valley","New Hampshire","Savage Municipal Water Supply Well Superfund site","Solute transport","USGS:226705a8-2a0e-4dda-8e36-84d2074d94c5","environment","geoscientificInformation","inlandWaters","remediation","usgsgroundwatermodel"],"modified":"2021-11-10T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-71.761976, 42.800697, -71.642849, 42.889263","theme":["geospatial"],"title":"MODFLOW-2005, MODPATH, and MOC3D used for groundwater flow simulation, pathlines analysis, and solute transport in the crystalline-rock aquifer in the vicinity of the Savage Municipal Water-Supply Well Superfund Site, Milford, New Hampshire"},"description":"The U.S. Geological Survey, in cooperation with the U.S. Environmental Protection Agency and\nthe New Hampshire Department of Environmental Services, developed a model for used with \nMODFLOW-2005 and MODPATH5 to evaluate groundwater flow and advective transport under\npre- and post-remediation conditions in the crystalline-rock aquifer in the vicinity of the Savage\nMunicipal Water-Supply Well Superfund site Milford, New Hampshire. In addition, a previously\ndeveloped model (https://doi.org/10.3133/sir20045176 and https://doi.org/10.3133/ofr20121079)\nwas used with MOC3D to evaluate the solute-transport of tetrachloroethylene (PCE). In 2010 \nPCE, a chlorinated volatile organic compound, was detected in groundwater from monitoring \nwells tapping the deep (more than 300 feet below land surface) fractures in a crystalline-rock \naquifer. The crystalline-rock aquifer underlies the Milford-Souhegan glacial-drift (MSGD) aquifer\n(a high water-producing aquifer) and the Savage Municipal Water-Supply Well Superfund site. \nResidential water-supply wells are within one-quarter of a mile of the PCE-contaminated \nmonitoring wells and many are likely installed in similar rock types and formations as those of\nthe monitoring wells. The need to understand and quantify flow and transport in the crystalline-\nrock aquifer is crucial in assessing strategies for remediation. The current, area-wide model \nsimulates flow in the crystalline-rock aquifer and covers a much larger area than previous models\nwith the goal of improving the computation of groundwater flow from distal locations to the \nresidential wells and the area. This USGS data release contains all of the input and output files\n for the simulations described in the associated model documentation report \n(https://doi.org/10.3133/sir20205137).","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/c9863779-bab1-4982-bd31-f5f9c5e3b8d7","harvest_record_raw":"https://catalog.data.gov/harvest_record/c9863779-bab1-4982-bd31-f5f9c5e3b8d7/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_226705a8-2a0e-4dda-8e36-84d2074d94c5","keyword":["Groundwater","Groundwater Model","InlandWaters","MOC3D","MODFLOW-2005","MODPATH","Milford","Milford-Souhegan River Valley","New Hampshire","Savage Municipal Water Supply Well Superfund site","Solute transport","USGS:226705a8-2a0e-4dda-8e36-84d2074d94c5","environment","geoscientificInformation","inlandWaters","remediation","usgsgroundwatermodel"],"last_harvested_date":"2026-09-05T19:08:17.963121","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":4,"publisher":"U.S. Geological Survey","slug":"modflow-2005-modpath-and-moc3d-used-for-groundwater-flow-simulation-pathlines-analysis-and","spatial_centroid":{"lat":42.8361234,"lon":-71.7143252},"spatial_shape":{"coordinates":[[[-71.761976,42.800697],[-71.761976,42.889263],[-71.642849,42.889263],[-71.642849,42.800697],[-71.761976,42.800697]]],"type":"Polygon"},"theme":["geospatial"],"title":"MODFLOW-2005, MODPATH, and MOC3D used for groundwater flow simulation, pathlines analysis, and solute transport in the crystalline-rock aquifer in the vicinity of the Savage Municipal Water-Supply Well Superfund Site, Milford, New Hampshire","type":"dataset"},{"_score":8.764525,"_sort":[1788635090300,8.764525,1,"e1cf63ea-cac7-49f0-be33-45dd67b5d604"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Luke Winslow","hasEmail":"mailto:lwinslow@usgs.gov"},"description":"It is well recognized that the climate is warming in response to anthropogenic emission of greenhouse gases. Over the last decade, this has had a warming effect on lakes. Water clarity is also known to effect water temperature in lakes. What is unclear is how a warming climate might interact with changes in water clarity in lakes. As part of a project at the USGS Office of Water Information, several water clarity scenarios were simulated for lakes in Wisconsin to examine how changing water clarity interacts with climate change to affect lake temperatures at a broad scale.\nThis data set contains the following parameters: year, WBIC, durStrat, max_schmidt_stability, mean_schmidt_stability_JAS, mean_schmidt_stability_July, SthermoD_mean_JAS, SthermoD_mean, lake_average_temp, peak_lake_average_temp, lake_average_temp_JAS, mean_epi_temp, mean_hypo_temp, mean_surf_temp, mean_bottom_temp, peak_surf_temp, peak_bottom_temp, mean_surf_temp_JAS, mean_bottom_temp_JAS, mean_bottom_temp_365, mean_surf_temp_365, mean_1m_temp, mean_surf_JA, GDD_wtr_5c, GDD_wtr_10c, volume_mean_m_3, simulation_length_days, mean_volumetric_temp, kd, out_val calculated for 2210 lakes.","distribution":[{"@type":"dcat:Distribution","accessURL":"http://dx.doi.org/10.5066/F7028PN4","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.57473491e4b07e28b663d822.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_57473491e4b07e28b663d822","keyword":["007","012","US","USGS:57473491e4b07e28b663d822","United States","WI","Wisconsin","climate change","environment","hydrodynamic model","inlandWaters","lakes","limnology","water clarity","water quality","water temperature"],"modified":"2026-09-03T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-92.91, 42.48, -86.75, 47.54","theme":["geospatial"],"title":"Wisconsin Lake Temperature Metrics Stable Clarity"},"description":"It is well recognized that the climate is warming in response to anthropogenic emission of greenhouse gases. Over the last decade, this has had a warming effect on lakes. Water clarity is also known to effect water temperature in lakes. What is unclear is how a warming climate might interact with changes in water clarity in lakes. As part of a project at the USGS Office of Water Information, several water clarity scenarios were simulated for lakes in Wisconsin to examine how changing water clarity interacts with climate change to affect lake temperatures at a broad scale.\nThis data set contains the following parameters: year, WBIC, durStrat, max_schmidt_stability, mean_schmidt_stability_JAS, mean_schmidt_stability_July, SthermoD_mean_JAS, SthermoD_mean, lake_average_temp, peak_lake_average_temp, lake_average_temp_JAS, mean_epi_temp, mean_hypo_temp, mean_surf_temp, mean_bottom_temp, peak_surf_temp, peak_bottom_temp, mean_surf_temp_JAS, mean_bottom_temp_JAS, mean_bottom_temp_365, mean_surf_temp_365, mean_1m_temp, mean_surf_JA, GDD_wtr_5c, GDD_wtr_10c, volume_mean_m_3, simulation_length_days, mean_volumetric_temp, kd, out_val calculated for 2210 lakes.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/63cec2ed-5be2-4b11-9fd4-2e254fd79f86","harvest_record_raw":"https://catalog.data.gov/harvest_record/63cec2ed-5be2-4b11-9fd4-2e254fd79f86/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_57473491e4b07e28b663d822","keyword":["007","012","US","USGS:57473491e4b07e28b663d822","United States","WI","Wisconsin","climate change","environment","hydrodynamic model","inlandWaters","lakes","limnology","water clarity","water quality","water temperature"],"last_harvested_date":"2026-09-05T19:04:50.300138","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":1,"publisher":"U.S. Geological Survey","slug":"wisconsin-lake-temperature-metrics-stable-clarity","spatial_centroid":{"lat":44.504,"lon":-90.446},"spatial_shape":{"coordinates":[[[-92.91,42.48],[-92.91,47.54],[-86.75,47.54],[-86.75,42.48],[-92.91,42.48]]],"type":"Polygon"},"theme":["geospatial"],"title":"Wisconsin Lake Temperature Metrics Stable Clarity","type":"dataset"},{"_score":10.350627,"_sort":[1788635017679,10.350627,5,"55601e8a-b8d0-401d-937c-f30f81edf947"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Ryan F. Thompson","hasEmail":"mailto:rcthomps@usgs.gov"},"description":"This geospatial data set contains an interpolated 3-D surface or, triangulated-irregular network (TIN), of \nthe change in elevation, in feet, of the substrate between cross-sections 22 and 35 following construction \nof Emergent Sandbar Habitat near River Mile 770.  The surface was generated from points collected by \nthe echosounder and real-time kinematic (RTK) GPS on cross-sections in the downstream project reach \nsurrounding the construction area at River Mile 770 below Gavins Point Dam on the Missouri River in \nSouth Dakota before and after construction of the sandbar.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://water.usgs.gov/lookup/getspatial?ofr07-1056_up_diff_tin","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.bab471f5-254a-4619-a308-17af1ab39dd0.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_bab471f5-254a-4619-a308-17af1ab39dd0","keyword":["Hydrographic Survey","USGS:bab471f5-254a-4619-a308-17af1ab39dd0","environment","geoscientificInformation","inlandWaters"],"modified":"2020-11-17T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-96.876334, 42.712792, -96.851104, 42.732505","theme":["geospatial"],"title":"Difference betweem postconstruction and preconstruction land surface elevation tins on the Missouri River Downstream from Gavins Point Dam near River Mile 769.8."},"description":"This geospatial data set contains an interpolated 3-D surface or, triangulated-irregular network (TIN), of \nthe change in elevation, in feet, of the substrate between cross-sections 22 and 35 following construction \nof Emergent Sandbar Habitat near River Mile 770.  The surface was generated from points collected by \nthe echosounder and real-time kinematic (RTK) GPS on cross-sections in the downstream project reach \nsurrounding the construction area at River Mile 770 below Gavins Point Dam on the Missouri River in \nSouth Dakota before and after construction of the sandbar.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/29dbc513-820f-4bf3-ae53-4e70428d8725","harvest_record_raw":"https://catalog.data.gov/harvest_record/29dbc513-820f-4bf3-ae53-4e70428d8725/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_bab471f5-254a-4619-a308-17af1ab39dd0","keyword":["Hydrographic Survey","USGS:bab471f5-254a-4619-a308-17af1ab39dd0","environment","geoscientificInformation","inlandWaters"],"last_harvested_date":"2026-09-05T19:03:37.679258","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":5,"publisher":"U.S. Geological Survey","slug":"difference-betweem-postconstruction-and-preconstruction-land-surface-elevation-tins-on-the-4e0f6","spatial_centroid":{"lat":42.7206772,"lon":-96.866242},"spatial_shape":{"coordinates":[[[-96.876334,42.712792],[-96.876334,42.732505],[-96.851104,42.732505],[-96.851104,42.712792],[-96.876334,42.712792]]],"type":"Polygon"},"theme":["geospatial"],"title":"Difference betweem postconstruction and preconstruction land surface elevation tins on the Missouri River Downstream from Gavins Point Dam near River Mile 769.8.","type":"dataset"},{"_score":10.274181,"_sort":[1788634959662,10.274181,1,"da73e18a-7c5e-401a-bdb1-0c3d66eb2ccc"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Ryan F. Thompson","hasEmail":"mailto:rcthomps@usgs.gov"},"description":"This geospatial data set contains the points collected by the echosounder on transects in the upstream project \nreach surrounding the construction area at River Mile 770.0 below Gavins Point Dam on the Missouri River in \nSouth Dakota.  This survey provides channel cross sections approximately every 500 feet prior to construction \nof Emergent Sandbar Habitat near River Mile 770.0","distribution":[{"@type":"dcat:Distribution","accessURL":"https://water.usgs.gov/GIS/dsdl/up_pre_bathy.zip","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.8c43e591-33d3-4be8-8685-9334db3e0c17.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_8c43e591-33d3-4be8-8685-9334db3e0c17","keyword":["Hydrographic Survey","USGS:8c43e591-33d3-4be8-8685-9334db3e0c17","environment","geoscientificInformation","inlandWaters"],"modified":"2020-11-17T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-96.912245, 42.701375, -96.821919, 42.736242","theme":["geospatial"],"title":"Bathymetry data for the pre-construction survey of the Emergent Sandbar Habitat project at river mile 769.8 downstream from Gavins Point Dam on the Missouri River."},"description":"This geospatial data set contains the points collected by the echosounder on transects in the upstream project \nreach surrounding the construction area at River Mile 770.0 below Gavins Point Dam on the Missouri River in \nSouth Dakota.  This survey provides channel cross sections approximately every 500 feet prior to construction \nof Emergent Sandbar Habitat near River Mile 770.0","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/b77e784d-cf00-4500-a817-4c48adba5546","harvest_record_raw":"https://catalog.data.gov/harvest_record/b77e784d-cf00-4500-a817-4c48adba5546/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_8c43e591-33d3-4be8-8685-9334db3e0c17","keyword":["Hydrographic Survey","USGS:8c43e591-33d3-4be8-8685-9334db3e0c17","environment","geoscientificInformation","inlandWaters"],"last_harvested_date":"2026-09-05T19:02:39.662963","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":1,"publisher":"U.S. Geological Survey","slug":"bathymetry-data-for-the-pre-construction-survey-of-the-emergent-sandbar-habitat-project-at-ba1fa","spatial_centroid":{"lat":42.7153218,"lon":-96.8761146},"spatial_shape":{"coordinates":[[[-96.912245,42.701375],[-96.912245,42.736242],[-96.821919,42.736242],[-96.821919,42.701375],[-96.912245,42.701375]]],"type":"Polygon"},"theme":["geospatial"],"title":"Bathymetry data for the pre-construction survey of the Emergent Sandbar Habitat project at river mile 769.8 downstream from Gavins Point Dam on the Missouri River.","type":"dataset"},{"_score":10.143366,"_sort":[1788634909493,10.143366,3,"1d2dba95-81b9-4104-9d66-3e588ee978ec"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Ryan F. Thompson","hasEmail":"mailto:rcthomps@usgs.gov"},"description":"This geospatial data set contains an interpolated 3-D surface or, triangulated-irregular network \n(TIN), of the substrate surface between cross-sections 23 and 39 following construction of \nEmergent Sandbar Habitat near River Mile 761.4.  The surface was generated from points \ncollected by the echosounder and real-time kinematic (RTK) GPS on cross-sections in the \ndownstream project reach surrounding the construction area at River Mile 761.4 below \nGavins Point Dam on the Missouri River in South Dakota.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://water.usgs.gov/GIS/dsdl/dn_post_tin.zip","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.27c54785-3cfd-4ccd-a2d3-c3f47c102e47.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_27c54785-3cfd-4ccd-a2d3-c3f47c102e47","keyword":["Hydrographic Survey","USGS:27c54785-3cfd-4ccd-a2d3-c3f47c102e47","environment","geoscientificInformation","inlandWaters"],"modified":"2020-11-17T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-96.769522, 42.657361, -96.739372, 42.666935","theme":["geospatial"],"title":"Postconstruction tin of land surface on the Missouri River downstream from Gavins Point Dam near River Mile 761.4"},"description":"This geospatial data set contains an interpolated 3-D surface or, triangulated-irregular network \n(TIN), of the substrate surface between cross-sections 23 and 39 following construction of \nEmergent Sandbar Habitat near River Mile 761.4.  The surface was generated from points \ncollected by the echosounder and real-time kinematic (RTK) GPS on cross-sections in the \ndownstream project reach surrounding the construction area at River Mile 761.4 below \nGavins Point Dam on the Missouri River in South Dakota.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/e11a0043-4c18-4814-8e92-52aa343c9620","harvest_record_raw":"https://catalog.data.gov/harvest_record/e11a0043-4c18-4814-8e92-52aa343c9620/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_27c54785-3cfd-4ccd-a2d3-c3f47c102e47","keyword":["Hydrographic Survey","USGS:27c54785-3cfd-4ccd-a2d3-c3f47c102e47","environment","geoscientificInformation","inlandWaters"],"last_harvested_date":"2026-09-05T19:01:49.493300","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":3,"publisher":"U.S. Geological Survey","slug":"postconstruction-tin-of-land-surface-on-the-missouri-river-downstream-from-gavins-point-da-5ef18","spatial_centroid":{"lat":42.661190600000005,"lon":-96.757462},"spatial_shape":{"coordinates":[[[-96.769522,42.657361],[-96.769522,42.666935],[-96.739372,42.666935],[-96.739372,42.657361],[-96.769522,42.657361]]],"type":"Polygon"},"theme":["geospatial"],"title":"Postconstruction tin of land surface on the Missouri River downstream from Gavins Point Dam near River Mile 761.4","type":"dataset"},{"_score":8.101959,"_sort":[1788634881825,8.101959,0,"f3d26010-cccb-46f4-9506-001aaf0b7c9f"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Climate Adaptation Science Centers","hasEmail":"mailto:casc-data@usgs.gov"},"description":"This is a spatially-explicit state-and-transition simulation model of rangeland vegetation dynamics in the southwest South Dakota study site. The study site encompasses part of multiple jurisdictions, including Badlands National Park, Buffalo Gap National Grasslands, and Pine Ridge Indian Reservation. It represents key vegetation types, grazing, exotic plants, fire, and the effects of climate and management on rangeland productivity and composition (i.e., distribution of ecological community phases). The model was built using the ST-Sim software platform. \nFrom http://wiki.syncrosim.com/index.php?title=Main_Page: ST-Sim allows users to develop and run spatially-explicit, stochastic state-and-transition simulation models (STSMs) of vegetation change, and is designed to simulate and compare possible vegetation conditions across a landscape over time by considering the interaction between succession, disturbances and management. ST-Sim is the latest in a 20-year lineage of STSM development tools that includes the Vegetation Dynamics Development Tool (VDDT), the Tool for Exploratory Landscape Scenario Analysis (TELSA), and the Path Landscape Model (Path). ST-Sim is intended as an upgrade to Path: in addition to all of the previous Path features, ST-Sim also provides a new option to run raster-based, spatially-explicit simulations.","distribution":[{"@type":"dcat:Distribution","accessURL":"http://doi.org/10.5066/F7T1524X","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.58e7ae48e4b09da6799c0e55.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_58e7ae48e4b09da6799c0e55","keyword":["Badlands National Park","Bison","Buffalo Gap National Grassland","Grazing","Northern Great Plains","South Dakota","State-and-transition simulation model","USGS:58e7ae48e4b09da6799c0e55","cattle","climate change","environment","fires","geospatial datasets","invasive species","livestock","modeling","scenario planning"],"modified":"2026-09-03T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-103.1759, 43.1995, -101.4480, 44.0587","theme":["geospatial"],"title":"State-and-Transition Simulation Model of Rangeland Vegetation in Southwest South Dakota (1969-2050)"},"description":"This is a spatially-explicit state-and-transition simulation model of rangeland vegetation dynamics in the southwest South Dakota study site. The study site encompasses part of multiple jurisdictions, including Badlands National Park, Buffalo Gap National Grasslands, and Pine Ridge Indian Reservation. It represents key vegetation types, grazing, exotic plants, fire, and the effects of climate and management on rangeland productivity and composition (i.e., distribution of ecological community phases). The model was built using the ST-Sim software platform. \nFrom http://wiki.syncrosim.com/index.php?title=Main_Page: ST-Sim allows users to develop and run spatially-explicit, stochastic state-and-transition simulation models (STSMs) of vegetation change, and is designed to simulate and compare possible vegetation conditions across a landscape over time by considering the interaction between succession, disturbances and management. ST-Sim is the latest in a 20-year lineage of STSM development tools that includes the Vegetation Dynamics Development Tool (VDDT), the Tool for Exploratory Landscape Scenario Analysis (TELSA), and the Path Landscape Model (Path). ST-Sim is intended as an upgrade to Path: in addition to all of the previous Path features, ST-Sim also provides a new option to run raster-based, spatially-explicit simulations.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/27a06cbb-eee2-4d7b-8bf4-10a849a8e556","harvest_record_raw":"https://catalog.data.gov/harvest_record/27a06cbb-eee2-4d7b-8bf4-10a849a8e556/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_58e7ae48e4b09da6799c0e55","keyword":["Badlands National Park","Bison","Buffalo Gap National Grassland","Grazing","Northern Great Plains","South Dakota","State-and-transition simulation model","USGS:58e7ae48e4b09da6799c0e55","cattle","climate change","environment","fires","geospatial datasets","invasive species","livestock","modeling","scenario planning"],"last_harvested_date":"2026-09-05T19:01:21.825628","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":0,"publisher":"U.S. Geological Survey","slug":"state-and-transition-simulation-model-of-rangeland-vegetation-in-southwest-south-1969-2050","spatial_centroid":{"lat":43.54318,"lon":-102.48473999999999},"spatial_shape":{"coordinates":[[[-103.1759,43.1995],[-103.1759,44.0587],[-101.448,44.0587],[-101.448,43.1995],[-103.1759,43.1995]]],"type":"Polygon"},"theme":["geospatial"],"title":"State-and-Transition Simulation Model of Rangeland Vegetation in Southwest South Dakota (1969-2050)","type":"dataset"},{"_score":9.144231,"_sort":[1788634840027,9.144231,2,"d1a22498-ea4e-4e99-9e84-48b94536504d"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Thomas J. Mack","hasEmail":"mailto:tjmack@usgs.gov"},"description":"A numerical groundwater flow model using MODFLOW-2005 was developed to examine \npredevelopment groundwater flow in eastern Abu Dhabi Emirate, United Arab Emirates. \nThe model was calibrated to conditions before the 1960s, the period before modern \npumping began. The model was used to evaluate the regional water budget and 4 \npotential recharge scenarios. This USGS data release contains all of the input and \noutput files for the simulations described in the associated model documentation report \n(https://doi.org/10.3133/sir20185158). This data release also includes input and output \ndata files for sensitivity and scenarios simulations, and MODFLOW-2015 source code.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P9ZWZISB","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.352bbf07-a8e1-4083-be31-aded7332e8fe.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_352bbf07-a8e1-4083-be31-aded7332e8fe","keyword":["Abu Dhabi","Groundwater","Groundwater Model","MODFLOW-2005","USGS:352bbf07-a8e1-4083-be31-aded7332e8fe","United Arab Emirates","environment","geoscientificInformation","inlandWaters","usgsgroundwatermodel"],"modified":"2020-11-17T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-80.78, 25.919, -80.018, 26.487","theme":["geospatial"],"title":"MODFLOW-2005 Groundwater Flow Model to Simulate Predevelopment Groundwater Flow in the Eastern Abu Dhabi Emirate, United Arab Emirates"},"description":"A numerical groundwater flow model using MODFLOW-2005 was developed to examine \npredevelopment groundwater flow in eastern Abu Dhabi Emirate, United Arab Emirates. \nThe model was calibrated to conditions before the 1960s, the period before modern \npumping began. The model was used to evaluate the regional water budget and 4 \npotential recharge scenarios. This USGS data release contains all of the input and \noutput files for the simulations described in the associated model documentation report \n(https://doi.org/10.3133/sir20185158). This data release also includes input and output \ndata files for sensitivity and scenarios simulations, and MODFLOW-2015 source code.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/3bba1820-ac19-4880-89b4-e0574ae68430","harvest_record_raw":"https://catalog.data.gov/harvest_record/3bba1820-ac19-4880-89b4-e0574ae68430/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_352bbf07-a8e1-4083-be31-aded7332e8fe","keyword":["Abu Dhabi","Groundwater","Groundwater Model","MODFLOW-2005","USGS:352bbf07-a8e1-4083-be31-aded7332e8fe","United Arab Emirates","environment","geoscientificInformation","inlandWaters","usgsgroundwatermodel"],"last_harvested_date":"2026-09-05T19:00:40.027689","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":2,"publisher":"U.S. Geological Survey","slug":"modflow-2005-groundwater-flow-model-to-simulate-predevelopment-groundwater-flow-in-the-eas","spatial_centroid":{"lat":26.1462,"lon":-80.4752},"spatial_shape":{"coordinates":[[[-80.78,25.919],[-80.78,26.487],[-80.018,26.487],[-80.018,25.919],[-80.78,25.919]]],"type":"Polygon"},"theme":["geospatial"],"title":"MODFLOW-2005 Groundwater Flow Model to Simulate Predevelopment Groundwater Flow in the Eastern Abu Dhabi Emirate, United Arab Emirates","type":"dataset"},{"_score":6.741436,"_sort":[1788634806676,6.741436,5,"ecff340e-3458-4575-be26-e3f864fadaec"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"U.S. Geological Survey, Alaska Science Center","hasEmail":"mailto:gs-ak_asc_datamanagers@usgs.gov"},"description":"This dataset contains fatty acid (FA) data expressed as mass percent of total FA for bearded seals, ringed seals and walrus. This is one of many datasets used in Bromaghin et al. 2016 (https://doi.org/10.1111/2041-210X.12456). These supplemental data were used in computer simulations to compare the bias of several quantitative fatty acid signature analysis (QFASA) estimators and develop recommendations regarding estimator selection.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/F7PR7T2W","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.ASC31.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_ASC31","keyword":["Alaska","Animals/Vertebrates","Arctic","Bearded seal","Bears","Biological informatics","Biota","Carnivores","Chukchi Sea","Coastal ecosystems","Diet composition","Diet estimation","Diets","Environment","Erignathus barbatus","Fatty Acids","Mammals","Marine ecosystems","Marine mammals","Pelagic habitat","Pinniped","Polar bear","Predator-prey","Pusa hispida","QFASA","Quantitative fatty acid signature analysis","Ringed seal","Seals/Sea lions/Walruses","USGS:ASC31","Ursus maritimus","Wildlife"],"modified":"2024-11-30T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-173.0, 65.0, -155.0, 72.0","theme":["geospatial"],"title":"Assessing the Robustness of Quantitative Fatty Acid Signature Analysis to Assumption Violations (Supplementary Data)"},"description":"This dataset contains fatty acid (FA) data expressed as mass percent of total FA for bearded seals, ringed seals and walrus. This is one of many datasets used in Bromaghin et al. 2016 (https://doi.org/10.1111/2041-210X.12456). These supplemental data were used in computer simulations to compare the bias of several quantitative fatty acid signature analysis (QFASA) estimators and develop recommendations regarding estimator selection.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/90706ff6-c634-4205-99b0-b496c559c717","harvest_record_raw":"https://catalog.data.gov/harvest_record/90706ff6-c634-4205-99b0-b496c559c717/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_ASC31","keyword":["Alaska","Animals/Vertebrates","Arctic","Bearded seal","Bears","Biological informatics","Biota","Carnivores","Chukchi Sea","Coastal ecosystems","Diet composition","Diet estimation","Diets","Environment","Erignathus barbatus","Fatty Acids","Mammals","Marine ecosystems","Marine mammals","Pelagic habitat","Pinniped","Polar bear","Predator-prey","Pusa hispida","QFASA","Quantitative fatty acid signature analysis","Ringed seal","Seals/Sea lions/Walruses","USGS:ASC31","Ursus maritimus","Wildlife"],"last_harvested_date":"2026-09-05T19:00:06.676583","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":5,"publisher":"U.S. Geological Survey","slug":"assessing-the-robustness-of-quantitative-fatty-acid-signature-analysis-to-assumption-viola","spatial_centroid":{"lat":67.8,"lon":-165.8},"spatial_shape":{"coordinates":[[[-173.0,65.0],[-173.0,72.0],[-155.0,72.0],[-155.0,65.0],[-173.0,65.0]]],"type":"Polygon"},"theme":["geospatial"],"title":"Assessing the Robustness of Quantitative Fatty Acid Signature Analysis to Assumption Violations (Supplementary Data)","type":"dataset"},{"_score":8.472546,"_sort":[1788634720058,8.472546,0,"190fdbec-3b1d-4cf1-b631-18ba9ac18637"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Toni Lyn Morelli","hasEmail":"mailto:tmorelli@usgs.gov"},"description":"We developed maps of of projected present and future climate niches for 9 focal species (including 4 plants [common bearberry, Bebb's sedge, highland rush, and shrubby five-fingers], 2 birds [grasshopper sparrow and black-throated green warbler], and 3 salamanders [blue-spotted salamander, jefferson salamander, and marbled salamander]) to identify climate change refugia, areas on the landscape relatively buffered from contemporary climate change. Climate change refugia were considered to be those areas projected to be climatically suitable now and in 2080. These maps are intended to inform management plans for refugia conservation throughout the northeastern United States, especially in protected areas including national parks, and can be used to support both climate adaptation efforts for focal species in protected areas individually and facilitate cross-boundary collaborations as species ranges shift across parks in the Northeast.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P16X6UKM","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.3b355ab9-bf4c-4b6c-a1c8-dab89366d5c7.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_3b355ab9-bf4c-4b6c-a1c8-dab89366d5c7","keyword":["USGS:3b355ab9-bf4c-4b6c-a1c8-dab89366d5c7","biota","climate adaptation","climate change","climate change refugia","climate envelope","climate niche","effects of climate change","environment","geospatial datasets","species range shifts"],"modified":"2026-09-03T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-83.6792, 34.5292, -66.4792, 49.3625","theme":["geospatial"],"title":"Maps of the climate envelopes of 9 focal species in the northeastern United States in 2020 and 2080 under RCP 8.5"},"description":"We developed maps of of projected present and future climate niches for 9 focal species (including 4 plants [common bearberry, Bebb's sedge, highland rush, and shrubby five-fingers], 2 birds [grasshopper sparrow and black-throated green warbler], and 3 salamanders [blue-spotted salamander, jefferson salamander, and marbled salamander]) to identify climate change refugia, areas on the landscape relatively buffered from contemporary climate change. Climate change refugia were considered to be those areas projected to be climatically suitable now and in 2080. These maps are intended to inform management plans for refugia conservation throughout the northeastern United States, especially in protected areas including national parks, and can be used to support both climate adaptation efforts for focal species in protected areas individually and facilitate cross-boundary collaborations as species ranges shift across parks in the Northeast.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/2f5e0bf4-0d8f-4ccf-99ab-ee261230e949","harvest_record_raw":"https://catalog.data.gov/harvest_record/2f5e0bf4-0d8f-4ccf-99ab-ee261230e949/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_3b355ab9-bf4c-4b6c-a1c8-dab89366d5c7","keyword":["USGS:3b355ab9-bf4c-4b6c-a1c8-dab89366d5c7","biota","climate adaptation","climate change","climate change refugia","climate envelope","climate niche","effects of climate change","environment","geospatial datasets","species range shifts"],"last_harvested_date":"2026-09-05T18:58:40.058142","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":0,"publisher":"U.S. Geological Survey","slug":"maps-of-the-climate-envelopes-of-9-focal-species-in-the-northeastern-united-states-in-2020","spatial_centroid":{"lat":40.46252,"lon":-76.7992},"spatial_shape":{"coordinates":[[[-83.6792,34.5292],[-83.6792,49.3625],[-66.4792,49.3625],[-66.4792,34.5292],[-83.6792,34.5292]]],"type":"Polygon"},"theme":["geospatial"],"title":"Maps of the climate envelopes of 9 focal species in the northeastern United States in 2020 and 2080 under RCP 8.5","type":"dataset"},{"_score":10.038139,"_sort":[1788634478022,10.038139,1,"4c15edc0-6824-49d4-a200-c9b1af8d5e7f"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Ryan F. Thompson","hasEmail":"mailto:rcthomps@usgs.gov"},"description":"This data set contains land surface elevations on dry and wadeable portions of transects for the \nhydrographic surveys on the Missouri River below Gavins Point Dam near River Mile 769.8.  \nThis data provides land surface elevations of shallow-water, shore, and highbank for the \nMissouri River prior to construction of Emergent Sandbar Habitat.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://water.usgs.gov/GIS/dsdl/up_pre_gps.zip","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.985cf61c-0fe2-4ecb-abca-86e5089aaeff.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_985cf61c-0fe2-4ecb-abca-86e5089aaeff","keyword":["Hydrographic Survey","USGS:985cf61c-0fe2-4ecb-abca-86e5089aaeff","environment","geoscientificInformation","inlandWaters"],"modified":"2020-11-17T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-96.914945, 42.701005, -96.821300, 42.738139","theme":["geospatial"],"title":"GPS data collected for transects as part of the pre-construction survey at Emergent Sandbar Habitat site on the Missouri River near river mile 769.8"},"description":"This data set contains land surface elevations on dry and wadeable portions of transects for the \nhydrographic surveys on the Missouri River below Gavins Point Dam near River Mile 769.8.  \nThis data provides land surface elevations of shallow-water, shore, and highbank for the \nMissouri River prior to construction of Emergent Sandbar Habitat.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/128212b8-b291-4d8d-9394-2ffc1af28e27","harvest_record_raw":"https://catalog.data.gov/harvest_record/128212b8-b291-4d8d-9394-2ffc1af28e27/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_985cf61c-0fe2-4ecb-abca-86e5089aaeff","keyword":["Hydrographic Survey","USGS:985cf61c-0fe2-4ecb-abca-86e5089aaeff","environment","geoscientificInformation","inlandWaters"],"last_harvested_date":"2026-09-05T18:54:38.022425","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":1,"publisher":"U.S. Geological Survey","slug":"gps-data-collected-for-transects-as-part-of-the-pre-construction-survey-at-emergent-sandba","spatial_centroid":{"lat":42.715858600000004,"lon":-96.877487},"spatial_shape":{"coordinates":[[[-96.914945,42.701005],[-96.914945,42.738139],[-96.8213,42.738139],[-96.8213,42.701005],[-96.914945,42.701005]]],"type":"Polygon"},"theme":["geospatial"],"title":"GPS data collected for transects as part of the pre-construction survey at Emergent Sandbar Habitat site on the Missouri River near river mile 769.8","type":"dataset"},{"_score":11.204124,"_sort":[1788634357708,11.204124,0,"d4038ec1-2954-42c6-a812-d558e4a02fe6"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Kenneth G. Boykin","hasEmail":"mailto:kboykin@nmsu.edu"},"description":"This dataset contains the result of the bioclimatic-envelope modeling of the six mammal species -- (a) New Mexican Jumping Mouse (Zapus hudsonius luteus), (b) Northern Pygmy Mouse (Baiomys taylori), (c) Gunnison's Prairie Dog (Cynomys gunnisoni), (d) Black-tailed Prairie Dog (Cynomys ludovicianus), (e) American Pika (Ochotona princeps), and (e) Swift Fox (Vulpes velox) -- in the South Central US using the downscaled data provided by WorldClim.  We used five species distribution models (SDM) including Generalized Linear Model, Random Forest, Boosted Regression Tree, Maxent, and Multivariate Adaptive Regression Splines (MARS) and ensembles to develop the present day distributions of the species based on climate-driven models alone.  We then projected future distributions of the species using data from four climate models: Community Climate System Model version 4 (CCSM4), Hadley Centre Global Environment Model version 2-Earth System (HadGEM2-ES), Model for Interdisciplinary Research on Climate version 5 (MIROC5), and Max Planck Institute Earth System Model, low resolution (MPI-ESM-LR).  We ran the climate models according to two greenhouse gas concentration pathways (RCP2.6 and RCP8.5).  Datasets in this file are the results for models RCP2.6 and RCP8.5 for the years 2050 and 2070.  It shows a comparison of ensembles of suitable bioclimatic conditions between present day and future day.  The dataset shows areas where ensembles agree and suitable conditions are stable (stable represented in green), future ensemble projects new suitable conditions (gain represented in yellow), present ensemble may be converted to unsuitable in the future (loss represented in red), and areas where conditions are unsuitable in the future (non represented in gray).","distribution":[{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.583322bee4b046f05f211a6b.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_583322bee4b046f05f211a6b","keyword":["American Pika","Baiomys taylori","Black-tailed Prairie Dog","Cynomys gunnisoni","Cynomys ludovicianus","Gunnison's Prairie Dog","New Mexican Jumping Mouse","Northern Pygmy Mouse","Ochotona princeps","Swift Fox","USGS:583322bee4b046f05f211a6b","Vulpes velox","Zapus hudsonius luteus","bioclimatic-envelope","biota","climate change","climatologyMeteorologyAtmosphere","geospatial datasets","modeling"],"modified":"2026-09-03T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-112.5861, 31.3322, -106.4861, 35.4988","theme":["geospatial"],"title":"Projected future bioclimate-envelope suitability for mammal species in South Central USA"},"description":"This dataset contains the result of the bioclimatic-envelope modeling of the six mammal species -- (a) New Mexican Jumping Mouse (Zapus hudsonius luteus), (b) Northern Pygmy Mouse (Baiomys taylori), (c) Gunnison's Prairie Dog (Cynomys gunnisoni), (d) Black-tailed Prairie Dog (Cynomys ludovicianus), (e) American Pika (Ochotona princeps), and (e) Swift Fox (Vulpes velox) -- in the South Central US using the downscaled data provided by WorldClim.  We used five species distribution models (SDM) including Generalized Linear Model, Random Forest, Boosted Regression Tree, Maxent, and Multivariate Adaptive Regression Splines (MARS) and ensembles to develop the present day distributions of the species based on climate-driven models alone.  We then projected future distributions of the species using data from four climate models: Community Climate System Model version 4 (CCSM4), Hadley Centre Global Environment Model version 2-Earth System (HadGEM2-ES), Model for Interdisciplinary Research on Climate version 5 (MIROC5), and Max Planck Institute Earth System Model, low resolution (MPI-ESM-LR).  We ran the climate models according to two greenhouse gas concentration pathways (RCP2.6 and RCP8.5).  Datasets in this file are the results for models RCP2.6 and RCP8.5 for the years 2050 and 2070.  It shows a comparison of ensembles of suitable bioclimatic conditions between present day and future day.  The dataset shows areas where ensembles agree and suitable conditions are stable (stable represented in green), future ensemble projects new suitable conditions (gain represented in yellow), present ensemble may be converted to unsuitable in the future (loss represented in red), and areas where conditions are unsuitable in the future (non represented in gray).","distribution_titles":["Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/ac5f2efd-8a07-47bf-bcac-3f977a8b2f51","harvest_record_raw":"https://catalog.data.gov/harvest_record/ac5f2efd-8a07-47bf-bcac-3f977a8b2f51/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_583322bee4b046f05f211a6b","keyword":["American Pika","Baiomys taylori","Black-tailed Prairie Dog","Cynomys gunnisoni","Cynomys ludovicianus","Gunnison's Prairie Dog","New Mexican Jumping Mouse","Northern Pygmy Mouse","Ochotona princeps","Swift Fox","USGS:583322bee4b046f05f211a6b","Vulpes velox","Zapus hudsonius luteus","bioclimatic-envelope","biota","climate change","climatologyMeteorologyAtmosphere","geospatial datasets","modeling"],"last_harvested_date":"2026-09-05T18:52:37.708750","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":0,"publisher":"U.S. Geological Survey","slug":"projected-future-bioclimate-envelope-suitability-for-mammal-species-in-south-central-usa","spatial_centroid":{"lat":32.99884,"lon":-110.1461},"spatial_shape":{"coordinates":[[[-112.5861,31.3322],[-112.5861,35.4988],[-106.4861,35.4988],[-106.4861,31.3322],[-112.5861,31.3322]]],"type":"Polygon"},"theme":["geospatial"],"title":"Projected future bioclimate-envelope suitability for mammal species in South Central USA","type":"dataset"},{"_score":8.853937,"_sort":[1788634343328,8.853937,2,"e3548643-25f3-4a5b-a4fd-8457c75c4e4d"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Luke Winslow","hasEmail":"mailto:lwinslow@usgs.gov"},"description":"It is well recognized that the climate is warming in response to anthropogenic emission of greenhouse gases. Over the last decade, this has had a warming effect on lakes. Water clarity is also known to effect water temperature in lakes. What is unclear is how a warming climate might interact with changes in water clarity in lakes. As part of a project at the USGS Office of Water Information, several water clarity scenarios were simulated for lakes in Wisconsin to examine how changing water clarity interacts with climate change to affect lake temperatures at a broad scale.\nThis data set contains the following parameters: year, WBIC, durStrat, max_schmidt_stability, mean_schmidt_stability_JAS, mean_schmidt_stability_July, SthermoD_mean_JAS, SthermoD_mean, lake_average_temp, peak_lake_average_temp, lake_average_temp_JAS, mean_epi_temp, mean_hypo_temp, mean_surf_temp, mean_bottom_temp, peak_surf_temp, peak_bottom_temp, mean_surf_temp_JAS, mean_bottom_temp_JAS, mean_bottom_temp_365, mean_surf_temp_365, mean_1m_temp, mean_surf_JA, GDD_wtr_5c, GDD_wtr_10c, volume_mean_m_3, simulation_length_days, mean_volumetric_temp, kd, out_val calculated for 2210 lakes.","distribution":[{"@type":"dcat:Distribution","accessURL":"http://dx.doi.org/10.5066/F7028PN4","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.57473446e4b07e28b663d81a.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_57473446e4b07e28b663d81a","keyword":["007","012","US","USGS:57473446e4b07e28b663d81a","United States","WI","Wisconsin","climate change","environment","hydrodynamic model","inlandWaters","lakes","limnology","water clarity","water quality","water temperature"],"modified":"2026-09-03T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-92.91, 42.48, -86.75, 47.54","theme":["geospatial"],"title":"Wisconsin Lake Temperature Metrics Decreasing Clarity"},"description":"It is well recognized that the climate is warming in response to anthropogenic emission of greenhouse gases. Over the last decade, this has had a warming effect on lakes. Water clarity is also known to effect water temperature in lakes. What is unclear is how a warming climate might interact with changes in water clarity in lakes. As part of a project at the USGS Office of Water Information, several water clarity scenarios were simulated for lakes in Wisconsin to examine how changing water clarity interacts with climate change to affect lake temperatures at a broad scale.\nThis data set contains the following parameters: year, WBIC, durStrat, max_schmidt_stability, mean_schmidt_stability_JAS, mean_schmidt_stability_July, SthermoD_mean_JAS, SthermoD_mean, lake_average_temp, peak_lake_average_temp, lake_average_temp_JAS, mean_epi_temp, mean_hypo_temp, mean_surf_temp, mean_bottom_temp, peak_surf_temp, peak_bottom_temp, mean_surf_temp_JAS, mean_bottom_temp_JAS, mean_bottom_temp_365, mean_surf_temp_365, mean_1m_temp, mean_surf_JA, GDD_wtr_5c, GDD_wtr_10c, volume_mean_m_3, simulation_length_days, mean_volumetric_temp, kd, out_val calculated for 2210 lakes.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/93f65afe-a523-451d-a9d3-0c5782d6b688","harvest_record_raw":"https://catalog.data.gov/harvest_record/93f65afe-a523-451d-a9d3-0c5782d6b688/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_57473446e4b07e28b663d81a","keyword":["007","012","US","USGS:57473446e4b07e28b663d81a","United States","WI","Wisconsin","climate change","environment","hydrodynamic model","inlandWaters","lakes","limnology","water clarity","water quality","water temperature"],"last_harvested_date":"2026-09-05T18:52:23.328381","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":2,"publisher":"U.S. Geological Survey","slug":"wisconsin-lake-temperature-metrics-decreasing-clarity","spatial_centroid":{"lat":44.504,"lon":-90.446},"spatial_shape":{"coordinates":[[[-92.91,42.48],[-92.91,47.54],[-86.75,47.54],[-86.75,42.48],[-92.91,42.48]]],"type":"Polygon"},"theme":["geospatial"],"title":"Wisconsin Lake Temperature Metrics Decreasing Clarity","type":"dataset"},{"_score":9.258675,"_sort":[1788633973522,9.258675,4,"a4ee9726-e6cf-4420-9c57-ede85375f5fa"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Ryan F. Thompson","hasEmail":"mailto:rcthomps@usgs.gov"},"description":"This data set contains water velocity and flow direction data collected in shallow areas on selected transects near \nRiver Mile 769.8 of the Missouri River below Gavins Point Dam, South Dakota and Nebraska.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://water.usgs.gov/GIS/dsdl/up_post_vel_pt.zip","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.d40e906c-a138-48ca-bab6-64d12085941e.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_d40e906c-a138-48ca-bab6-64d12085941e","keyword":["Missouri River below Gavins Point Dam","Nebraska","South Dakota","Stream velocity and direction","USGS:d40e906c-a138-48ca-bab6-64d12085941e","environment","geoscientificInformation","inlandWaters"],"modified":"2020-11-17T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-96.891155, 42.717146, -96.851894, 42.731632","theme":["geospatial"],"title":"Postconstruction water velocity data collected at selected points on the Missouri River downstream from Gavins Point Dam near River Mile 769.8"},"description":"This data set contains water velocity and flow direction data collected in shallow areas on selected transects near \nRiver Mile 769.8 of the Missouri River below Gavins Point Dam, South Dakota and Nebraska.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/791948c5-9674-42c9-ba88-66683a1a934d","harvest_record_raw":"https://catalog.data.gov/harvest_record/791948c5-9674-42c9-ba88-66683a1a934d/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_d40e906c-a138-48ca-bab6-64d12085941e","keyword":["Missouri River below Gavins Point Dam","Nebraska","South Dakota","Stream velocity and direction","USGS:d40e906c-a138-48ca-bab6-64d12085941e","environment","geoscientificInformation","inlandWaters"],"last_harvested_date":"2026-09-05T18:46:13.522821","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":4,"publisher":"U.S. Geological Survey","slug":"postconstruction-water-velocity-data-collected-at-selected-points-on-the-missouri-river-do","spatial_centroid":{"lat":42.7229404,"lon":-96.8754506},"spatial_shape":{"coordinates":[[[-96.891155,42.717146],[-96.891155,42.731632],[-96.851894,42.731632],[-96.851894,42.717146],[-96.891155,42.717146]]],"type":"Polygon"},"theme":["geospatial"],"title":"Postconstruction water velocity data collected at selected points on the Missouri River downstream from Gavins Point Dam near River Mile 769.8","type":"dataset"},{"_score":7.371777,"_sort":[1788633965964,7.371777,9,"3e3f1ae3-38c3-4d58-af23-0d368264d848"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"U.S. Geological Survey","hasEmail":"mailto:whsc_data_contact@usgs.gov"},"description":"Geospatial data that is a derivative land cover product depicting woodland on topographic maps.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://www.usgs.gov/the-national-map-data-delivery","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.ea931b2b-ad6c-4ad3-bec7-e991b0081106.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_ea931b2b-ad6c-4ad3-bec7-e991b0081106","keyword":["Agricultural land","Barren land","FileGDB 10.1","Forest land","Land Cover - Woodland","Not Classified","Orthoimage","Range land","State","US","USGS:ea931b2b-ad6c-4ad3-bec7-e991b0081106","United States","Urban and built-up land","Water","Wetland","Woodland","annotations","biota","ecology","environment","farming","flora","habitat","imagery","imageryBaseMapsEarthCover","land cover"],"modified":"2023-08-31T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-179.229655487448, -14.4246950942767, 179.856674735386, 71.4395725901531","theme":["geospatial"],"title":"USGS Land Cover - Woodland Downloadable Data Collection"},"description":"Geospatial data that is a derivative land cover product depicting woodland on topographic maps.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/3d0650d8-7325-4da9-a859-ade687b70063","harvest_record_raw":"https://catalog.data.gov/harvest_record/3d0650d8-7325-4da9-a859-ade687b70063/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_ea931b2b-ad6c-4ad3-bec7-e991b0081106","keyword":["Agricultural land","Barren land","FileGDB 10.1","Forest land","Land Cover - Woodland","Not Classified","Orthoimage","Range land","State","US","USGS:ea931b2b-ad6c-4ad3-bec7-e991b0081106","United States","Urban and built-up land","Water","Wetland","Woodland","annotations","biota","ecology","environment","farming","flora","habitat","imagery","imageryBaseMapsEarthCover","land cover"],"last_harvested_date":"2026-09-05T18:46:05.964551","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":9,"publisher":"U.S. Geological Survey","slug":"usgs-land-cover-woodland-downloadable-data-collection","spatial_centroid":{"lat":19.921011979495223,"lon":-35.595123398314406},"spatial_shape":{"coordinates":[[[-179.229655487448,-14.4246950942767],[-179.229655487448,71.4395725901531],[179.856674735386,71.4395725901531],[179.856674735386,-14.4246950942767],[-179.229655487448,-14.4246950942767]]],"type":"Polygon"},"theme":["geospatial"],"title":"USGS Land Cover - Woodland Downloadable Data Collection","type":"dataset"},{"_score":10.266226,"_sort":[1788633719129,10.266226,2,"592bf83c-b187-4d3d-8699-c48ef2def528"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Ryan F. Thompson","hasEmail":"mailto:rcthomps@usgs.gov"},"description":"This geospatial data set contains the points collected by the echosounder on transects in the \ndownstream project reach surrounding the construction area at River Mile 761.4 below Gavins \nPoint Dam on the Missouri River in South Dakota.  This survey provides channel cross sections \nfor new and selected existing transects following construction of Emergent Sandbar Habitat \nnear River Mile 761.4","distribution":[{"@type":"dcat:Distribution","accessURL":"https://water.usgs.gov/GIS/dsdl/dn_post_bathy.zip","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.c0753ab2-c87b-4337-ac9c-8d0a287ec630.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_c0753ab2-c87b-4337-ac9c-8d0a287ec630","keyword":["Hydrographic Survey","USGS:c0753ab2-c87b-4337-ac9c-8d0a287ec630","environment","geoscientificInformation","inlandWaters"],"modified":"2020-11-17T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-96.912030, 42.701452, -96.822611, 42.736188","theme":["geospatial"],"title":"Bathymetry data for the post-construction survey of the Emergent Sandbar Habitat project at river mile 761.4 downstream from Gavins Point dam on the Missouri River."},"description":"This geospatial data set contains the points collected by the echosounder on transects in the \ndownstream project reach surrounding the construction area at River Mile 761.4 below Gavins \nPoint Dam on the Missouri River in South Dakota.  This survey provides channel cross sections \nfor new and selected existing transects following construction of Emergent Sandbar Habitat \nnear River Mile 761.4","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/bd41bdb3-0242-4e49-9927-2988bb359401","harvest_record_raw":"https://catalog.data.gov/harvest_record/bd41bdb3-0242-4e49-9927-2988bb359401/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_c0753ab2-c87b-4337-ac9c-8d0a287ec630","keyword":["Hydrographic Survey","USGS:c0753ab2-c87b-4337-ac9c-8d0a287ec630","environment","geoscientificInformation","inlandWaters"],"last_harvested_date":"2026-09-05T18:41:59.129608","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":2,"publisher":"U.S. Geological Survey","slug":"bathymetry-data-for-the-post-construction-survey-of-the-emergent-sandbar-habitat-project-a-8922e","spatial_centroid":{"lat":42.7153464,"lon":-96.8762624},"spatial_shape":{"coordinates":[[[-96.91203,42.701452],[-96.91203,42.736188],[-96.822611,42.736188],[-96.822611,42.701452],[-96.91203,42.701452]]],"type":"Polygon"},"theme":["geospatial"],"title":"Bathymetry data for the post-construction survey of the Emergent Sandbar Habitat project at river mile 761.4 downstream from Gavins Point dam on the Missouri River.","type":"dataset"},{"_score":10.020328,"_sort":[1788633488108,10.020328,2,"2bc7b65b-db44-47cb-886b-e60e43b5b0f1"],"dcat":{"accessLevel":"public","bureauCode":["010:04"],"contactPoint":{"@type":"vcard:Contact","fn":"Bureau of Land Management, sjeronimo","hasEmail":"mailto:sjeronimo@blm.gov"},"description":"HARV_POLY: This dataset represents completed harvest land treatments on BLM managed lands in the states of Oregon and Washington. Harvest treatments are the cutting and removal or trees or biomass.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://blm-egis.maps.arcgis.com/sharing/rest/content/items/2aef15715fcf4a50a282c51f288ba4f5/info/metadata/metadata.xml?format=iso19139","mediaType":"text/xml","title":"ISO-19139 metadata"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/2aef15715fcf4a50a282c51f288ba4f5/csv?layers=3","format":"CSV","mediaType":"text/csv","title":"CSV"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/2aef15715fcf4a50a282c51f288ba4f5/excel?layers=3","format":"XLSX","mediaType":"application/vnd.openxmlformats-officedocument.spreadsheetml.sheet","title":"Excel"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/2aef15715fcf4a50a282c51f288ba4f5/featureCollection?layers=3","format":"TXT","mediaType":"text/plain","title":"Feature Collection"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/2aef15715fcf4a50a282c51f288ba4f5/filegdb?layers=3","format":"ZIP","mediaType":"application/zip","title":"File Geodatabase"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/2aef15715fcf4a50a282c51f288ba4f5/geojson?layers=3","format":"GeoJSON","mediaType":"application/vnd.geo+json","title":"GeoJSON"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/2aef15715fcf4a50a282c51f288ba4f5/gpkg?layers=3","format":"ZIP","mediaType":"application/geopackage+sqlite3","title":"GeoPackage"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/2aef15715fcf4a50a282c51f288ba4f5/kml?layers=3","format":"KML","mediaType":"application/vnd.google-earth.kml+xml","title":"KML"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/2aef15715fcf4a50a282c51f288ba4f5/shapefile?layers=3","format":"ZIP","mediaType":"application/zip","title":"Shapefile"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/2aef15715fcf4a50a282c51f288ba4f5/sqlite?layers=3","format":"GDB","mediaType":"application/geopackage+sqlite3","title":"SQLite"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/datasets/BLM-EGIS::blm-or-harvest-land-treatments-polygon-hub","format":"Web Page","mediaType":"text/html","title":"ArcGIS Hub Dataset"},{"@type":"dcat:Distribution","accessURL":"https://services1.arcgis.com/KbxwQRRfWyEYLgp4/arcgis/rest/services/BLM_OR_Harvest_Land_Treatments_Polygon_Hub/FeatureServer/3","format":"ArcGIS GeoServices REST API","mediaType":"application/json","title":"ArcGIS GeoService"}],"identifier":"https://blm-egis.maps.arcgis.com/home/item.html?id=2aef15715fcf4a50a282c51f288ba4f5&sublayer=3","issued":"2022-09-26T15:45:18Z","keyword":["Biomass","Completed","Geospatial","Harvest","Management","Oregon","Treatments","Trees","Vegetation","Washington","biota","environment"],"landingPage":"https://gbp-blm-egis.hub.arcgis.com/datasets/BLM-EGIS::blm-or-harvest-land-treatments-polygon-hub","license":"http://www.usa.gov/publicdomain/label/1.0/","modified":"2026-09-02T12:19:58Z","programCode":["010:000"],"publisher":{"@type":"org:Organization","name":"Bureau of Land Management"},"spatial":"-125,49,-116,42","theme":["geospatial"],"title":"BLM OR Harvest Land Treatments Polygon Hub"},"description":"HARV_POLY: This dataset represents completed harvest land treatments on BLM managed lands in the states of Oregon and Washington. Harvest treatments are the cutting and removal or trees or biomass.","distribution_titles":["ISO-19139 metadata","CSV","Excel","Feature Collection","File Geodatabase","GeoJSON","GeoPackage","KML","Shapefile","SQLite","ArcGIS Hub Dataset","ArcGIS GeoService"],"harvest_record":"https://catalog.data.gov/harvest_record/6ad30eed-e985-4c0f-bb03-ecb2604705ef","harvest_record_raw":"https://catalog.data.gov/harvest_record/6ad30eed-e985-4c0f-bb03-ecb2604705ef/raw","has_download":false,"has_spatial":true,"identifier":"https://blm-egis.maps.arcgis.com/home/item.html?id=2aef15715fcf4a50a282c51f288ba4f5&sublayer=3","keyword":["Biomass","Completed","Geospatial","Harvest","Management","Oregon","Treatments","Trees","Vegetation","Washington","biota","environment"],"last_harvested_date":"2026-09-05T18:38:08.108326","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":2,"publisher":"Bureau of Land Management","slug":"blm-or-harvest-land-treatments-polygon-hub","spatial_centroid":{"lat":46.2,"lon":-121.4},"spatial_shape":{"coordinates":[[[-125,49],[-125,42],[-116,42],[-116,49],[-125,49]]],"type":"Polygon"},"theme":["geospatial"],"title":"BLM OR Harvest Land Treatments Polygon Hub","type":"dataset"},{"_score":9.866295,"_sort":[1788633483022,9.866295,2,"d364dc93-124b-4924-ad5d-b4fb793f83cb"],"dcat":{"accessLevel":"public","bureauCode":["010:04"],"contactPoint":{"@type":"vcard:Contact","fn":"Bureau of Land Management, gkrosts","hasEmail":"mailto:gkrosts@blm.gov"},"description":"LSE_CLM_POLY: This dataset is a spatial representation of Leases and Claims (LSE_CLM).  It is a portion of the total encumbrance data category that includes information about entities, rights, and restrictions relating to the use of Federal minerals.  This dataset contains Leases and Claims within Oregon and Washington BLM-administered lands (surface and subsurface) and over mineral estate in areas of split estate (i.e., areas where the BLM administers Federal mineral estate, but the surface is not owned by the BLM).","distribution":[{"@type":"dcat:Distribution","accessURL":"https://blm-egis.maps.arcgis.com/sharing/rest/content/items/1b9cb36f5a6941f5acb4cdc72098b54a/info/metadata/metadata.xml?format=iso19139","mediaType":"text/xml","title":"ISO-19139 metadata"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/1b9cb36f5a6941f5acb4cdc72098b54a/csv?layers=0","format":"CSV","mediaType":"text/csv","title":"CSV"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/1b9cb36f5a6941f5acb4cdc72098b54a/excel?layers=0","format":"XLSX","mediaType":"application/vnd.openxmlformats-officedocument.spreadsheetml.sheet","title":"Excel"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/1b9cb36f5a6941f5acb4cdc72098b54a/featureCollection?layers=0","format":"TXT","mediaType":"text/plain","title":"Feature Collection"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/1b9cb36f5a6941f5acb4cdc72098b54a/filegdb?layers=0","format":"ZIP","mediaType":"application/zip","title":"File Geodatabase"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/1b9cb36f5a6941f5acb4cdc72098b54a/geojson?layers=0","format":"GeoJSON","mediaType":"application/vnd.geo+json","title":"GeoJSON"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/1b9cb36f5a6941f5acb4cdc72098b54a/gpkg?layers=0","format":"ZIP","mediaType":"application/geopackage+sqlite3","title":"GeoPackage"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/1b9cb36f5a6941f5acb4cdc72098b54a/kml?layers=0","format":"KML","mediaType":"application/vnd.google-earth.kml+xml","title":"KML"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/1b9cb36f5a6941f5acb4cdc72098b54a/shapefile?layers=0","format":"ZIP","mediaType":"application/zip","title":"Shapefile"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/1b9cb36f5a6941f5acb4cdc72098b54a/sqlite?layers=0","format":"GDB","mediaType":"application/geopackage+sqlite3","title":"SQLite"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/datasets/BLM-EGIS::blm-or-leases-and-claims-polygon-hub","format":"Web Page","mediaType":"text/html","title":"ArcGIS Hub Dataset"},{"@type":"dcat:Distribution","accessURL":"https://services1.arcgis.com/KbxwQRRfWyEYLgp4/arcgis/rest/services/BLM_OR_Leases_and_Claims_Polygon_Hub/FeatureServer/0","format":"ArcGIS GeoServices REST API","mediaType":"application/json","title":"ArcGIS GeoService"}],"identifier":"https://blm-egis.maps.arcgis.com/home/item.html?id=1b9cb36f5a6941f5acb4cdc72098b54a&sublayer=0","issued":"2026-03-17T15:18:11Z","keyword":["Authorization","Claim","Encumbrance","Energy","Geology","Geospatial","Lease","Management","Minerals","Mining","Oregon","Washington","environment","geoscientificInformation"],"landingPage":"https://gbp-blm-egis.hub.arcgis.com/datasets/BLM-EGIS::blm-or-leases-and-claims-polygon-hub","license":"http://www.usa.gov/publicdomain/label/1.0/","modified":"2026-09-03T12:27:31Z","programCode":["010:000"],"publisher":{"@type":"org:Organization","name":"Bureau of Land Management"},"spatial":"-124.416,49.0001,-117.0047,41.9959","theme":["geospatial"],"title":"BLM OR Leases and Claims Polygon Hub"},"description":"LSE_CLM_POLY: This dataset is a spatial representation of Leases and Claims (LSE_CLM).  It is a portion of the total encumbrance data category that includes information about entities, rights, and restrictions relating to the use of Federal minerals.  This dataset contains Leases and Claims within Oregon and Washington BLM-administered lands (surface and subsurface) and over mineral estate in areas of split estate (i.e., areas where the BLM administers Federal mineral estate, but the surface is not owned by the BLM).","distribution_titles":["ISO-19139 metadata","CSV","Excel","Feature Collection","File Geodatabase","GeoJSON","GeoPackage","KML","Shapefile","SQLite","ArcGIS Hub Dataset","ArcGIS GeoService"],"harvest_record":"https://catalog.data.gov/harvest_record/79218f9a-22ef-4f1f-a6c3-c86519816431","harvest_record_raw":"https://catalog.data.gov/harvest_record/79218f9a-22ef-4f1f-a6c3-c86519816431/raw","has_download":false,"has_spatial":true,"identifier":"https://blm-egis.maps.arcgis.com/home/item.html?id=1b9cb36f5a6941f5acb4cdc72098b54a&sublayer=0","keyword":["Authorization","Claim","Encumbrance","Energy","Geology","Geospatial","Lease","Management","Minerals","Mining","Oregon","Washington","environment","geoscientificInformation"],"last_harvested_date":"2026-09-05T18:38:03.022961","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":2,"publisher":"Bureau of Land Management","slug":"blm-or-leases-and-claims-polygon-hub","spatial_centroid":{"lat":46.19842,"lon":-121.45147999999999},"spatial_shape":{"coordinates":[[[-124.416,49.0001],[-124.416,41.9959],[-117.0047,41.9959],[-117.0047,49.0001],[-124.416,49.0001]]],"type":"Polygon"},"theme":["geospatial"],"title":"BLM OR Leases and Claims Polygon Hub","type":"dataset"},{"_score":10.143366,"_sort":[1788633479165,10.143366,1,"8a6fd1e5-087f-4ecb-acd3-958d039ba509"],"dcat":{"accessLevel":"public","bureauCode":["010:04"],"contactPoint":{"@type":"vcard:Contact","fn":"Bureau of Land Management, sjeronimo","hasEmail":"mailto:sjeronimo@blm.gov"},"description":"MECH_POLY: This dataset represents completed mechanical treatments on BLM managed lands in the states of Oregon and Washington. Mechanical treatments are 1.) machine and manual methods of area treatment; 2.) pulling, piling, chopping, grinding, or mowing treatments to consolidate, reduce or clear live or dead vegetation (might be grass, brush, small trees, stump removal), as well as \"Cut-Leave\" of trees, and soil preparation such as plowing or ripping.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://blm-egis.maps.arcgis.com/sharing/rest/content/items/81eb695f59804488adad42cebea2a557/info/metadata/metadata.xml?format=iso19139","mediaType":"text/xml","title":"ISO-19139 metadata"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/81eb695f59804488adad42cebea2a557/csv?layers=4","format":"CSV","mediaType":"text/csv","title":"CSV"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/81eb695f59804488adad42cebea2a557/excel?layers=4","format":"XLSX","mediaType":"application/vnd.openxmlformats-officedocument.spreadsheetml.sheet","title":"Excel"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/81eb695f59804488adad42cebea2a557/featureCollection?layers=4","format":"TXT","mediaType":"text/plain","title":"Feature Collection"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/81eb695f59804488adad42cebea2a557/filegdb?layers=4","format":"ZIP","mediaType":"application/zip","title":"File Geodatabase"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/81eb695f59804488adad42cebea2a557/geojson?layers=4","format":"GeoJSON","mediaType":"application/vnd.geo+json","title":"GeoJSON"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/81eb695f59804488adad42cebea2a557/gpkg?layers=4","format":"ZIP","mediaType":"application/geopackage+sqlite3","title":"GeoPackage"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/81eb695f59804488adad42cebea2a557/kml?layers=4","format":"KML","mediaType":"application/vnd.google-earth.kml+xml","title":"KML"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/81eb695f59804488adad42cebea2a557/shapefile?layers=4","format":"ZIP","mediaType":"application/zip","title":"Shapefile"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/81eb695f59804488adad42cebea2a557/sqlite?layers=4","format":"GDB","mediaType":"application/geopackage+sqlite3","title":"SQLite"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/datasets/BLM-EGIS::blm-or-mechanical-treatments-polygon-hub","format":"Web Page","mediaType":"text/html","title":"ArcGIS Hub Dataset"},{"@type":"dcat:Distribution","accessURL":"https://services1.arcgis.com/KbxwQRRfWyEYLgp4/arcgis/rest/services/BLM_OR_Mechanical_Treatments_Polygon_Hub/FeatureServer/4","format":"ArcGIS GeoServices REST API","mediaType":"application/json","title":"ArcGIS GeoService"}],"identifier":"https://blm-egis.maps.arcgis.com/home/item.html?id=81eb695f59804488adad42cebea2a557&sublayer=4","issued":"2022-09-27T14:15:11Z","keyword":["Completed","Geospatial","Management","Mech","Mechanical","Oregon","Treatments","Vegetation","Washington","biota","environment"],"landingPage":"https://gbp-blm-egis.hub.arcgis.com/datasets/BLM-EGIS::blm-or-mechanical-treatments-polygon-hub","license":"http://www.usa.gov/publicdomain/label/1.0/","modified":"2026-09-02T12:23:14Z","programCode":["010:000"],"publisher":{"@type":"org:Organization","name":"Bureau of Land Management"},"spatial":"-125,49,-116,42","theme":["geospatial"],"title":"BLM OR Mechanical Treatments Polygon Hub"},"description":"MECH_POLY: This dataset represents completed mechanical treatments on BLM managed lands in the states of Oregon and Washington. Mechanical treatments are 1.) machine and manual methods of area treatment; 2.) pulling, piling, chopping, grinding, or mowing treatments to consolidate, reduce or clear live or dead vegetation (might be grass, brush, small trees, stump removal), as well as \"Cut-Leave\" of trees, and soil preparation such as plowing or ripping.","distribution_titles":["ISO-19139 metadata","CSV","Excel","Feature Collection","File Geodatabase","GeoJSON","GeoPackage","KML","Shapefile","SQLite","ArcGIS Hub Dataset","ArcGIS GeoService"],"harvest_record":"https://catalog.data.gov/harvest_record/0c1e417f-0971-4ec2-bb02-0182f9bf375f","harvest_record_raw":"https://catalog.data.gov/harvest_record/0c1e417f-0971-4ec2-bb02-0182f9bf375f/raw","has_download":false,"has_spatial":true,"identifier":"https://blm-egis.maps.arcgis.com/home/item.html?id=81eb695f59804488adad42cebea2a557&sublayer=4","keyword":["Completed","Geospatial","Management","Mech","Mechanical","Oregon","Treatments","Vegetation","Washington","biota","environment"],"last_harvested_date":"2026-09-05T18:37:59.165347","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":1,"publisher":"Bureau of Land Management","slug":"blm-or-mechanical-treatments-polygon-hub","spatial_centroid":{"lat":46.2,"lon":-121.4},"spatial_shape":{"coordinates":[[[-125,49],[-125,42],[-116,42],[-116,49],[-125,49]]],"type":"Polygon"},"theme":["geospatial"],"title":"BLM OR Mechanical Treatments Polygon Hub","type":"dataset"},{"_score":9.796621,"_sort":[1788633476891,9.796621,3,"a06cba37-6e36-4e89-b1c3-402af73b2ffe"],"dcat":{"accessLevel":"public","bureauCode":["010:04"],"contactPoint":{"@type":"vcard:Contact","fn":"Bureau of Land Management, sjeronimo","hasEmail":"mailto:sjeronimo@blm.gov"},"description":"BIO_POLY: This dataset represents completed biological land treatments for BLM managed lands in the states of Oregon and Washington. Biological treatments are the introduction of foraging species, predators or parasites to control plant or animal pests, or to selectively suppress or remove vegetation.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://blm-egis.maps.arcgis.com/sharing/rest/content/items/32d9114a77c34e6dae1cb666065695ab/info/metadata/metadata.xml?format=iso19139","mediaType":"text/xml","title":"ISO-19139 metadata"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/32d9114a77c34e6dae1cb666065695ab/csv?layers=0","format":"CSV","mediaType":"text/csv","title":"CSV"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/32d9114a77c34e6dae1cb666065695ab/excel?layers=0","format":"XLSX","mediaType":"application/vnd.openxmlformats-officedocument.spreadsheetml.sheet","title":"Excel"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/32d9114a77c34e6dae1cb666065695ab/featureCollection?layers=0","format":"TXT","mediaType":"text/plain","title":"Feature Collection"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/32d9114a77c34e6dae1cb666065695ab/filegdb?layers=0","format":"ZIP","mediaType":"application/zip","title":"File Geodatabase"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/32d9114a77c34e6dae1cb666065695ab/geojson?layers=0","format":"GeoJSON","mediaType":"application/vnd.geo+json","title":"GeoJSON"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/32d9114a77c34e6dae1cb666065695ab/gpkg?layers=0","format":"ZIP","mediaType":"application/geopackage+sqlite3","title":"GeoPackage"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/32d9114a77c34e6dae1cb666065695ab/kml?layers=0","format":"KML","mediaType":"application/vnd.google-earth.kml+xml","title":"KML"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/32d9114a77c34e6dae1cb666065695ab/shapefile?layers=0","format":"ZIP","mediaType":"application/zip","title":"Shapefile"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/32d9114a77c34e6dae1cb666065695ab/sqlite?layers=0","format":"GDB","mediaType":"application/geopackage+sqlite3","title":"SQLite"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/datasets/BLM-EGIS::blm-or-biological-treatments-polygon-hub","format":"Web Page","mediaType":"text/html","title":"ArcGIS Hub Dataset"},{"@type":"dcat:Distribution","accessURL":"https://services1.arcgis.com/KbxwQRRfWyEYLgp4/arcgis/rest/services/BLM_OR_Biological_Treatments_Polygon_Hub/FeatureServer/0","format":"ArcGIS GeoServices REST API","mediaType":"application/json","title":"ArcGIS GeoService"}],"identifier":"https://blm-egis.maps.arcgis.com/home/item.html?id=32d9114a77c34e6dae1cb666065695ab&sublayer=0","issued":"2026-05-12T14:45:01Z","keyword":["BIO","Biological","Completed","Disturbance","Fire","Forest","Oregon","Treatments","Vegetation","Washington","biota","economy","environment","farming","location"],"landingPage":"https://gbp-blm-egis.hub.arcgis.com/datasets/BLM-EGIS::blm-or-biological-treatments-polygon-hub","license":"http://www.usa.gov/publicdomain/label/1.0/","modified":"2026-09-02T12:12:47Z","programCode":["010:000"],"publisher":{"@type":"org:Organization","name":"Bureau of Land Management"},"spatial":"-125,49,-116,42","theme":["geospatial"],"title":"BLM OR Biological Treatments Polygon Hub"},"description":"BIO_POLY: This dataset represents completed biological land treatments for BLM managed lands in the states of Oregon and Washington. Biological treatments are the introduction of foraging species, predators or parasites to control plant or animal pests, or to selectively suppress or remove vegetation.","distribution_titles":["ISO-19139 metadata","CSV","Excel","Feature Collection","File Geodatabase","GeoJSON","GeoPackage","KML","Shapefile","SQLite","ArcGIS Hub Dataset","ArcGIS GeoService"],"harvest_record":"https://catalog.data.gov/harvest_record/2b19d4cd-cdc1-4897-bbe1-7d392a88c304","harvest_record_raw":"https://catalog.data.gov/harvest_record/2b19d4cd-cdc1-4897-bbe1-7d392a88c304/raw","has_download":false,"has_spatial":true,"identifier":"https://blm-egis.maps.arcgis.com/home/item.html?id=32d9114a77c34e6dae1cb666065695ab&sublayer=0","keyword":["BIO","Biological","Completed","Disturbance","Fire","Forest","Oregon","Treatments","Vegetation","Washington","biota","economy","environment","farming","location"],"last_harvested_date":"2026-09-05T18:37:56.891627","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":3,"publisher":"Bureau of Land Management","slug":"blm-or-biological-treatments-polygon-hub","spatial_centroid":{"lat":46.2,"lon":-121.4},"spatial_shape":{"coordinates":[[[-125,49],[-125,42],[-116,42],[-116,49],[-125,49]]],"type":"Polygon"},"theme":["geospatial"],"title":"BLM OR Biological Treatments Polygon Hub","type":"dataset"},{"_score":21.81921,"_sort":[1788633475128,21.81921,2,"4f17f574-16ea-48be-ae27-3c013a61ba0d"],"dcat":{"accessLevel":"public","bureauCode":["010:04"],"contactPoint":{"@type":"vcard:Contact","fn":"Bureau of Land Management, eglenn","hasEmail":"mailto:eglenn@blm.gov"},"description":"<div style='text-align:left;'><div><div><p><font size='3'>The layers within this feature service represent the spatial extent and boundaries of the San Rafael Swell Recreation Area. As part of the John D. Dingell. Jr. Conservation, Management, and Recreation Act of 2019, Congress designated San Rafael Swell Recreation Area (approximately 217,000 acres). The San Rafael Swell Recreation area features magnificent badlands of brightly colored and wildly eroded sandstone formations, deep canyons, and giant plates of stone tilted upright through massive geologic upheaval. Data within these services are a live copy of BLM Utah's enterprise production environment. Quality control is conducted annually.</font></p><p><font size='3'>Complete metadata for these data sets can be found at:<br /></font></p><p></p><ul><li><font size='3'><a href='https://gis.blm.gov/utarcgis/rest/services/Recreation/BLM_UT_RecAreas/FeatureServer/0/metadata' target='_blank' rel='nofollow ugc noopener noreferrer'><font color='#4169e1'><u>BLM UT Congressionally Designated Recreation Areas (Arc)</u></font></a><br /></font></li><li><a href='https://gis.blm.gov/utarcgis/rest/services/Recreation/BLM_UT_RecAreas/FeatureServer/1/metadata' target='_blank' rel='nofollow ugc noopener noreferrer'><font color='#4169e1' size='3'><u>BLM UT Congressionally Designated Recreation Areas (Polygon)</u></font></a><br /></li></ul><p></p></div></div></div>","distribution":[{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/maps/BLM-EGIS::blm-ut-congressionally-designated-recreation-areas","format":"Web Page","mediaType":"text/html","title":"ArcGIS Hub Dataset"},{"@type":"dcat:Distribution","accessURL":"https://gis.blm.gov/utarcgis/rest/services/Recreation/BLM_UT_RecAreas/FeatureServer/","format":"ArcGIS GeoServices REST API","mediaType":"application/json","title":"ArcGIS GeoService"},{"@type":"dcat:Distribution","accessURL":"https://gis.blm.gov/utarcgis/rest/services/Recreation/BLM_UT_RecAreas/FeatureServer/info/metadata?format=iso19139","mediaType":"text/xml","title":"ISO-19139 metadata"}],"identifier":"https://blm-egis.maps.arcgis.com/home/item.html?id=7e6f5bcf96ad4ddd8bf1b30e3fde21ff","issued":"2022-05-25T20:58:54Z","keyword":["BLM","Bureau of Land Management","Geospatial","Management","Public Lands","Recreation","Recreation Areas","UT","Utah","Wilderness","Withdrawal","boundaries","environment","planningCadastre"],"landingPage":"https://gbp-blm-egis.hub.arcgis.com/maps/BLM-EGIS::blm-ut-congressionally-designated-recreation-areas","license":"http://www.usa.gov/publicdomain/label/1.0/","modified":"2022-11-04T17:16:45Z","programCode":["010:000"],"publisher":{"@type":"org:Organization","name":"Bureau of Land Management"},"spatial":"-124.4783,29.0842,-82.6747,49.0004","theme":["geospatial"],"title":"BLM UT Congressionally Designated Recreation Areas"},"description":"<div style='text-align:left;'><div><div><p><font size='3'>The layers within this feature service represent the spatial extent and boundaries of the San Rafael Swell Recreation Area. As part of the John D. Dingell. Jr. Conservation, Management, and Recreation Act of 2019, Congress designated San Rafael Swell Recreation Area (approximately 217,000 acres). The San Rafael Swell Recreation area features magnificent badlands of brightly colored and wildly eroded sandstone formations, deep canyons, and giant plates of stone tilted upright through massive geologic upheaval. Data within these services are a live copy of BLM Utah's enterprise production environment. Quality control is conducted annually.</font></p><p><font size='3'>Complete metadata for these data sets can be found at:<br /></font></p><p></p><ul><li><font size='3'><a href='https://gis.blm.gov/utarcgis/rest/services/Recreation/BLM_UT_RecAreas/FeatureServer/0/metadata' target='_blank' rel='nofollow ugc noopener noreferrer'><font color='#4169e1'><u>BLM UT Congressionally Designated Recreation Areas (Arc)</u></font></a><br /></font></li><li><a href='https://gis.blm.gov/utarcgis/rest/services/Recreation/BLM_UT_RecAreas/FeatureServer/1/metadata' target='_blank' rel='nofollow ugc noopener noreferrer'><font color='#4169e1' size='3'><u>BLM UT Congressionally Designated Recreation Areas (Polygon)</u></font></a><br /></li></ul><p></p></div></div></div>","distribution_titles":["ArcGIS Hub Dataset","ArcGIS GeoService","ISO-19139 metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/932f687f-f574-471a-9c7d-75195077fd9c","harvest_record_raw":"https://catalog.data.gov/harvest_record/932f687f-f574-471a-9c7d-75195077fd9c/raw","has_download":false,"has_spatial":true,"identifier":"https://blm-egis.maps.arcgis.com/home/item.html?id=7e6f5bcf96ad4ddd8bf1b30e3fde21ff","keyword":["BLM","Bureau of Land Management","Geospatial","Management","Public Lands","Recreation","Recreation Areas","UT","Utah","Wilderness","Withdrawal","boundaries","environment","planningCadastre"],"last_harvested_date":"2026-09-05T18:37:55.128170","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":2,"publisher":"Bureau of Land Management","slug":"blm-ut-congressionally-designated-recreation-areas","spatial_centroid":{"lat":37.05068,"lon":-107.75686},"spatial_shape":{"coordinates":[[[-124.4783,29.0842],[-124.4783,49.0004],[-82.6747,49.0004],[-82.6747,29.0842],[-124.4783,29.0842]]],"type":"Polygon"},"theme":["geospatial"],"title":"BLM UT Congressionally Designated Recreation Areas","type":"dataset"},{"_score":9.9118,"_sort":[1788633472648,9.9118,1,"3845e84e-fc61-43f7-aded-ddcca2a3c58b"],"dcat":{"accessLevel":"public","bureauCode":["010:04"],"contactPoint":{"@type":"vcard:Contact","fn":"Bureau of Land Management, sjeronimo","hasEmail":"mailto:sjeronimo@blm.gov"},"description":"CHEM_POLY: This dataset represents completed chemical land treatments on BLM managed lands in the states of Oregon and Washington. Chemical treatments are applications of herbicide or pesticide, to control or kill pests and invasive plants, or fertilizer to enhance plant growth.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://blm-egis.maps.arcgis.com/sharing/rest/content/items/51c73397552d44caae568705331aba1d/info/metadata/metadata.xml?format=iso19139","mediaType":"text/xml","title":"ISO-19139 metadata"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/51c73397552d44caae568705331aba1d/csv?layers=2","format":"CSV","mediaType":"text/csv","title":"CSV"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/51c73397552d44caae568705331aba1d/excel?layers=2","format":"XLSX","mediaType":"application/vnd.openxmlformats-officedocument.spreadsheetml.sheet","title":"Excel"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/51c73397552d44caae568705331aba1d/featureCollection?layers=2","format":"TXT","mediaType":"text/plain","title":"Feature Collection"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/51c73397552d44caae568705331aba1d/filegdb?layers=2","format":"ZIP","mediaType":"application/zip","title":"File Geodatabase"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/51c73397552d44caae568705331aba1d/geojson?layers=2","format":"GeoJSON","mediaType":"application/vnd.geo+json","title":"GeoJSON"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/51c73397552d44caae568705331aba1d/gpkg?layers=2","format":"ZIP","mediaType":"application/geopackage+sqlite3","title":"GeoPackage"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/51c73397552d44caae568705331aba1d/kml?layers=2","format":"KML","mediaType":"application/vnd.google-earth.kml+xml","title":"KML"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/51c73397552d44caae568705331aba1d/shapefile?layers=2","format":"ZIP","mediaType":"application/zip","title":"Shapefile"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/51c73397552d44caae568705331aba1d/sqlite?layers=2","format":"GDB","mediaType":"application/geopackage+sqlite3","title":"SQLite"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/datasets/BLM-EGIS::blm-or-chemical-treatments-polygon-hub","format":"Web Page","mediaType":"text/html","title":"ArcGIS Hub Dataset"},{"@type":"dcat:Distribution","accessURL":"https://services1.arcgis.com/KbxwQRRfWyEYLgp4/arcgis/rest/services/BLM_OR_Chemical_Treatments_Polygon_Hub/FeatureServer/2","format":"ArcGIS GeoServices REST API","mediaType":"application/json","title":"ArcGIS GeoService"}],"identifier":"https://blm-egis.maps.arcgis.com/home/item.html?id=51c73397552d44caae568705331aba1d&sublayer=2","issued":"2022-09-27T14:00:04Z","keyword":["CHEM","Chemical","Geospatial","Land Use Planning","Management","Oregon","Treatments","Vegetation","Washington","biota","environment","planningCadastre"],"landingPage":"https://gbp-blm-egis.hub.arcgis.com/datasets/BLM-EGIS::blm-or-chemical-treatments-polygon-hub","license":"http://www.usa.gov/publicdomain/label/1.0/","modified":"2026-09-02T12:17:46Z","programCode":["010:000"],"publisher":{"@type":"org:Organization","name":"Bureau of Land Management"},"spatial":"-125,49,-116,42","theme":["geospatial"],"title":"BLM OR Chemical Treatments Polygon Hub"},"description":"CHEM_POLY: This dataset represents completed chemical land treatments on BLM managed lands in the states of Oregon and Washington. Chemical treatments are applications of herbicide or pesticide, to control or kill pests and invasive plants, or fertilizer to enhance plant growth.","distribution_titles":["ISO-19139 metadata","CSV","Excel","Feature Collection","File Geodatabase","GeoJSON","GeoPackage","KML","Shapefile","SQLite","ArcGIS Hub Dataset","ArcGIS GeoService"],"harvest_record":"https://catalog.data.gov/harvest_record/e805e397-954c-4846-b996-1254770ef182","harvest_record_raw":"https://catalog.data.gov/harvest_record/e805e397-954c-4846-b996-1254770ef182/raw","has_download":false,"has_spatial":true,"identifier":"https://blm-egis.maps.arcgis.com/home/item.html?id=51c73397552d44caae568705331aba1d&sublayer=2","keyword":["CHEM","Chemical","Geospatial","Land Use Planning","Management","Oregon","Treatments","Vegetation","Washington","biota","environment","planningCadastre"],"last_harvested_date":"2026-09-05T18:37:52.648547","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":1,"publisher":"Bureau of Land Management","slug":"blm-or-chemical-treatments-polygon-hub","spatial_centroid":{"lat":46.2,"lon":-121.4},"spatial_shape":{"coordinates":[[[-125,49],[-125,42],[-116,42],[-116,49],[-125,49]]],"type":"Polygon"},"theme":["geospatial"],"title":"BLM OR Chemical Treatments Polygon Hub","type":"dataset"},{"_score":10.150478,"_sort":[1788633467625,10.150478,2,"be6cbaa0-e542-4747-8be3-23c9959aa6d2"],"dcat":{"accessLevel":"public","bureauCode":["010:04"],"contactPoint":{"@type":"vcard:Contact","fn":"Bureau of Land Management, sjeronimo","hasEmail":"mailto:sjeronimo@blm.gov"},"description":"REVEG_POLY: This dataset represents completed revegetation treatments on BLM managed lands in the states of Oregon and Washington. Revegetation treatments are revegetation by planting or seeding.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://blm-egis.maps.arcgis.com/sharing/rest/content/items/b8f8401423d24bd9b85811b474f071ab/info/metadata/metadata.xml?format=iso19139","mediaType":"text/xml","title":"ISO-19139 metadata"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/b8f8401423d24bd9b85811b474f071ab/csv?layers=6","format":"CSV","mediaType":"text/csv","title":"CSV"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/b8f8401423d24bd9b85811b474f071ab/excel?layers=6","format":"XLSX","mediaType":"application/vnd.openxmlformats-officedocument.spreadsheetml.sheet","title":"Excel"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/b8f8401423d24bd9b85811b474f071ab/featureCollection?layers=6","format":"TXT","mediaType":"text/plain","title":"Feature Collection"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/b8f8401423d24bd9b85811b474f071ab/filegdb?layers=6","format":"ZIP","mediaType":"application/zip","title":"File Geodatabase"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/b8f8401423d24bd9b85811b474f071ab/geojson?layers=6","format":"GeoJSON","mediaType":"application/vnd.geo+json","title":"GeoJSON"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/b8f8401423d24bd9b85811b474f071ab/gpkg?layers=6","format":"ZIP","mediaType":"application/geopackage+sqlite3","title":"GeoPackage"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/b8f8401423d24bd9b85811b474f071ab/kml?layers=6","format":"KML","mediaType":"application/vnd.google-earth.kml+xml","title":"KML"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/b8f8401423d24bd9b85811b474f071ab/shapefile?layers=6","format":"ZIP","mediaType":"application/zip","title":"Shapefile"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/b8f8401423d24bd9b85811b474f071ab/sqlite?layers=6","format":"GDB","mediaType":"application/geopackage+sqlite3","title":"SQLite"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/datasets/BLM-EGIS::blm-or-revegetation-treatments-polygon-hub","format":"Web Page","mediaType":"text/html","title":"ArcGIS Hub Dataset"},{"@type":"dcat:Distribution","accessURL":"https://services1.arcgis.com/KbxwQRRfWyEYLgp4/arcgis/rest/services/BLM_OR_Revegetation_Treatments_Polygon_Hub/FeatureServer/6","format":"ArcGIS GeoServices REST API","mediaType":"application/json","title":"ArcGIS GeoService"}],"identifier":"https://blm-egis.maps.arcgis.com/home/item.html?id=b8f8401423d24bd9b85811b474f071ab&sublayer=6","issued":"2022-07-26T14:27:33Z","keyword":["Completed","Geospatial","Management","Oregon","Planting","Revegetation","Seed","Treatments","Vegetation","Washington","biota","environment"],"landingPage":"https://gbp-blm-egis.hub.arcgis.com/datasets/BLM-EGIS::blm-or-revegetation-treatments-polygon-hub","license":"http://www.usa.gov/publicdomain/label/1.0/","modified":"2026-09-02T12:31:40Z","programCode":["010:000"],"publisher":{"@type":"org:Organization","name":"Bureau of Land Management"},"spatial":"-125,49,-116,42","theme":["geospatial"],"title":"BLM OR Revegetation Treatments Polygon Hub"},"description":"REVEG_POLY: This dataset represents completed revegetation treatments on BLM managed lands in the states of Oregon and Washington. Revegetation treatments are revegetation by planting or seeding.","distribution_titles":["ISO-19139 metadata","CSV","Excel","Feature Collection","File Geodatabase","GeoJSON","GeoPackage","KML","Shapefile","SQLite","ArcGIS Hub Dataset","ArcGIS GeoService"],"harvest_record":"https://catalog.data.gov/harvest_record/453651d9-4478-4011-9e16-d0343f21e169","harvest_record_raw":"https://catalog.data.gov/harvest_record/453651d9-4478-4011-9e16-d0343f21e169/raw","has_download":false,"has_spatial":true,"identifier":"https://blm-egis.maps.arcgis.com/home/item.html?id=b8f8401423d24bd9b85811b474f071ab&sublayer=6","keyword":["Completed","Geospatial","Management","Oregon","Planting","Revegetation","Seed","Treatments","Vegetation","Washington","biota","environment"],"last_harvested_date":"2026-09-05T18:37:47.625183","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":2,"publisher":"Bureau of Land Management","slug":"blm-or-revegetation-treatments-polygon-hub","spatial_centroid":{"lat":46.2,"lon":-121.4},"spatial_shape":{"coordinates":[[[-125,49],[-125,42],[-116,42],[-116,49],[-125,49]]],"type":"Polygon"},"theme":["geospatial"],"title":"BLM OR Revegetation Treatments Polygon Hub","type":"dataset"},{"_score":9.337736,"_sort":[1788633464280,9.337736,1,"1b41f460-9312-4656-8c96-c2a5508ca0ad"],"dcat":{"accessLevel":"public","bureauCode":["010:04"],"contactPoint":{"@type":"vcard:Contact","fn":"Bureau of Land Management, sjeronimo","hasEmail":"mailto:sjeronimo@blm.gov"},"description":"PROT_POLY: This dataset represents completed treatments involving fenced exclosures or protective devices on trees or soil surfaces on BLM managed lands in the states of Oregon and Washington. The entire area is considered \"treated\" with protection measures. The individual structures or devices used may or may not be captured on a separate theme (STRCT_ARC and/or STRCT_PT).","distribution":[{"@type":"dcat:Distribution","accessURL":"https://blm-egis.maps.arcgis.com/sharing/rest/content/items/b73744ee8dce44baa2a1e3782d43411f/info/metadata/metadata.xml?format=iso19139","mediaType":"text/xml","title":"ISO-19139 metadata"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/b73744ee8dce44baa2a1e3782d43411f/csv?layers=5","format":"CSV","mediaType":"text/csv","title":"CSV"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/b73744ee8dce44baa2a1e3782d43411f/excel?layers=5","format":"XLSX","mediaType":"application/vnd.openxmlformats-officedocument.spreadsheetml.sheet","title":"Excel"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/b73744ee8dce44baa2a1e3782d43411f/featureCollection?layers=5","format":"TXT","mediaType":"text/plain","title":"Feature Collection"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/b73744ee8dce44baa2a1e3782d43411f/filegdb?layers=5","format":"ZIP","mediaType":"application/zip","title":"File Geodatabase"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/b73744ee8dce44baa2a1e3782d43411f/geojson?layers=5","format":"GeoJSON","mediaType":"application/vnd.geo+json","title":"GeoJSON"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/b73744ee8dce44baa2a1e3782d43411f/gpkg?layers=5","format":"ZIP","mediaType":"application/geopackage+sqlite3","title":"GeoPackage"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/b73744ee8dce44baa2a1e3782d43411f/kml?layers=5","format":"KML","mediaType":"application/vnd.google-earth.kml+xml","title":"KML"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/b73744ee8dce44baa2a1e3782d43411f/shapefile?layers=5","format":"ZIP","mediaType":"application/zip","title":"Shapefile"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/b73744ee8dce44baa2a1e3782d43411f/sqlite?layers=5","format":"GDB","mediaType":"application/geopackage+sqlite3","title":"SQLite"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/datasets/BLM-EGIS::blm-or-exclosure-protection-treatments-polygon-hub","format":"Web Page","mediaType":"text/html","title":"ArcGIS Hub Dataset"},{"@type":"dcat:Distribution","accessURL":"https://services1.arcgis.com/KbxwQRRfWyEYLgp4/arcgis/rest/services/BLM_OR_Exclosure_Protection_Treatments_Polygon_Hub/FeatureServer/5","format":"ArcGIS GeoServices REST API","mediaType":"application/json","title":"ArcGIS GeoService"}],"identifier":"https://blm-egis.maps.arcgis.com/home/item.html?id=b73744ee8dce44baa2a1e3782d43411f&sublayer=5","issued":"2025-11-19T15:29:49Z","keyword":["Completed","Disturbance","Exclosures","Fire","Forest","Land Use Planning","Oregon","Protection","Treatments","Vegetation","Washington","biota","economy","environment","farming","location"],"landingPage":"https://gbp-blm-egis.hub.arcgis.com/datasets/BLM-EGIS::blm-or-exclosure-protection-treatments-polygon-hub","license":"http://www.usa.gov/publicdomain/label/1.0/","modified":"2026-09-02T12:29:18Z","programCode":["010:000"],"publisher":{"@type":"org:Organization","name":"Bureau of Land Management"},"spatial":"-125,49,-116,42","theme":["geospatial"],"title":"BLM OR Exclosure Protection Treatments Polygon Hub"},"description":"PROT_POLY: This dataset represents completed treatments involving fenced exclosures or protective devices on trees or soil surfaces on BLM managed lands in the states of Oregon and Washington. The entire area is considered \"treated\" with protection measures. The individual structures or devices used may or may not be captured on a separate theme (STRCT_ARC and/or STRCT_PT).","distribution_titles":["ISO-19139 metadata","CSV","Excel","Feature Collection","File Geodatabase","GeoJSON","GeoPackage","KML","Shapefile","SQLite","ArcGIS Hub Dataset","ArcGIS GeoService"],"harvest_record":"https://catalog.data.gov/harvest_record/357c8544-381c-4510-a20c-c9659f2a88d3","harvest_record_raw":"https://catalog.data.gov/harvest_record/357c8544-381c-4510-a20c-c9659f2a88d3/raw","has_download":false,"has_spatial":true,"identifier":"https://blm-egis.maps.arcgis.com/home/item.html?id=b73744ee8dce44baa2a1e3782d43411f&sublayer=5","keyword":["Completed","Disturbance","Exclosures","Fire","Forest","Land Use Planning","Oregon","Protection","Treatments","Vegetation","Washington","biota","economy","environment","farming","location"],"last_harvested_date":"2026-09-05T18:37:44.280437","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":1,"publisher":"Bureau of Land Management","slug":"blm-or-exclosure-protection-treatments-polygon-hub","spatial_centroid":{"lat":46.2,"lon":-121.4},"spatial_shape":{"coordinates":[[[-125,49],[-125,42],[-116,42],[-116,49],[-125,49]]],"type":"Polygon"},"theme":["geospatial"],"title":"BLM OR Exclosure Protection Treatments Polygon Hub","type":"dataset"},{"_score":21.275986,"_sort":[1788633460034,21.275986,0,"92259a8c-1c56-4ef6-abf5-5ce60bebca4c"],"dcat":{"accessLevel":"public","bureauCode":["010:04"],"contactPoint":{"@type":"vcard:Contact","fn":"Bureau of Land Management, eglenn","hasEmail":"mailto:eglenn@blm.gov"},"description":"<div style='text-align:left;'><div><div><p><font size='3'>The layers within this feature service represent the spatial extent and boundaries of the San Rafael Swell Recreation Area. As part of the John D. Dingell. Jr. Conservation, Management, and Recreation Act of 2019, Congress designated San Rafael Swell Recreation Area (approximately 217,000 acres). The San Rafael Swell Recreation area features magnificent badlands of brightly colored and wildly eroded sandstone formations, deep canyons, and giant plates of stone tilted upright through massive geologic upheaval. Data within these services are a live copy of BLM Utah's enterprise production environment. Quality control is conducted annually.</font></p><p><font size='3'>Complete metadata for these data sets can be found at:<br /></font></p><p></p><ul><li><font size='3'><a href='https://gis.blm.gov/utarcgis/rest/services/Recreation/BLM_UT_RecAreas/FeatureServer/0/metadata' target='_blank' rel='nofollow ugc noopener noreferrer'><font color='#4169e1'><u>BLM UT Congressionally Designated Recreation Areas (Arc)</u></font></a><br /></font></li><li><a href='https://gis.blm.gov/utarcgis/rest/services/Recreation/BLM_UT_RecAreas/FeatureServer/1/metadata' target='_blank' rel='nofollow ugc noopener noreferrer'><font color='#4169e1' size='3'><u>BLM UT Congressionally Designated Recreation Areas (Polygon)</u></font></a><br /></li></ul><p></p></div></div></div>","distribution":[{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/7e6f5bcf96ad4ddd8bf1b30e3fde21ff/csv?layers=0","format":"CSV","mediaType":"text/csv","title":"CSV"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/7e6f5bcf96ad4ddd8bf1b30e3fde21ff/filegdb?layers=0","format":"ZIP","mediaType":"application/zip","title":"File Geodatabase"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/7e6f5bcf96ad4ddd8bf1b30e3fde21ff/geojson?layers=0","format":"GeoJSON","mediaType":"application/vnd.geo+json","title":"GeoJSON"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/7e6f5bcf96ad4ddd8bf1b30e3fde21ff/kml?layers=0","format":"KML","mediaType":"application/vnd.google-earth.kml+xml","title":"KML"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/7e6f5bcf96ad4ddd8bf1b30e3fde21ff/shapefile?layers=0","format":"ZIP","mediaType":"application/zip","title":"Shapefile"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/datasets/BLM-EGIS::blm-ut-congressionally-designated-recreation-areas-arc","format":"Web Page","mediaType":"text/html","title":"ArcGIS Hub Dataset"},{"@type":"dcat:Distribution","accessURL":"https://gis.blm.gov/utarcgis/rest/services/Recreation/BLM_UT_RecAreas/FeatureServer/0","format":"ArcGIS GeoServices REST API","mediaType":"application/json","title":"ArcGIS GeoService"},{"@type":"dcat:Distribution","accessURL":"https://gis.blm.gov/utarcgis/rest/services/Recreation/BLM_UT_RecAreas/FeatureServer/0/metadata?format=iso19139","mediaType":"text/xml","title":"ISO-19139 metadata"}],"identifier":"https://blm-egis.maps.arcgis.com/home/item.html?id=7e6f5bcf96ad4ddd8bf1b30e3fde21ff&sublayer=0","issued":"2022-05-25T20:58:54Z","keyword":["BLM","Bureau of Land Management","Geospatial","Management","Public Lands","Recreation","Recreation Areas","UT","Utah","Wilderness","Withdrawal","boundaries","environment","planningCadastre"],"landingPage":"https://gbp-blm-egis.hub.arcgis.com/datasets/BLM-EGIS::blm-ut-congressionally-designated-recreation-areas-arc","license":"http://www.usa.gov/publicdomain/label/1.0/","modified":"2022-11-04T17:16:45Z","programCode":["010:000"],"publisher":{"@type":"org:Organization","name":"Bureau of Land Management"},"spatial":"-111.1026,39.2194,-110.3983,38.4984","theme":["geospatial"],"title":"BLM UT Congressionally Designated Recreation Areas (Arc)"},"description":"<div style='text-align:left;'><div><div><p><font size='3'>The layers within this feature service represent the spatial extent and boundaries of the San Rafael Swell Recreation Area. As part of the John D. Dingell. Jr. Conservation, Management, and Recreation Act of 2019, Congress designated San Rafael Swell Recreation Area (approximately 217,000 acres). The San Rafael Swell Recreation area features magnificent badlands of brightly colored and wildly eroded sandstone formations, deep canyons, and giant plates of stone tilted upright through massive geologic upheaval. Data within these services are a live copy of BLM Utah's enterprise production environment. Quality control is conducted annually.</font></p><p><font size='3'>Complete metadata for these data sets can be found at:<br /></font></p><p></p><ul><li><font size='3'><a href='https://gis.blm.gov/utarcgis/rest/services/Recreation/BLM_UT_RecAreas/FeatureServer/0/metadata' target='_blank' rel='nofollow ugc noopener noreferrer'><font color='#4169e1'><u>BLM UT Congressionally Designated Recreation Areas (Arc)</u></font></a><br /></font></li><li><a href='https://gis.blm.gov/utarcgis/rest/services/Recreation/BLM_UT_RecAreas/FeatureServer/1/metadata' target='_blank' rel='nofollow ugc noopener noreferrer'><font color='#4169e1' size='3'><u>BLM UT Congressionally Designated Recreation Areas (Polygon)</u></font></a><br /></li></ul><p></p></div></div></div>","distribution_titles":["CSV","File Geodatabase","GeoJSON","KML","Shapefile","ArcGIS Hub Dataset","ArcGIS GeoService","ISO-19139 metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/dd5b2bbe-9fdb-4493-a94a-ea44609c3030","harvest_record_raw":"https://catalog.data.gov/harvest_record/dd5b2bbe-9fdb-4493-a94a-ea44609c3030/raw","has_download":false,"has_spatial":true,"identifier":"https://blm-egis.maps.arcgis.com/home/item.html?id=7e6f5bcf96ad4ddd8bf1b30e3fde21ff&sublayer=0","keyword":["BLM","Bureau of Land Management","Geospatial","Management","Public Lands","Recreation","Recreation Areas","UT","Utah","Wilderness","Withdrawal","boundaries","environment","planningCadastre"],"last_harvested_date":"2026-09-05T18:37:40.034869","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":0,"publisher":"Bureau of Land Management","slug":"blm-ut-congressionally-designated-recreation-areas-arc","spatial_centroid":{"lat":38.931,"lon":-110.82087999999999},"spatial_shape":{"coordinates":[[[-111.1026,39.2194],[-111.1026,38.4984],[-110.3983,38.4984],[-110.3983,39.2194],[-111.1026,39.2194]]],"type":"Polygon"},"theme":["geospatial"],"title":"BLM UT Congressionally Designated Recreation Areas (Arc)","type":"dataset"},{"_score":9.899342,"_sort":[1788633457807,9.899342,3,"90041f15-0e41-449e-b983-49696ba563f4"],"dcat":{"accessLevel":"public","bureauCode":["010:04"],"contactPoint":{"@type":"vcard:Contact","fn":"Bureau of Land Management, rjcarter","hasEmail":"mailto:rjcarter@blm.gov"},"description":"SAMPLE_PT: This dataset represents monitoring and sample locations (points). Monitoring is a generic term describing various kinds of assessments that the BLM makes on public land natural resources and/or management actions undertaken. The SAMPLE_PT dataset represents places where a measurement of some type has occurred. Examples of measurement types are: vegetation transects or plots, soil pit descriptions, and observations/photos of resource use or impact. For full documentation see SAMPLE POINTS SPATIAL DATA STANDARD. http://www.blm.gov/or/efoia/fy2012/im/p/im-or-2012-051.pdf","distribution":[{"@type":"dcat:Distribution","accessURL":"https://blm-egis.maps.arcgis.com/sharing/rest/content/items/e8d0b8852ad1498ab300b6419f31cc27/info/metadata/metadata.xml?format=iso19139","mediaType":"text/xml","title":"ISO-19139 metadata"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/e8d0b8852ad1498ab300b6419f31cc27/csv?layers=0","format":"CSV","mediaType":"text/csv","title":"CSV"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/e8d0b8852ad1498ab300b6419f31cc27/excel?layers=0","format":"XLSX","mediaType":"application/vnd.openxmlformats-officedocument.spreadsheetml.sheet","title":"Excel"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/e8d0b8852ad1498ab300b6419f31cc27/featureCollection?layers=0","format":"TXT","mediaType":"text/plain","title":"Feature Collection"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/e8d0b8852ad1498ab300b6419f31cc27/filegdb?layers=0","format":"ZIP","mediaType":"application/zip","title":"File Geodatabase"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/e8d0b8852ad1498ab300b6419f31cc27/geojson?layers=0","format":"GeoJSON","mediaType":"application/vnd.geo+json","title":"GeoJSON"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/e8d0b8852ad1498ab300b6419f31cc27/gpkg?layers=0","format":"ZIP","mediaType":"application/geopackage+sqlite3","title":"GeoPackage"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/e8d0b8852ad1498ab300b6419f31cc27/kml?layers=0","format":"KML","mediaType":"application/vnd.google-earth.kml+xml","title":"KML"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/e8d0b8852ad1498ab300b6419f31cc27/shapefile?layers=0","format":"ZIP","mediaType":"application/zip","title":"Shapefile"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/e8d0b8852ad1498ab300b6419f31cc27/sqlite?layers=0","format":"GDB","mediaType":"application/geopackage+sqlite3","title":"SQLite"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/datasets/BLM-EGIS::blm-or-monitoring-and-sample-point-hub","format":"Web Page","mediaType":"text/html","title":"ArcGIS Hub Dataset"},{"@type":"dcat:Distribution","accessURL":"https://services1.arcgis.com/KbxwQRRfWyEYLgp4/arcgis/rest/services/BLM_OR_Monitoring_and_Sample_Point_Hub/FeatureServer/0","format":"ArcGIS GeoServices REST API","mediaType":"application/json","title":"ArcGIS GeoService"}],"identifier":"https://blm-egis.maps.arcgis.com/home/item.html?id=e8d0b8852ad1498ab300b6419f31cc27&sublayer=0","issued":"2022-09-22T15:37:23Z","keyword":["Geospatial","Management","Monitoring","Monitoring Points","Oregon","Sample Points","Samples","Vegetation","Washington","biota","environment"],"landingPage":"https://gbp-blm-egis.hub.arcgis.com/datasets/BLM-EGIS::blm-or-monitoring-and-sample-point-hub","license":"http://www.usa.gov/publicdomain/label/1.0/","modified":"2026-09-03T13:11:23Z","programCode":["010:000"],"publisher":{"@type":"org:Organization","name":"Bureau of Land Management"},"spatial":"-125,49,-116,42","theme":["geospatial"],"title":"BLM OR Monitoring and Sample Point Hub"},"description":"SAMPLE_PT: This dataset represents monitoring and sample locations (points). Monitoring is a generic term describing various kinds of assessments that the BLM makes on public land natural resources and/or management actions undertaken. The SAMPLE_PT dataset represents places where a measurement of some type has occurred. Examples of measurement types are: vegetation transects or plots, soil pit descriptions, and observations/photos of resource use or impact. For full documentation see SAMPLE POINTS SPATIAL DATA STANDARD. http://www.blm.gov/or/efoia/fy2012/im/p/im-or-2012-051.pdf","distribution_titles":["ISO-19139 metadata","CSV","Excel","Feature Collection","File Geodatabase","GeoJSON","GeoPackage","KML","Shapefile","SQLite","ArcGIS Hub Dataset","ArcGIS GeoService"],"harvest_record":"https://catalog.data.gov/harvest_record/fe09df1e-44c9-4bc8-8468-ac0f4cbbd128","harvest_record_raw":"https://catalog.data.gov/harvest_record/fe09df1e-44c9-4bc8-8468-ac0f4cbbd128/raw","has_download":false,"has_spatial":true,"identifier":"https://blm-egis.maps.arcgis.com/home/item.html?id=e8d0b8852ad1498ab300b6419f31cc27&sublayer=0","keyword":["Geospatial","Management","Monitoring","Monitoring Points","Oregon","Sample Points","Samples","Vegetation","Washington","biota","environment"],"last_harvested_date":"2026-09-05T18:37:37.807583","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":3,"publisher":"Bureau of Land Management","slug":"blm-or-monitoring-and-sample-point-hub","spatial_centroid":{"lat":46.2,"lon":-121.4},"spatial_shape":{"coordinates":[[[-125,49],[-125,42],[-116,42],[-116,49],[-125,49]]],"type":"Polygon"},"theme":["geospatial"],"title":"BLM OR Monitoring and Sample Point Hub","type":"dataset"},{"_score":10.141787,"_sort":[1788633457490,10.141787,7,"e5853919-d487-4b3b-8cac-f33577272e32"],"dcat":{"accessLevel":"public","bureauCode":["010:04"],"contactPoint":{"@type":"vcard:Contact","fn":"Bureau of Land Management, sjeronimo","hasEmail":"mailto:sjeronimo@blm.gov"},"description":"BURN_POLY: This dataset represents completed burn land treatments on BLM managed lands in the states of Oregon and Washington. Burn treatments are prescribed burning of wildland fuels in either their natural or modified state, and under specified environmental conditions.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://blm-egis.maps.arcgis.com/sharing/rest/content/items/8442ad4f14e14f3b9e91db9d699968b6/info/metadata/metadata.xml?format=iso19139","mediaType":"text/xml","title":"ISO-19139 metadata"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/8442ad4f14e14f3b9e91db9d699968b6/csv?layers=1","format":"CSV","mediaType":"text/csv","title":"CSV"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/8442ad4f14e14f3b9e91db9d699968b6/excel?layers=1","format":"XLSX","mediaType":"application/vnd.openxmlformats-officedocument.spreadsheetml.sheet","title":"Excel"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/8442ad4f14e14f3b9e91db9d699968b6/featureCollection?layers=1","format":"TXT","mediaType":"text/plain","title":"Feature Collection"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/8442ad4f14e14f3b9e91db9d699968b6/filegdb?layers=1","format":"ZIP","mediaType":"application/zip","title":"File Geodatabase"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/8442ad4f14e14f3b9e91db9d699968b6/geojson?layers=1","format":"GeoJSON","mediaType":"application/vnd.geo+json","title":"GeoJSON"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/8442ad4f14e14f3b9e91db9d699968b6/gpkg?layers=1","format":"ZIP","mediaType":"application/geopackage+sqlite3","title":"GeoPackage"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/8442ad4f14e14f3b9e91db9d699968b6/kml?layers=1","format":"KML","mediaType":"application/vnd.google-earth.kml+xml","title":"KML"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/8442ad4f14e14f3b9e91db9d699968b6/shapefile?layers=1","format":"ZIP","mediaType":"application/zip","title":"Shapefile"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/api/download/v1/items/8442ad4f14e14f3b9e91db9d699968b6/sqlite?layers=1","format":"GDB","mediaType":"application/geopackage+sqlite3","title":"SQLite"},{"@type":"dcat:Distribution","accessURL":"https://gbp-blm-egis.hub.arcgis.com/datasets/BLM-EGIS::blm-or-prescribed-fire-treatments-polygon-hub","format":"Web Page","mediaType":"text/html","title":"ArcGIS Hub Dataset"},{"@type":"dcat:Distribution","accessURL":"https://services1.arcgis.com/KbxwQRRfWyEYLgp4/arcgis/rest/services/BLM_OR_Prescribed_Fire_Treatments_Polygon_Hub/FeatureServer/1","format":"ArcGIS GeoServices REST API","mediaType":"application/json","title":"ArcGIS GeoService"}],"identifier":"https://blm-egis.maps.arcgis.com/home/item.html?id=8442ad4f14e14f3b9e91db9d699968b6&sublayer=1","issued":"2022-09-27T13:50:56Z","keyword":["Burn","Completed","Fire","Geospatial","Management","Oregon","Treatments","Vegetation","Washington","biota","environment"],"landingPage":"https://gbp-blm-egis.hub.arcgis.com/datasets/BLM-EGIS::blm-or-prescribed-fire-treatments-polygon-hub","license":"http://www.usa.gov/publicdomain/label/1.0/","modified":"2026-09-02T12:15:21Z","programCode":["010:000"],"publisher":{"@type":"org:Organization","name":"Bureau of Land Management"},"spatial":"-125,49,-116,42","theme":["geospatial"],"title":"BLM OR Prescribed Fire Treatments Polygon Hub"},"description":"BURN_POLY: This dataset represents completed burn land treatments on BLM managed lands in the states of Oregon and Washington. Burn treatments are prescribed burning of wildland fuels in either their natural or modified state, and under specified environmental conditions.","distribution_titles":["ISO-19139 metadata","CSV","Excel","Feature Collection","File Geodatabase","GeoJSON","GeoPackage","KML","Shapefile","SQLite","ArcGIS Hub Dataset","ArcGIS GeoService"],"harvest_record":"https://catalog.data.gov/harvest_record/008386da-8e0c-4370-bafd-d629dd029bc5","harvest_record_raw":"https://catalog.data.gov/harvest_record/008386da-8e0c-4370-bafd-d629dd029bc5/raw","has_download":false,"has_spatial":true,"identifier":"https://blm-egis.maps.arcgis.com/home/item.html?id=8442ad4f14e14f3b9e91db9d699968b6&sublayer=1","keyword":["Burn","Completed","Fire","Geospatial","Management","Oregon","Treatments","Vegetation","Washington","biota","environment"],"last_harvested_date":"2026-09-05T18:37:37.490313","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":7,"publisher":"Bureau of Land Management","slug":"blm-or-prescribed-fire-treatments-polygon-hub","spatial_centroid":{"lat":46.2,"lon":-121.4},"spatial_shape":{"coordinates":[[[-125,49],[-125,42],[-116,42],[-116,49],[-125,49]]],"type":"Polygon"},"theme":["geospatial"],"title":"BLM OR Prescribed Fire Treatments Polygon Hub","type":"dataset"},{"_score":10.22514,"_sort":[1788633240639,10.22514,3,"2c5bba23-c14d-487d-90ba-ce454b31ee54"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Ryan F. Thompson","hasEmail":"mailto:rcthomps@usgs.gov"},"description":"This geospatial data set contains an interpolated 3-D surface or, triangulated-irregular network (TIN), of the \nsubstrate surface between cross-sections 22 and 35 following construction of Emergent Sandbar Habitat \nnear River Mile 770.  The surface was generated from points collected by the echosounder and real-time \nkinematic (RTK) GPS on cross-sections in the downstream project reach surrounding the construction \narea at River Mile 770 below Gavins Point Dam on the Missouri River in South Dakota.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://water.usgs.gov/lookup/getspatial?ofr07-1056_up_post_tin","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.817e2f6f-af3e-4cce-92df-47f65c69879a.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_817e2f6f-af3e-4cce-92df-47f65c69879a","keyword":["Hydrographic Survey","USGS:817e2f6f-af3e-4cce-92df-47f65c69879a","environment","geoscientificInformation","inlandWaters"],"modified":"2020-11-17T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-96.876339, 42.712693, -96.851104, 42.732505","theme":["geospatial"],"title":"Postconstruction tin of land surface on the Missouri River downstream from Gavins Point Dam near River Mile 769.8"},"description":"This geospatial data set contains an interpolated 3-D surface or, triangulated-irregular network (TIN), of the \nsubstrate surface between cross-sections 22 and 35 following construction of Emergent Sandbar Habitat \nnear River Mile 770.  The surface was generated from points collected by the echosounder and real-time \nkinematic (RTK) GPS on cross-sections in the downstream project reach surrounding the construction \narea at River Mile 770 below Gavins Point Dam on the Missouri River in South Dakota.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/eaf71a26-e769-46bb-9126-db0e312d8718","harvest_record_raw":"https://catalog.data.gov/harvest_record/eaf71a26-e769-46bb-9126-db0e312d8718/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_817e2f6f-af3e-4cce-92df-47f65c69879a","keyword":["Hydrographic Survey","USGS:817e2f6f-af3e-4cce-92df-47f65c69879a","environment","geoscientificInformation","inlandWaters"],"last_harvested_date":"2026-09-05T18:34:00.639512","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":3,"publisher":"U.S. Geological Survey","slug":"postconstruction-tin-of-land-surface-on-the-missouri-river-downstream-from-gavins-point-da","spatial_centroid":{"lat":42.7206178,"lon":-96.866245},"spatial_shape":{"coordinates":[[[-96.876339,42.712693],[-96.876339,42.732505],[-96.851104,42.732505],[-96.851104,42.712693],[-96.876339,42.712693]]],"type":"Polygon"},"theme":["geospatial"],"title":"Postconstruction tin of land surface on the Missouri River downstream from Gavins Point Dam near River Mile 769.8","type":"dataset"},{"_score":9.030353,"_sort":[1788633133163,9.030353,1,"801011d8-3cb2-4d6f-b4bc-f837e77a2d33"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Ronald B. Zelt","hasEmail":"mailto:rbzelt@usgs.gov"},"description":"Mineral resource areas are defined as those areas with a high likelihood of containing occurrences of valuable mineral deposits.  A variety of sources of minerals information were consulted in compiling a digital map of mineral resource areas for metallic minerals in the Yellowstone River Basin. Source scales varied, but were no smaller than 1:500,000.  The data are intended for river-basin level assessment and general analysis and are not suitable for site-specific analyses.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/p9q9d135","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.b5b40ce4-0aca-4cc1-bf76-7e59d46122fa.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_b5b40ce4-0aca-4cc1-bf76-7e59d46122fa","keyword":["Montana","USGS:b5b40ce4-0aca-4cc1-bf76-7e59d46122fa","Wyoming","Yellowstone River","Yellowstone River Basin","environment","geoscientificInformation","inlandWaters","metals","mineral deposits","mineralized areas","uranium"],"modified":"2004-11-08T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-110.7513, 42.4787, -105.6860, 45.6279","theme":["geospatial"],"title":"Mineral resource areas of the Yellowstone River Basin, Montana and Wyoming"},"description":"Mineral resource areas are defined as those areas with a high likelihood of containing occurrences of valuable mineral deposits.  A variety of sources of minerals information were consulted in compiling a digital map of mineral resource areas for metallic minerals in the Yellowstone River Basin. Source scales varied, but were no smaller than 1:500,000.  The data are intended for river-basin level assessment and general analysis and are not suitable for site-specific analyses.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/10aa6e87-962f-4ed5-a69c-79f847afcf29","harvest_record_raw":"https://catalog.data.gov/harvest_record/10aa6e87-962f-4ed5-a69c-79f847afcf29/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_b5b40ce4-0aca-4cc1-bf76-7e59d46122fa","keyword":["Montana","USGS:b5b40ce4-0aca-4cc1-bf76-7e59d46122fa","Wyoming","Yellowstone River","Yellowstone River Basin","environment","geoscientificInformation","inlandWaters","metals","mineral deposits","mineralized areas","uranium"],"last_harvested_date":"2026-09-05T18:32:13.163892","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":1,"publisher":"U.S. Geological Survey","slug":"mineral-resource-areas-of-the-yellowstone-river-basin-montana-and-wyoming","spatial_centroid":{"lat":43.73838,"lon":-108.72518},"spatial_shape":{"coordinates":[[[-110.7513,42.4787],[-110.7513,45.6279],[-105.686,45.6279],[-105.686,42.4787],[-110.7513,42.4787]]],"type":"Polygon"},"theme":["geospatial"],"title":"Mineral resource areas of the Yellowstone River Basin, Montana and Wyoming","type":"dataset"},{"_score":10.22514,"_sort":[1788633107068,10.22514,3,"bedaa09e-ea00-4ad9-9b43-27c05a7ac753"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Ryan F. Thompson","hasEmail":"mailto:rcthomps@usgs.gov"},"description":"This data set contains land surface elevations on dry and wadeable portions of transects for the hydrographic \nsurveys on the Missouri River below Gavins Point Dam near River Mile 769.8.  This data provides land surface \nelevations of shallow-water, shore, and highbank for the Missouri River following construction of Emergent \nSandbar Habitat.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://water.usgs.gov/GIS/dsdl/up_post_gps.zip","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.1c1dd2c7-efbe-4def-afff-1138dc63fbe9.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_1c1dd2c7-efbe-4def-afff-1138dc63fbe9","keyword":["Hydrographic Survey","USGS:1c1dd2c7-efbe-4def-afff-1138dc63fbe9","environment","geoscientificInformation","inlandWaters"],"modified":"2020-11-17T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-96.913901, 42.701339, -96.822211, 42.737252","theme":["geospatial"],"title":"GPS data collected for transects as part of the post-construction survey at Emergent Sandbar Habitat site on the Missouri River near river mile 769.8"},"description":"This data set contains land surface elevations on dry and wadeable portions of transects for the hydrographic \nsurveys on the Missouri River below Gavins Point Dam near River Mile 769.8.  This data provides land surface \nelevations of shallow-water, shore, and highbank for the Missouri River following construction of Emergent \nSandbar Habitat.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/4008dcd0-b76e-4833-86ee-ac6178560112","harvest_record_raw":"https://catalog.data.gov/harvest_record/4008dcd0-b76e-4833-86ee-ac6178560112/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_1c1dd2c7-efbe-4def-afff-1138dc63fbe9","keyword":["Hydrographic Survey","USGS:1c1dd2c7-efbe-4def-afff-1138dc63fbe9","environment","geoscientificInformation","inlandWaters"],"last_harvested_date":"2026-09-05T18:31:47.068717","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":3,"publisher":"U.S. Geological Survey","slug":"gps-data-collected-for-transects-as-part-of-the-post-construction-survey-at-emergent-sandb","spatial_centroid":{"lat":42.7157042,"lon":-96.877225},"spatial_shape":{"coordinates":[[[-96.913901,42.701339],[-96.913901,42.737252],[-96.822211,42.737252],[-96.822211,42.701339],[-96.913901,42.701339]]],"type":"Polygon"},"theme":["geospatial"],"title":"GPS data collected for transects as part of the post-construction survey at Emergent Sandbar Habitat site on the Missouri River near river mile 769.8","type":"dataset"},{"_score":8.96336,"_sort":[1788632557153,8.96336,2,"111b902a-b408-48f9-b933-5ead1b570e93"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Luke Winslow","hasEmail":"mailto:lwinslow@usgs.gov"},"description":"It is well recognized that the climate is warming in response to anthropogenic emission of greenhouse gases. Over the last decade, this has had a warming effect on lakes. Water clarity is also known to effect water temperature in lakes. What is unclear is how a warming climate might interact with changes in water clarity in lakes. As part of a project at the USGS Office of Water Information, several water clarity scenarios were simulated for lakes in Wisconsin to examine how changing water clarity interacts with climate change to affect lake temperatures at a broad scale.\nThis data set contains the following parameters: year, WBIC, durStrat, max_schmidt_stability, mean_schmidt_stability_JAS, mean_schmidt_stability_July, SthermoD_mean_JAS, SthermoD_mean, lake_average_temp, peak_lake_average_temp, lake_average_temp_JAS, mean_epi_temp, mean_hypo_temp, mean_surf_temp, mean_bottom_temp, peak_surf_temp, peak_bottom_temp, mean_surf_temp_JAS, mean_bottom_temp_JAS, mean_bottom_temp_365, mean_surf_temp_365, mean_1m_temp, mean_surf_JA, GDD_wtr_5c, GDD_wtr_10c, volume_mean_m_3, simulation_length_days, mean_volumetric_temp, kd, out_val calculated for 2210 lakes.","distribution":[{"@type":"dcat:Distribution","accessURL":"http://dx.doi.org/10.5066/F7028PN4","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.5747345ae4b07e28b663d81e.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_5747345ae4b07e28b663d81e","keyword":["007","012","US","USGS:5747345ae4b07e28b663d81e","United States","WI","Wisconsin","climate change","environment","hydrodynamic model","inlandWaters","lakes","limnology","water clarity","water quality","water temperature"],"modified":"2026-09-03T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-92.91, 42.48, -86.75, 47.54","theme":["geospatial"],"title":"Wisconsin Lake Temperature Metrics Increasing Clarity"},"description":"It is well recognized that the climate is warming in response to anthropogenic emission of greenhouse gases. Over the last decade, this has had a warming effect on lakes. Water clarity is also known to effect water temperature in lakes. What is unclear is how a warming climate might interact with changes in water clarity in lakes. As part of a project at the USGS Office of Water Information, several water clarity scenarios were simulated for lakes in Wisconsin to examine how changing water clarity interacts with climate change to affect lake temperatures at a broad scale.\nThis data set contains the following parameters: year, WBIC, durStrat, max_schmidt_stability, mean_schmidt_stability_JAS, mean_schmidt_stability_July, SthermoD_mean_JAS, SthermoD_mean, lake_average_temp, peak_lake_average_temp, lake_average_temp_JAS, mean_epi_temp, mean_hypo_temp, mean_surf_temp, mean_bottom_temp, peak_surf_temp, peak_bottom_temp, mean_surf_temp_JAS, mean_bottom_temp_JAS, mean_bottom_temp_365, mean_surf_temp_365, mean_1m_temp, mean_surf_JA, GDD_wtr_5c, GDD_wtr_10c, volume_mean_m_3, simulation_length_days, mean_volumetric_temp, kd, out_val calculated for 2210 lakes.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/e4f46541-3a85-42ab-99be-3522da487fc9","harvest_record_raw":"https://catalog.data.gov/harvest_record/e4f46541-3a85-42ab-99be-3522da487fc9/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_5747345ae4b07e28b663d81e","keyword":["007","012","US","USGS:5747345ae4b07e28b663d81e","United States","WI","Wisconsin","climate change","environment","hydrodynamic model","inlandWaters","lakes","limnology","water clarity","water quality","water temperature"],"last_harvested_date":"2026-09-05T18:22:37.153512","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":2,"publisher":"U.S. Geological Survey","slug":"wisconsin-lake-temperature-metrics-increasing-clarity","spatial_centroid":{"lat":44.504,"lon":-90.446},"spatial_shape":{"coordinates":[[[-92.91,42.48],[-92.91,47.54],[-86.75,47.54],[-86.75,42.48],[-92.91,42.48]]],"type":"Polygon"},"theme":["geospatial"],"title":"Wisconsin Lake Temperature Metrics Increasing Clarity","type":"dataset"},{"_score":10.400936,"_sort":[1788632356027,10.400936,2,"7ce335ed-1386-489a-ae8a-98892f03948e"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Ryan F. Thompson","hasEmail":"mailto:rcthomps@usgs.gov"},"description":"This geospatial data set contains the points collected by the echosounder on transects in the \ndownstream project reach surrounding the construction area at River Mile 761.4 below Gavins \nPoint Dam on the Missouri River in South Dakota.  This survey provides channel cross sections \napproximately every 500 feet prior to construction of Emergent Sandbar Habitat near River \nMile 761.4","distribution":[{"@type":"dcat:Distribution","accessURL":"https://water.usgs.gov/GIS/dsdl/dn_pre_bathy.zip","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.e8a3fa64-8a22-4a12-b3cc-33df260133f3.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_e8a3fa64-8a22-4a12-b3cc-33df260133f3","keyword":["Hydrographic Survey","USGS:e8a3fa64-8a22-4a12-b3cc-33df260133f3","environment","geoscientificInformation","inlandWaters"],"modified":"2020-11-17T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-96.799768, 42.654850, -96.701205, 42.670947","theme":["geospatial"],"title":"Bathymetry data for the pre-construction survey of the Emergent Sandbar Habitat project at river mile 761.4 downstream from Gavins Point dam on the Missouri River."},"description":"This geospatial data set contains the points collected by the echosounder on transects in the \ndownstream project reach surrounding the construction area at River Mile 761.4 below Gavins \nPoint Dam on the Missouri River in South Dakota.  This survey provides channel cross sections \napproximately every 500 feet prior to construction of Emergent Sandbar Habitat near River \nMile 761.4","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/47ba9fa4-3bce-4d38-a3ca-bef0cdddcb89","harvest_record_raw":"https://catalog.data.gov/harvest_record/47ba9fa4-3bce-4d38-a3ca-bef0cdddcb89/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_e8a3fa64-8a22-4a12-b3cc-33df260133f3","keyword":["Hydrographic Survey","USGS:e8a3fa64-8a22-4a12-b3cc-33df260133f3","environment","geoscientificInformation","inlandWaters"],"last_harvested_date":"2026-09-05T18:19:16.027771","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":2,"publisher":"U.S. Geological Survey","slug":"bathymetry-data-for-the-pre-construction-survey-of-the-emergent-sandbar-habitat-project-at","spatial_centroid":{"lat":42.6612888,"lon":-96.7603428},"spatial_shape":{"coordinates":[[[-96.799768,42.65485],[-96.799768,42.670947],[-96.701205,42.670947],[-96.701205,42.65485],[-96.799768,42.65485]]],"type":"Polygon"},"theme":["geospatial"],"title":"Bathymetry data for the pre-construction survey of the Emergent Sandbar Habitat project at river mile 761.4 downstream from Gavins Point dam on the Missouri River.","type":"dataset"},{"_score":10.532825,"_sort":[1788632173313,10.532825,0,"c3bc1f63-172b-4add-b1b3-82dd5a68553d"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Climate Adaptation Science Centers","hasEmail":"mailto:casc-data@usgs.gov"},"description":"While climate change is rapidly warming lakes and reservoirs, warming rates can be highly variable among systems because lake characteristics can modulate atmospheric forcing. While it is known that water clarity changes can alter lake water temperatures, it is unknown if frequently observed water clarity trends are sufficient to meaningfully impact the thermal trajectories of diverse lake populations. Using process-based modeling and empirical observations, this study demonstrates that water clarity changes of about 1% per year amplifies or suppresses warming at rates comparable to climate-induced warming. These results demonstrate that trends in water clarity, which are occurring in many lakes, may be as important as rising air temperatures in determining how waterbodies respond to climate change.\nThese data support the following publication:  \nJordan S. Read, Luke A. Winslow, Gretchen J.A. Hansen, Jamon Van Den Hoek, Paul C. Hanson, Louise C. Bruce, 2014, Simulating 2368 temperate lakes reveals weak coherence in stratification phenology: Ecological Modeling, http://dx.doi.org/10.1016/j.ecolmodel.2014.07.029.","distribution":[{"@type":"dcat:Distribution","accessURL":"http://dx.doi.org/10.5066/F7028PN4","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.5735f0f2e4b0dae0d5df6c67.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_5735f0f2e4b0dae0d5df6c67","keyword":["USGS:5735f0f2e4b0dae0d5df6c67","climate change","environment","lakes","pre-SM502.8"],"modified":"2026-09-03T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-92.8800, 42.4800, -86.8000, 47.0700","theme":["geospatial"],"title":"Climate warming of Wisconsin lakes can be either amplified or suppressed by trends in water clarity"},"description":"While climate change is rapidly warming lakes and reservoirs, warming rates can be highly variable among systems because lake characteristics can modulate atmospheric forcing. While it is known that water clarity changes can alter lake water temperatures, it is unknown if frequently observed water clarity trends are sufficient to meaningfully impact the thermal trajectories of diverse lake populations. Using process-based modeling and empirical observations, this study demonstrates that water clarity changes of about 1% per year amplifies or suppresses warming at rates comparable to climate-induced warming. These results demonstrate that trends in water clarity, which are occurring in many lakes, may be as important as rising air temperatures in determining how waterbodies respond to climate change.\nThese data support the following publication:  \nJordan S. Read, Luke A. Winslow, Gretchen J.A. Hansen, Jamon Van Den Hoek, Paul C. Hanson, Louise C. Bruce, 2014, Simulating 2368 temperate lakes reveals weak coherence in stratification phenology: Ecological Modeling, http://dx.doi.org/10.1016/j.ecolmodel.2014.07.029.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/a53f98c2-98b9-431f-bb85-4e2967a9d414","harvest_record_raw":"https://catalog.data.gov/harvest_record/a53f98c2-98b9-431f-bb85-4e2967a9d414/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_5735f0f2e4b0dae0d5df6c67","keyword":["USGS:5735f0f2e4b0dae0d5df6c67","climate change","environment","lakes","pre-SM502.8"],"last_harvested_date":"2026-09-05T18:16:13.313755","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":0,"publisher":"U.S. Geological Survey","slug":"climate-warming-of-wisconsin-lakes-can-be-either-amplified-or-suppressed-by-trends-in-wate","spatial_centroid":{"lat":44.315999999999995,"lon":-90.44800000000001},"spatial_shape":{"coordinates":[[[-92.88,42.48],[-92.88,47.07],[-86.8,47.07],[-86.8,42.48],[-92.88,42.48]]],"type":"Polygon"},"theme":["geospatial"],"title":"Climate warming of Wisconsin lakes can be either amplified or suppressed by trends in water clarity","type":"dataset"},{"_score":10.269945,"_sort":[1788631960074,10.269945,4,"fa1dc7f2-b2d9-4436-bd3e-e2d07b89003a"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Ryan F. Thompson","hasEmail":"mailto:rcthomps@usgs.gov"},"description":"This geospatial data set contains the points collected by the echosounder on transects in the \nupstream project reach surrounding the construction area at River Mile 769.8 below Gavins \nPoint Dam on the Missouri River in South Dakota.  This survey provides channel cross sections \nfor new and selected existing transects following construction of Emergent Sandbar Habitat \nnear River Mile 769.8","distribution":[{"@type":"dcat:Distribution","accessURL":"https://water.usgs.gov/GIS/dsdl/up_post_bathy.zip","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.e26db77b-f122-4ba0-b2ad-f20c347003f5.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_e26db77b-f122-4ba0-b2ad-f20c347003f5","keyword":["Hydrographic Survey","USGS:e26db77b-f122-4ba0-b2ad-f20c347003f5","environment","geoscientificInformation","inlandWaters"],"modified":"2020-11-17T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-96.912030, 42.701452, -96.822611, 42.736188","theme":["geospatial"],"title":"Bathymetry data for the post-construction survey of the Emergent Sandbar Habitat project at river mile 769.8 downstream from Gavins Point Dam on the Missouri River."},"description":"This geospatial data set contains the points collected by the echosounder on transects in the \nupstream project reach surrounding the construction area at River Mile 769.8 below Gavins \nPoint Dam on the Missouri River in South Dakota.  This survey provides channel cross sections \nfor new and selected existing transects following construction of Emergent Sandbar Habitat \nnear River Mile 769.8","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/d1697da2-7642-4898-81e3-971b678e3a1f","harvest_record_raw":"https://catalog.data.gov/harvest_record/d1697da2-7642-4898-81e3-971b678e3a1f/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_e26db77b-f122-4ba0-b2ad-f20c347003f5","keyword":["Hydrographic Survey","USGS:e26db77b-f122-4ba0-b2ad-f20c347003f5","environment","geoscientificInformation","inlandWaters"],"last_harvested_date":"2026-09-05T18:12:40.074075","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":4,"publisher":"U.S. Geological Survey","slug":"bathymetry-data-for-the-post-construction-survey-of-the-emergent-sandbar-habitat-project-a","spatial_centroid":{"lat":42.7153464,"lon":-96.8762624},"spatial_shape":{"coordinates":[[[-96.91203,42.701452],[-96.91203,42.736188],[-96.822611,42.736188],[-96.822611,42.701452],[-96.91203,42.701452]]],"type":"Polygon"},"theme":["geospatial"],"title":"Bathymetry data for the post-construction survey of the Emergent Sandbar Habitat project at river mile 769.8 downstream from Gavins Point Dam on the Missouri River.","type":"dataset"},{"_score":10.266226,"_sort":[1788631877143,10.266226,1,"b6caff4c-d0f5-482b-af09-8ec58d7aadf0"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Ryan F. Thompson","hasEmail":"mailto:rcthomps@usgs.gov"},"description":"This data set contains land surface elevations on dry and wadeable portions of transects for the \nhydrographic surveys on the Missouri River below Gavins Point Dam near River Mile 761.4.  This \ndata provides land surface elevations of shallow-water, shore, and highbank for the Missouri River \nfollowing construction of Emergent Sandbar Habitat.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://water.usgs.gov/GIS/dsdl/dn_post_gps.zip","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.e92cc781-ee80-4609-8733-54072c302ca2.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_e92cc781-ee80-4609-8733-54072c302ca2","keyword":["Hydrographic Survey","USGS:e92cc781-ee80-4609-8733-54072c302ca2","environment","geoscientificInformation","inlandWaters"],"modified":"2020-11-17T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-96.800230, 42.654601, -96.700315, 42.673551","theme":["geospatial"],"title":"GPS data collected for postconstruction hydrographic surveys of Missouri River downstream from Gavins Point Dam near river mile 761.4"},"description":"This data set contains land surface elevations on dry and wadeable portions of transects for the \nhydrographic surveys on the Missouri River below Gavins Point Dam near River Mile 761.4.  This \ndata provides land surface elevations of shallow-water, shore, and highbank for the Missouri River \nfollowing construction of Emergent Sandbar Habitat.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/76724715-562e-4722-9e3a-57c4f5fbfb79","harvest_record_raw":"https://catalog.data.gov/harvest_record/76724715-562e-4722-9e3a-57c4f5fbfb79/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_e92cc781-ee80-4609-8733-54072c302ca2","keyword":["Hydrographic Survey","USGS:e92cc781-ee80-4609-8733-54072c302ca2","environment","geoscientificInformation","inlandWaters"],"last_harvested_date":"2026-09-05T18:11:17.143683","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":1,"publisher":"U.S. Geological Survey","slug":"gps-data-collected-for-postconstruction-hydrographic-surveys-of-missouri-river-downstream-","spatial_centroid":{"lat":42.662181,"lon":-96.760264},"spatial_shape":{"coordinates":[[[-96.80023,42.654601],[-96.80023,42.673551],[-96.700315,42.673551],[-96.700315,42.654601],[-96.80023,42.654601]]],"type":"Polygon"},"theme":["geospatial"],"title":"GPS data collected for postconstruction hydrographic surveys of Missouri River downstream from Gavins Point Dam near river mile 761.4","type":"dataset"},{"_score":9.030353,"_sort":[1788631796422,9.030353,0,"79aa5f01-cab1-4354-ae5d-003be68b71b6"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Kimberley Davis","hasEmail":"mailto:Kimberley.davis@usda.gov"},"description":"This dataset includes spatial projections of the post-fire recruitment index for ponderosa pine (Pinus ponderosa) and Douglas-fir (Pseudotsuga menziesii) using climate data from different time periods (1980-1989, 1990-1999, 2000-2009, 2010-2014) and a future climate scenario of a global mean increase in temperature of two degrees Celsius. The post-fire recruitment index varies from 0 to 1 and represents the proportion of the first five years following wildfire that had climate suitable for regeneration of the given species. We chose a five-year window because the majority (69%) of recruitment across all sites in the dataset used to build our recruitment models occurred within the first five post-fire years. In the projections, climate and time since fire varies by year but other predictors stay constant at fixed values. Distance to seed source was set at 50 m and fire severity, measured as the differenced normalized burn ratio (dNBR), was set at 400 for all projections. Because we hold distance to seed source and fire severity constant, the post-fire recruitment index is interpreted as the climate suitability for post-fire recruitment, under the given scenario. We recognize that post-fire recruitment is also influenced by other local factors that are unaccounted for in our models, including biotic interactions, such as herbivory and competition, and abiotic factors, such as substrate, topography and soil moisture.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.21429/hzh5-6h93","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.633f1aebd34e342aee062eee.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_633f1aebd34e342aee062eee","keyword":["Pinus ponderosa","Pseudotsuga menziesii","USGS:633f1aebd34e342aee062eee","biota","environment","external research support","fires","geospatial datasets","modeling","post-fire regeneration","tree regeneration","wildfire"],"modified":"2026-09-03T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-120.5420, 31.3161, -103.2715, 48.9514","theme":["geospatial"],"title":"Maps of post-fire conifer recruitment from: Fire-catalyzed vegetation shifts in ponderosa pine and Douglas-fir forests of the western United States"},"description":"This dataset includes spatial projections of the post-fire recruitment index for ponderosa pine (Pinus ponderosa) and Douglas-fir (Pseudotsuga menziesii) using climate data from different time periods (1980-1989, 1990-1999, 2000-2009, 2010-2014) and a future climate scenario of a global mean increase in temperature of two degrees Celsius. The post-fire recruitment index varies from 0 to 1 and represents the proportion of the first five years following wildfire that had climate suitable for regeneration of the given species. We chose a five-year window because the majority (69%) of recruitment across all sites in the dataset used to build our recruitment models occurred within the first five post-fire years. In the projections, climate and time since fire varies by year but other predictors stay constant at fixed values. Distance to seed source was set at 50 m and fire severity, measured as the differenced normalized burn ratio (dNBR), was set at 400 for all projections. Because we hold distance to seed source and fire severity constant, the post-fire recruitment index is interpreted as the climate suitability for post-fire recruitment, under the given scenario. We recognize that post-fire recruitment is also influenced by other local factors that are unaccounted for in our models, including biotic interactions, such as herbivory and competition, and abiotic factors, such as substrate, topography and soil moisture.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/ed2483da-0f1d-4043-a36a-05d43e4e6956","harvest_record_raw":"https://catalog.data.gov/harvest_record/ed2483da-0f1d-4043-a36a-05d43e4e6956/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_633f1aebd34e342aee062eee","keyword":["Pinus ponderosa","Pseudotsuga menziesii","USGS:633f1aebd34e342aee062eee","biota","environment","external research support","fires","geospatial datasets","modeling","post-fire regeneration","tree regeneration","wildfire"],"last_harvested_date":"2026-09-05T18:09:56.422487","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":0,"publisher":"U.S. Geological Survey","slug":"maps-of-post-fire-conifer-recruitment-from-fire-catalyzed-vegetation-shifts-in-ponderosa-p","spatial_centroid":{"lat":38.37022,"lon":-113.6338},"spatial_shape":{"coordinates":[[[-120.542,31.3161],[-120.542,48.9514],[-103.2715,48.9514],[-103.2715,31.3161],[-120.542,31.3161]]],"type":"Polygon"},"theme":["geospatial"],"title":"Maps of post-fire conifer recruitment from: Fire-catalyzed vegetation shifts in ponderosa pine and Douglas-fir forests of the western United States","type":"dataset"},{"_score":12.952427,"_sort":[1788631663944,12.952427,1,"516e0bea-1f12-4a8f-8eaa-f80cd34baeb4"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Elizabeth Tomaszewski","hasEmail":"mailto:etomaszewski@usgs.gov"},"description":"This data set was collected throughout the Gallinas watershed in New, Mexico following the Hermit's Peak-Calf Canyon fires on April 6, 2022. The watershed has a history of mining and prospecting, which acts as an additional stressor to post-wildfire water quality and ecosystem health. Water samples were collected immediately post-fire. Water, sediment deposit and bed sediment samples were collected in October 2022 and April 2023, 6 months and 1-year post-fire. Samples were collected from Gallinas Creek and its tributaries. Geochemical analyses of water samples include major and trace metals via inductively coupled plasma optical emission spectroscopy and plasma mass spectrometry (ICP-MS), total organic carbon, and major anions (sulfate, nitrate). Sediment deposit samples were exposed to various extractions including water extractions, sequential extractions and aqua regia. The extractions were analyzed for major and trace metals via inductively coupled plasma optical emission spectroscopy (ICP-OES) and ICP-MS, total organic carbon, and major anions (sulfate, nitrate). Weight percentage of carbon and nitrogen in the sediment deposits were also analyzed. Bed sediments were digested with aqua regia and analyzed for metals via ICP-MS. The data collectively demonstrate the effects of wildfire in a disturbed environment on water quality and ecosystem health.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P9IN3YOR","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.65566a7ed34ee4b6e05c4e71.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_65566a7ed34ee4b6e05c4e71","keyword":["USGS:65566a7ed34ee4b6e05c4e71","biota","geochemistry; wildfire;"],"modified":"2026-09-03T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-105.43070, 35.64853, -105.31800, 35.73154","theme":["geospatial"],"title":"Water and sediment geochemistry in the Gallinas Creek Watershed, New Mexico following the Hermits Peak-Calf Canyon fire 2022-2023"},"description":"This data set was collected throughout the Gallinas watershed in New, Mexico following the Hermit's Peak-Calf Canyon fires on April 6, 2022. The watershed has a history of mining and prospecting, which acts as an additional stressor to post-wildfire water quality and ecosystem health. Water samples were collected immediately post-fire. Water, sediment deposit and bed sediment samples were collected in October 2022 and April 2023, 6 months and 1-year post-fire. Samples were collected from Gallinas Creek and its tributaries. Geochemical analyses of water samples include major and trace metals via inductively coupled plasma optical emission spectroscopy and plasma mass spectrometry (ICP-MS), total organic carbon, and major anions (sulfate, nitrate). Sediment deposit samples were exposed to various extractions including water extractions, sequential extractions and aqua regia. The extractions were analyzed for major and trace metals via inductively coupled plasma optical emission spectroscopy (ICP-OES) and ICP-MS, total organic carbon, and major anions (sulfate, nitrate). Weight percentage of carbon and nitrogen in the sediment deposits were also analyzed. Bed sediments were digested with aqua regia and analyzed for metals via ICP-MS. The data collectively demonstrate the effects of wildfire in a disturbed environment on water quality and ecosystem health.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/bb90b418-2c51-416b-b53e-70f1747da34c","harvest_record_raw":"https://catalog.data.gov/harvest_record/bb90b418-2c51-416b-b53e-70f1747da34c/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_65566a7ed34ee4b6e05c4e71","keyword":["USGS:65566a7ed34ee4b6e05c4e71","biota","geochemistry; wildfire;"],"last_harvested_date":"2026-09-05T18:07:43.944807","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":1,"publisher":"U.S. Geological Survey","slug":"water-and-sediment-geochemistry-in-the-gallinas-creek-watershed-new-mexico-follo-2022-2023","spatial_centroid":{"lat":35.681734,"lon":-105.38561999999999},"spatial_shape":{"coordinates":[[[-105.4307,35.64853],[-105.4307,35.73154],[-105.318,35.73154],[-105.318,35.64853],[-105.4307,35.64853]]],"type":"Polygon"},"theme":["geospatial"],"title":"Water and sediment geochemistry in the Gallinas Creek Watershed, New Mexico following the Hermits Peak-Calf Canyon fire 2022-2023","type":"dataset"},{"_score":9.21921,"_sort":[1788631492491,9.21921,1,"6ac5b77d-b5e4-4832-99e2-040e59375c70"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Ryan F. Thompson","hasEmail":"mailto:rcthomps@usgs.gov"},"description":"This data set contains arrays of water velocity collected on selected transects of the Missouri River \nbelow Gavin's Point Dam near River Mile 769.8.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://water.usgs.gov/GIS/dsdl/up_post_vel_array.zip","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.b769dea1-2cd6-4336-bcd1-232466b91b32.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_b769dea1-2cd6-4336-bcd1-232466b91b32","keyword":["Accoustic Doppler Current Profile data","Missouri River","Nebraska","South Dakota","USGS:b769dea1-2cd6-4336-bcd1-232466b91b32","Water Velocity","environment","geoscientificInformation","inlandWaters"],"modified":"2020-11-17T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-96.912755, 42.701457, -96.822603, 42.736215","theme":["geospatial"],"title":"Postconstruction water velocity arrays collected at selected transects on the Missouri River downstream from Gavins Point Dam near River Mile 769.8"},"description":"This data set contains arrays of water velocity collected on selected transects of the Missouri River \nbelow Gavin's Point Dam near River Mile 769.8.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/0848dee2-eb30-4b42-8d8a-baacbf9d4df6","harvest_record_raw":"https://catalog.data.gov/harvest_record/0848dee2-eb30-4b42-8d8a-baacbf9d4df6/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_b769dea1-2cd6-4336-bcd1-232466b91b32","keyword":["Accoustic Doppler Current Profile data","Missouri River","Nebraska","South Dakota","USGS:b769dea1-2cd6-4336-bcd1-232466b91b32","Water Velocity","environment","geoscientificInformation","inlandWaters"],"last_harvested_date":"2026-09-05T18:04:52.491550","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":1,"publisher":"U.S. Geological Survey","slug":"postconstruction-water-velocity-arrays-collected-at-selected-transects-on-the-missouri-riv","spatial_centroid":{"lat":42.7153602,"lon":-96.8766942},"spatial_shape":{"coordinates":[[[-96.912755,42.701457],[-96.912755,42.736215],[-96.822603,42.736215],[-96.822603,42.701457],[-96.912755,42.701457]]],"type":"Polygon"},"theme":["geospatial"],"title":"Postconstruction water velocity arrays collected at selected transects on the Missouri River downstream from Gavins Point Dam near River Mile 769.8","type":"dataset"},{"_score":6.6669044,"_sort":[1788631082362,6.6669044,6,"d4f53c92-ef00-4049-9da6-8fab8b7501a3"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"U.S. Geological Survey, Alaska Science Center","hasEmail":"mailto:gs-ak_asc_datamanagers@usgs.gov"},"description":"These data are daily summary checklists of all bird species observed at U.S. Geological Survey, Alaska Science Center (ASC) field camps. Data include species observation details such as observers, dates, location, and number of individuals seen.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P950QX28","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.ASC367.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_ASC367","keyword":["Alaska","Albatrosses/Petrels and Allies","Animals/Vertebrates","Biota","Birds","Coastal ecosystems","Cranes","Ducks/Geese/Swans","Eagles/Falcons/Hawks and Allies","Environment","Fowl","Game birds","Loons","Migration (organisms)","Migratory birds","Migratory rates/routes","Migratory species","Owls","Perching Birds","Raptors","Sandpipers","Seabirds","Seasonal distribution","Shorebirds","Songbirds","Tundra ecosystems","USGS:ASC367","United States","Waders/Gulls/Auks and Allies","Waterfowl","Wetland ecosystems","Wildlife"],"modified":"2022-03-10T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"170.0, 25.0, -110.0, 72.0","theme":["geospatial"],"title":"Bird Species Checklists from USGS Alaska Science Center Field Camps"},"description":"These data are daily summary checklists of all bird species observed at U.S. Geological Survey, Alaska Science Center (ASC) field camps. Data include species observation details such as observers, dates, location, and number of individuals seen.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/d742df1d-2993-407d-be17-b51080aaac82","harvest_record_raw":"https://catalog.data.gov/harvest_record/d742df1d-2993-407d-be17-b51080aaac82/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_ASC367","keyword":["Alaska","Albatrosses/Petrels and Allies","Animals/Vertebrates","Biota","Birds","Coastal ecosystems","Cranes","Ducks/Geese/Swans","Eagles/Falcons/Hawks and Allies","Environment","Fowl","Game birds","Loons","Migration (organisms)","Migratory birds","Migratory rates/routes","Migratory species","Owls","Perching Birds","Raptors","Sandpipers","Seabirds","Seasonal distribution","Shorebirds","Songbirds","Tundra ecosystems","USGS:ASC367","United States","Waders/Gulls/Auks and Allies","Waterfowl","Wetland ecosystems","Wildlife"],"last_harvested_date":"2026-09-05T17:58:02.362813","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":6,"publisher":"U.S. Geological Survey","slug":"bird-species-checklists-from-usgs-alaska-science-center-field-camps","spatial_centroid":{"lat":43.8,"lon":58.0},"spatial_shape":{"coordinates":[[[170.0,25.0],[170.0,72.0],[-110.0,72.0],[-110.0,25.0],[170.0,25.0]]],"type":"Polygon"},"theme":["geospatial"],"title":"Bird Species Checklists from USGS Alaska Science Center Field Camps","type":"dataset"},{"_score":8.741451,"_sort":[1788630947829,8.741451,3,"d5510ca0-8b5e-416f-bcbf-e3c284305059"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Richard B. Moore","hasEmail":"mailto:rmoore@usgs.gov"},"description":"Multi Order Hydrologic Position (MOHP) raster datasets: Distance from Stream to \nDivide (DSD) and Lateral Position (LP) have been produced nationally for the 48 \ncontiguous United States at a 30-meter resolution for stream orders 1 through 9.  \nThese data are available for testing as predictor variables for various regional and \nnational groundwater-flow and groundwater-quality statistical models. \n\t  \nThe concept behind MOHP is that for any given point on the earth\u2019s surface there \nis the potential for longer and longer groundwater flow paths as one goes deeper \nand deeper beneath the land surface.  These increasing depths correspond to \nincreasing stream orders.  Or in other words, with increasing depth these paths \nof groundwater flow travel further from divides to point of discharge which are to \nincreasingly larger streams of higher stream order.  \n\t  \nDSD \u2013 Raster \u2013 Distance from Stream to Divide (DSD) rasters have cell values \nequal to the sum of the shortest distance to the stream or associated waterbody \nplus the shortest distance to the matching Thiessen divide. There are 9 rasters \nfor streams orders 1 through 9. Units are in meters.\n\t  \nLP \u2013 Raster -- the lateral position (LP) raster has cell values equal to the shortest \ndistance to the stream or associated waterbody divided by the DSD. There are 9 \nrasters for streams orders 1 through 9.\n\t  \nCombined, these two factors, DSD and LP, provide a measure or description of \npotential distance of groundwater flow to any location along the groundwater flow \npath.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P9ST73KV","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.72bead86-13ef-47b8-9f0c-910061a33c37.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_72bead86-13ef-47b8-9f0c-910061a33c37","keyword":["Canada","Cycle 3","Groundwater","Hydrologic Position","Mexico","NAWQA","National Rasters","Statistical Predictors","USGS:72bead86-13ef-47b8-9f0c-910061a33c37","United States","Water Quality","environment","geoscientificInformation","inlandWaters"],"modified":"2020-11-17T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-127.857240873, 23.2443912389, -65.3748244399, 51.5120922457","theme":["geospatial"],"title":"National Multi Order Hydrologic Position (MOHP - High Resolution) Predictor Data for Groundwater and Groundwater-Quality Modeling"},"description":"Multi Order Hydrologic Position (MOHP) raster datasets: Distance from Stream to \nDivide (DSD) and Lateral Position (LP) have been produced nationally for the 48 \ncontiguous United States at a 30-meter resolution for stream orders 1 through 9.  \nThese data are available for testing as predictor variables for various regional and \nnational groundwater-flow and groundwater-quality statistical models. \n\t  \nThe concept behind MOHP is that for any given point on the earth\u2019s surface there \nis the potential for longer and longer groundwater flow paths as one goes deeper \nand deeper beneath the land surface.  These increasing depths correspond to \nincreasing stream orders.  Or in other words, with increasing depth these paths \nof groundwater flow travel further from divides to point of discharge which are to \nincreasingly larger streams of higher stream order.  \n\t  \nDSD \u2013 Raster \u2013 Distance from Stream to Divide (DSD) rasters have cell values \nequal to the sum of the shortest distance to the stream or associated waterbody \nplus the shortest distance to the matching Thiessen divide. There are 9 rasters \nfor streams orders 1 through 9. Units are in meters.\n\t  \nLP \u2013 Raster -- the lateral position (LP) raster has cell values equal to the shortest \ndistance to the stream or associated waterbody divided by the DSD. There are 9 \nrasters for streams orders 1 through 9.\n\t  \nCombined, these two factors, DSD and LP, provide a measure or description of \npotential distance of groundwater flow to any location along the groundwater flow \npath.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/71ff3bae-7375-4420-8e4b-d8377b90ede3","harvest_record_raw":"https://catalog.data.gov/harvest_record/71ff3bae-7375-4420-8e4b-d8377b90ede3/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_72bead86-13ef-47b8-9f0c-910061a33c37","keyword":["Canada","Cycle 3","Groundwater","Hydrologic Position","Mexico","NAWQA","National Rasters","Statistical Predictors","USGS:72bead86-13ef-47b8-9f0c-910061a33c37","United States","Water Quality","environment","geoscientificInformation","inlandWaters"],"last_harvested_date":"2026-09-05T17:55:47.829893","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":3,"publisher":"U.S. Geological Survey","slug":"national-multi-order-hydrologic-position-mohp-high-resolution-predictor-data-for-groundwat","spatial_centroid":{"lat":34.551471641620005,"lon":-102.86427429976},"spatial_shape":{"coordinates":[[[-127.857240873,23.2443912389],[-127.857240873,51.5120922457],[-65.3748244399,51.5120922457],[-65.3748244399,23.2443912389],[-127.857240873,23.2443912389]]],"type":"Polygon"},"theme":["geospatial"],"title":"National Multi Order Hydrologic Position (MOHP - High Resolution) Predictor Data for Groundwater and Groundwater-Quality Modeling","type":"dataset"},{"_score":12.891962,"_sort":[1788549771588,12.891962,10,"6fb419d7-9511-4360-b3f0-6216d44e5e4e"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","accrualPeriodicity":"R/P1M","contactPoint":{"@type":"vcard:Contact","fn":"U.S. Environmental Protection Agency, Headquarters","hasEmail":"mailto:frs_support@epa.gov"},"describedByType":"application/octet-stream","description":"This web feature service contains location and facility identification information from EPA's Facility Registry System (FRS) for the subset of facilities that link to the Toxic Release Inventory (TRI) System. TRI is a publicly available EPA database reported annually by certain covered industry groups, as well as federal facilities. It contains information about more than 650 toxic chemicals that are being used, manufactured, treated, transported, or released into the environment, and includes information about waste management and pollution prevention activities. FRS identifies and geospatially locates facilities, sites or places subject to environmental regulations or of environmental interest. Using vigorous verification and data management procedures, FRS integrates facility data from EPA's national program systems, other federal agencies, and State and tribal master facility records and provides EPA with a centrally managed, single source of comprehensive and authoritative information on facilities. This data set contains the subset of FRS integrated facilities that link to TRI facilities once the TRI data has been integrated into the FRS database. Additional information on FRS is available at the EPA website https://www.epa.gov/enviro/facility-registry-service-frs. These data are considered sensitive and are restricted to internal use only. The download file and map service are accessible only on the EPA intranet. EPA Category: Mission Sensitive, NARA Category: Critical Infrastructure.","distribution":[{"@type":"dcat:Distribution","describedByType":"application/octet-stream","downloadURL":"https://v18ovhrtay724.aa.ad.epa.gov/FRS/downloads/ESF10.gdb.zip","format":"ZIP","mediaType":"application/zip","title":"Zipped File Geodatabase (Accessible on the EPA Intranet only)"},{"@type":"dcat:Distribution","accessURL":"https://igeo.epa.gov/arcgis/rest/services/OEI/FRS_ESF10/MapServer","describedByType":"application/octet-stream","mediaType":"text/html","title":"ArcGIS Server Map Services (Accessible on the EPA Intranet only)"}],"identifier":"https://edg.epa.gov/WAFer_harvest/ISO/frs-internet_FRS_ER_TRI_metadata.xml","isPartOf":"EPA Facility Registry Service Collection","issued":"2016-06-29T00:00:00.000+00:00","keyword":["New Hampshire","South Dakota","Indiana","Massachusetts","Alaska","Wisconsin","United States (US) (USA)","Utah","Puerto Rico","New Mexico","Iowa","conterminous United States (CONUS)","Hawaii","Tennessee","Mississippi","Maine","Arkansas","North Dakota","Oklahoma","Georgia","Nebraska","Texas","Rhode Island","Pennsylvania","New York","Alabama","Ohio","Oregon","Minnesota","California","Florida","Washington","Maryland","North Carolina","Kansas","Montana","Wyoming","Vermont","Virgin Islands","Arizona","American Samoa","South Carolina","Colorado","Nevada","District of Columbia","Washington DC","Virginia","Idaho","Louisiana","West Virginia","Missouri","Illinois","Connecticut","Delaware","Michigan","Kentucky","New Jersey","Facilities","Waste","Sites","Remediation","Resources","Environmental Management","Cleanup","Contaminant","Compliance","Regulatory","Emergency Response","Toxics","ESF10"],"language":[],"license":"https://creativecommons.org/publicdomain/zero/1.0/","modified":"2016-06-29T00:00:00.000+00:00","publisher":{"@type":"org:Organization","name":"U.S. EPA Office of Environmental Information (OEI)"},"temporal":"2020-12-12T00:00:00+00:00/2020-12-12T00:00:00+00:00","theme":["geospatial"],"title":"EPA Facility Registry Service (FRS): ER_TRI"},"description":"This web feature service contains location and facility identification information from EPA's Facility Registry System (FRS) for the subset of facilities that link to the Toxic Release Inventory (TRI) System. TRI is a publicly available EPA database reported annually by certain covered industry groups, as well as federal facilities. It contains information about more than 650 toxic chemicals that are being used, manufactured, treated, transported, or released into the environment, and includes information about waste management and pollution prevention activities. FRS identifies and geospatially locates facilities, sites or places subject to environmental regulations or of environmental interest. Using vigorous verification and data management procedures, FRS integrates facility data from EPA's national program systems, other federal agencies, and State and tribal master facility records and provides EPA with a centrally managed, single source of comprehensive and authoritative information on facilities. This data set contains the subset of FRS integrated facilities that link to TRI facilities once the TRI data has been integrated into the FRS database. Additional information on FRS is available at the EPA website https://www.epa.gov/enviro/facility-registry-service-frs. These data are considered sensitive and are restricted to internal use only. The download file and map service are accessible only on the EPA intranet. EPA Category: Mission Sensitive, NARA Category: Critical Infrastructure.","distribution_titles":["Zipped File Geodatabase (Accessible on the EPA Intranet only)","ArcGIS Server Map Services (Accessible on the EPA Intranet only)"],"harvest_record":"https://catalog.data.gov/harvest_record/999a1c9c-afcc-44b2-a761-ed8212d74807","harvest_record_raw":"https://catalog.data.gov/harvest_record/999a1c9c-afcc-44b2-a761-ed8212d74807/raw","harvest_record_transformed":"https://catalog.data.gov/harvest_record/999a1c9c-afcc-44b2-a761-ed8212d74807/transformed","has_download":true,"has_spatial":true,"identifier":"https://edg.epa.gov/WAFer_harvest/ISO/frs-internet_FRS_ER_TRI_metadata.xml","keyword":["New Hampshire","South Dakota","Indiana","Massachusetts","Alaska","Wisconsin","United States (US) (USA)","Utah","Puerto Rico","New Mexico","Iowa","conterminous United States (CONUS)","Hawaii","Tennessee","Mississippi","Maine","Arkansas","North Dakota","Oklahoma","Georgia","Nebraska","Texas","Rhode Island","Pennsylvania","New York","Alabama","Ohio","Oregon","Minnesota","California","Florida","Washington","Maryland","North Carolina","Kansas","Montana","Wyoming","Vermont","Virgin Islands","Arizona","American Samoa","South Carolina","Colorado","Nevada","District of Columbia","Washington DC","Virginia","Idaho","Louisiana","West Virginia","Missouri","Illinois","Connecticut","Delaware","Michigan","Kentucky","New Jersey","Facilities","Waste","Sites","Remediation","Resources","Environmental Management","Cleanup","Contaminant","Compliance","Regulatory","Emergency Response","Toxics","ESF10"],"last_harvested_date":"2026-09-04T19:22:51.588434","organization":{"aliases":["EPA"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"82b85475-f85d-404a-b95b-89d1a42e9f6b","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/epa.png","name":"U.S. Environmental Protection Agency","organization_type":"Federal Government","slug":"epa"},"parent_identifier":null,"popularity":10,"publisher":"U.S. EPA Office of Environmental Information (OEI)","slug":"epa-facility-registry-service-frs-er_tri","spatial_centroid":null,"spatial_shape":null,"theme":["geospatial"],"title":"EPA Facility Registry Service (FRS): ER_TRI","type":"dataset"},{"_score":28.238905,"_sort":[1788549770789,28.238905,8,"377f56f8-58ef-4f8b-bb46-f78317e7fdf7"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","contactPoint":{"@type":"vcard:Contact","fn":"U.S. Environmental Protection Agency, Office of Environmental Information, Office of Information Collection","hasEmail":"mailto:frs_support@epa.gov"},"describedByType":"application/octet-stream","description":"To improve public health and the environment, the United States Environmental Protection Agency (USEPA) collects information about facilities, sites, or places subject to environmental regulation or of environmental interest. These data are considered sensitive and are restricted to internal use only. The download file and map service are accessible only on the EPA intranet. EPA Category: Mission Sensitive, NARA Category: Critical Infrastructure.","distribution":[{"@type":"dcat:Distribution","describedByType":"application/octet-stream","downloadURL":"https://v18ovhrtay724.aa.ad.epa.gov/FRS/downloads/ESF10.gdb.zip","format":"ZIP","mediaType":"application/zip","title":"Zipped File Geodatabase (Accessible on the EPA Intranet only)"},{"@type":"dcat:Distribution","accessURL":"https://igeo.epa.gov/arcgis/rest/services/OEI/FRS_ESF10/MapServer","describedByType":"application/octet-stream","mediaType":"text/html","title":"ArcGIS Server Map Services (Accessible on the EPA Intranet only)"}],"identifier":"https://edg.epa.gov/WAFer_harvest/ISO/frs-internet_FRS_ER_STATE_ID_metadata.xml","isPartOf":"EPA Facility Registry Service Collection","issued":"2016-06-29T00:00:00.000+00:00","keyword":["Alaska","Puerto Rico","United States","Washington DC","American Samoa","Virgin Islands","Facilities","Permits","Contaminant","Compliance","Regulatory","Cleanup","Environment","Air","ESF10","ESF3"],"language":[],"license":"https://creativecommons.org/publicdomain/zero/1.0/","modified":"2016-06-29T00:00:00.000+00:00","publisher":{"@type":"org:Organization","name":"U.S. Environmental Protection Agency, Headquarters"},"spatial":"-12.68151645,6.65223303,-138.21454852,61.7110157","theme":["geospatial"],"title":"EPA Facility Registry Service (FRS): ER_STATE_ID"},"description":"To improve public health and the environment, the United States Environmental Protection Agency (USEPA) collects information about facilities, sites, or places subject to environmental regulation or of environmental interest. These data are considered sensitive and are restricted to internal use only. The download file and map service are accessible only on the EPA intranet. EPA Category: Mission Sensitive, NARA Category: Critical Infrastructure.","distribution_titles":["Zipped File Geodatabase (Accessible on the EPA Intranet only)","ArcGIS Server Map Services (Accessible on the EPA Intranet only)"],"harvest_record":"https://catalog.data.gov/harvest_record/f9ebcdff-9c9e-499e-bffc-b47f7a218dac","harvest_record_raw":"https://catalog.data.gov/harvest_record/f9ebcdff-9c9e-499e-bffc-b47f7a218dac/raw","harvest_record_transformed":"https://catalog.data.gov/harvest_record/f9ebcdff-9c9e-499e-bffc-b47f7a218dac/transformed","has_download":true,"has_spatial":true,"identifier":"https://edg.epa.gov/WAFer_harvest/ISO/frs-internet_FRS_ER_STATE_ID_metadata.xml","keyword":["Alaska","Puerto Rico","United States","Washington DC","American Samoa","Virgin Islands","Facilities","Permits","Contaminant","Compliance","Regulatory","Cleanup","Environment","Air","ESF10","ESF3"],"last_harvested_date":"2026-09-04T19:22:50.789697","organization":{"aliases":["EPA"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"82b85475-f85d-404a-b95b-89d1a42e9f6b","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/epa.png","name":"U.S. Environmental Protection Agency","organization_type":"Federal Government","slug":"epa"},"parent_identifier":null,"popularity":8,"publisher":"U.S. Environmental Protection Agency, Headquarters","slug":"epa-facility-registry-service-frs-er_state_id","spatial_centroid":{"lat":28.675746097999998,"lon":-62.894729278},"spatial_shape":{"coordinates":[[[-12.68151645,6.65223303],[-12.68151645,61.7110157],[-138.21454852,61.7110157],[-138.21454852,6.65223303],[-12.68151645,6.65223303]]],"type":"Polygon"},"theme":["geospatial"],"title":"EPA Facility Registry Service (FRS): ER_STATE_ID","type":"dataset"},{"_score":28.238905,"_sort":[1788549770036,28.238905,7,"fa1e4301-1b10-442c-b35c-e11f0fd1f39f"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","contactPoint":{"@type":"vcard:Contact","fn":"U.S. Environmental Protection Agency, Office of Environmental Information, Office of Information Collection","hasEmail":"mailto:frs_support@epa.gov"},"describedByType":"application/octet-stream","description":"To improve public health and the environment, the United States Environmental Protection Agency (USEPA) collects information about facilities, sites, or places subject to environmental regulation or of environmental interest. These data are considered sensitive and are restricted to internal use only. The download file and map service are accessible only on the EPA intranet. EPA Category: Mission Sensitive, NARA Category: Critical Infrastructure.","distribution":[{"@type":"dcat:Distribution","describedByType":"application/octet-stream","downloadURL":"https://v18ovhrtay724.aa.ad.epa.gov/FRS/downloads/ESF10.gdb.zip","format":"ZIP","mediaType":"application/zip","title":"Zipped File Geodatabase (Accessible on the EPA Intranet only)"},{"@type":"dcat:Distribution","accessURL":"https://igeo.epa.gov/arcgis/rest/services/OEI/FRS_ESF10/MapServer","describedByType":"application/octet-stream","mediaType":"text/html","title":"ArcGIS Server Map Services (Accessible on the EPA Intranet only)"}],"identifier":"https://edg.epa.gov/WAFer_harvest/ISO/frs-internet_FRS_ER_SIC_metadata.xml","isPartOf":"EPA Facility Registry Service Collection","issued":"2016-06-29T00:00:00.000+00:00","keyword":["Alaska","Puerto Rico","United States","Washington DC","American Samoa","Virgin Islands","Facilities","Permits","Contaminant","Compliance","Regulatory","Cleanup","Environment","Air","ESF10","ESF3"],"language":[],"license":"https://creativecommons.org/publicdomain/zero/1.0/","modified":"2016-06-29T00:00:00.000+00:00","publisher":{"@type":"org:Organization","name":"U.S. Environmental Protection Agency, Headquarters"},"spatial":"-12.68151645,6.65223303,-138.21454852,61.7110157","theme":["geospatial"],"title":"EPA Facility Registry Service (FRS): ER_SIC"},"description":"To improve public health and the environment, the United States Environmental Protection Agency (USEPA) collects information about facilities, sites, or places subject to environmental regulation or of environmental interest. These data are considered sensitive and are restricted to internal use only. The download file and map service are accessible only on the EPA intranet. EPA Category: Mission Sensitive, NARA Category: Critical Infrastructure.","distribution_titles":["Zipped File Geodatabase (Accessible on the EPA Intranet only)","ArcGIS Server Map Services (Accessible on the EPA Intranet only)"],"harvest_record":"https://catalog.data.gov/harvest_record/95cae05c-5c10-415e-ac49-4f835c5e9bc8","harvest_record_raw":"https://catalog.data.gov/harvest_record/95cae05c-5c10-415e-ac49-4f835c5e9bc8/raw","harvest_record_transformed":"https://catalog.data.gov/harvest_record/95cae05c-5c10-415e-ac49-4f835c5e9bc8/transformed","has_download":true,"has_spatial":true,"identifier":"https://edg.epa.gov/WAFer_harvest/ISO/frs-internet_FRS_ER_SIC_metadata.xml","keyword":["Alaska","Puerto Rico","United States","Washington DC","American Samoa","Virgin Islands","Facilities","Permits","Contaminant","Compliance","Regulatory","Cleanup","Environment","Air","ESF10","ESF3"],"last_harvested_date":"2026-09-04T19:22:50.036051","organization":{"aliases":["EPA"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"82b85475-f85d-404a-b95b-89d1a42e9f6b","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/epa.png","name":"U.S. Environmental Protection Agency","organization_type":"Federal Government","slug":"epa"},"parent_identifier":null,"popularity":7,"publisher":"U.S. Environmental Protection Agency, Headquarters","slug":"epa-facility-registry-service-frs-er_sic","spatial_centroid":{"lat":28.675746097999998,"lon":-62.894729278},"spatial_shape":{"coordinates":[[[-12.68151645,6.65223303],[-12.68151645,61.7110157],[-138.21454852,61.7110157],[-138.21454852,6.65223303],[-12.68151645,6.65223303]]],"type":"Polygon"},"theme":["geospatial"],"title":"EPA Facility Registry Service (FRS): ER_SIC","type":"dataset"},{"_score":28.238905,"_sort":[1788549767831,28.238905,9,"0a8915db-1790-4008-b019-072b2610e29a"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","contactPoint":{"@type":"vcard:Contact","fn":"U.S. Environmental Protection Agency, Office of Environmental Information, Office of Information Collection","hasEmail":"mailto:frs_support@epa.gov"},"describedByType":"application/octet-stream","description":"To improve public health and the environment, the United States Environmental Protection Agency (USEPA) collects information about facilities, sites, or places subject to environmental regulation or of environmental interest. These data are considered sensitive and are restricted to internal use only. The download file and map service are accessible only on the EPA intranet. EPA Category: Mission Sensitive, NARA Category: Critical Infrastructure.","distribution":[{"@type":"dcat:Distribution","describedByType":"application/octet-stream","downloadURL":"https://v18ovhrtay724.aa.ad.epa.gov/FRS/downloads/ESF10.gdb.zip","format":"ZIP","mediaType":"application/zip","title":"Zipped File Geodatabase (Accessible on the EPA Intranet only)"},{"@type":"dcat:Distribution","accessURL":"https://igeo.epa.gov/arcgis/rest/services/OEI/FRS_ESF10/MapServer","describedByType":"application/octet-stream","mediaType":"text/html","title":"ArcGIS Server Map Services (Accessible on the EPA Intranet only)"}],"identifier":"https://edg.epa.gov/WAFer_harvest/ISO/frs-internet_FRS_ER_NAICS_metadata.xml","isPartOf":"EPA Facility Registry Service Collection","issued":"2016-06-29T00:00:00.000+00:00","keyword":["Alaska","Puerto Rico","United States","Washington DC","American Samoa","Virgin Islands","Facilities","Permits","Contaminant","Compliance","Regulatory","Cleanup","Environment","Air","ESF10","ESF3"],"language":[],"license":"https://creativecommons.org/publicdomain/zero/1.0/","modified":"2016-06-29T00:00:00.000+00:00","publisher":{"@type":"org:Organization","name":"U.S. Environmental Protection Agency, Headquarters"},"spatial":"-12.68151645,6.65223303,-138.21454852,61.7110157","theme":["geospatial"],"title":"EPA Facility Registry Service (FRS): ER_NAICS"},"description":"To improve public health and the environment, the United States Environmental Protection Agency (USEPA) collects information about facilities, sites, or places subject to environmental regulation or of environmental interest. These data are considered sensitive and are restricted to internal use only. The download file and map service are accessible only on the EPA intranet. EPA Category: Mission Sensitive, NARA Category: Critical Infrastructure.","distribution_titles":["Zipped File Geodatabase (Accessible on the EPA Intranet only)","ArcGIS Server Map Services (Accessible on the EPA Intranet only)"],"harvest_record":"https://catalog.data.gov/harvest_record/9bac7ec4-2a51-4315-b91d-7724c7483027","harvest_record_raw":"https://catalog.data.gov/harvest_record/9bac7ec4-2a51-4315-b91d-7724c7483027/raw","harvest_record_transformed":"https://catalog.data.gov/harvest_record/9bac7ec4-2a51-4315-b91d-7724c7483027/transformed","has_download":true,"has_spatial":true,"identifier":"https://edg.epa.gov/WAFer_harvest/ISO/frs-internet_FRS_ER_NAICS_metadata.xml","keyword":["Alaska","Puerto Rico","United States","Washington DC","American Samoa","Virgin Islands","Facilities","Permits","Contaminant","Compliance","Regulatory","Cleanup","Environment","Air","ESF10","ESF3"],"last_harvested_date":"2026-09-04T19:22:47.831629","organization":{"aliases":["EPA"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"82b85475-f85d-404a-b95b-89d1a42e9f6b","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/epa.png","name":"U.S. Environmental Protection Agency","organization_type":"Federal Government","slug":"epa"},"parent_identifier":null,"popularity":9,"publisher":"U.S. Environmental Protection Agency, Headquarters","slug":"epa-facility-registry-service-frs-er_naics","spatial_centroid":{"lat":28.675746097999998,"lon":-62.894729278},"spatial_shape":{"coordinates":[[[-12.68151645,6.65223303],[-12.68151645,61.7110157],[-138.21454852,61.7110157],[-138.21454852,6.65223303],[-12.68151645,6.65223303]]],"type":"Polygon"},"theme":["geospatial"],"title":"EPA Facility Registry Service (FRS): ER_NAICS","type":"dataset"},{"_score":28.238905,"_sort":[1788549766337,28.238905,1,"58bdea70-d0f2-43e7-995c-6e8986ba9a9c"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","contactPoint":{"@type":"vcard:Contact","fn":"U.S. Environmental Protection Agency, Office of Environmental Information, Office of Information Collection","hasEmail":"mailto:frs_support@epa.gov"},"describedByType":"application/octet-stream","description":"To improve public health and the environment, the United States Environmental Protection Agency (USEPA) collects information about facilities, sites, or places subject to environmental regulation or of environmental interest. These data are considered sensitive and are restricted to internal use only. The download file and map service are accessible only on the EPA intranet. EPA Category: Mission Sensitive, NARA Category: Critical Infrastructure.","distribution":[{"@type":"dcat:Distribution","describedByType":"application/octet-stream","downloadURL":"https://v18ovhrtay724.aa.ad.epa.gov/FRS/downloads/ESF10.gdb.zip","format":"ZIP","mediaType":"application/zip","title":"Zipped File Geodatabase (Accessible on the EPA Intranet only)"},{"@type":"dcat:Distribution","accessURL":"https://igeo.epa.gov/arcgis/rest/services/OEI/FRS_ESF10/MapServer","describedByType":"application/octet-stream","mediaType":"text/html","title":"ArcGIS Server Map Services (Accessible on the EPA Intranet only)"}],"identifier":"https://edg.epa.gov/WAFer_harvest/ISO/frs-internet_FRS_ER_CONTACTS_metadata.xml","isPartOf":"EPA Facility Registry Service Collection","issued":"2016-06-29T00:00:00.000+00:00","keyword":["Alaska","Puerto Rico","United States","Washington DC","American Samoa","Virgin Islands","Facilities","Permits","Contaminant","Compliance","Regulatory","Cleanup","Environment","Air","ESF10","ESF3"],"language":[],"license":"https://creativecommons.org/publicdomain/zero/1.0/","modified":"2016-06-29T00:00:00.000+00:00","publisher":{"@type":"org:Organization","name":"U.S. Environmental Protection Agency, Headquarters"},"spatial":"-12.68151645,6.65223303,-138.21454852,61.7110157","theme":["geospatial"],"title":"EPA Facility Registry Service (FRS): ER_CONTACTS"},"description":"To improve public health and the environment, the United States Environmental Protection Agency (USEPA) collects information about facilities, sites, or places subject to environmental regulation or of environmental interest. These data are considered sensitive and are restricted to internal use only. The download file and map service are accessible only on the EPA intranet. EPA Category: Mission Sensitive, NARA Category: Critical Infrastructure.","distribution_titles":["Zipped File Geodatabase (Accessible on the EPA Intranet only)","ArcGIS Server Map Services (Accessible on the EPA Intranet only)"],"harvest_record":"https://catalog.data.gov/harvest_record/2e48b1c7-98a8-49cc-8f5c-e28dbf9152fd","harvest_record_raw":"https://catalog.data.gov/harvest_record/2e48b1c7-98a8-49cc-8f5c-e28dbf9152fd/raw","harvest_record_transformed":"https://catalog.data.gov/harvest_record/2e48b1c7-98a8-49cc-8f5c-e28dbf9152fd/transformed","has_download":true,"has_spatial":true,"identifier":"https://edg.epa.gov/WAFer_harvest/ISO/frs-internet_FRS_ER_CONTACTS_metadata.xml","keyword":["Alaska","Puerto Rico","United States","Washington DC","American Samoa","Virgin Islands","Facilities","Permits","Contaminant","Compliance","Regulatory","Cleanup","Environment","Air","ESF10","ESF3"],"last_harvested_date":"2026-09-04T19:22:46.337054","organization":{"aliases":["EPA"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"82b85475-f85d-404a-b95b-89d1a42e9f6b","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/epa.png","name":"U.S. Environmental Protection Agency","organization_type":"Federal Government","slug":"epa"},"parent_identifier":null,"popularity":1,"publisher":"U.S. Environmental Protection Agency, Headquarters","slug":"epa-facility-registry-service-frs-er_contacts","spatial_centroid":{"lat":28.675746097999998,"lon":-62.894729278},"spatial_shape":{"coordinates":[[[-12.68151645,6.65223303],[-12.68151645,61.7110157],[-138.21454852,61.7110157],[-138.21454852,6.65223303],[-12.68151645,6.65223303]]],"type":"Polygon"},"theme":["geospatial"],"title":"EPA Facility Registry Service (FRS): ER_CONTACTS","type":"dataset"},{"_score":28.142529,"_sort":[1788549765383,28.142529,4,"c1ff7bf1-4e8a-4d7e-bdf7-1bf3f0cfaf6a"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","contactPoint":{"@type":"vcard:Contact","fn":"U.S. Environmental Protection Agency, Office of Environmental Information, Office of Information Collection","hasEmail":"mailto:frs_support@epa.gov"},"describedByType":"application/octet-stream","description":"To improve public health and the environment, the United States Environmental Protection Agency (USEPA) collects information about facilities, sites, or places subject to environmental regulation or of environmental interest. These data are considered sensitive and are restricted to internal use only. The download file and map service are accessible only on the EPA intranet. EPA Category: Mission Sensitive, NARA Category: Critical Infrastructure.","distribution":[{"@type":"dcat:Distribution","describedByType":"application/octet-stream","downloadURL":"https://v18ovhrtay724.aa.ad.epa.gov/FRS/downloads/ESF10.gdb.zip","format":"ZIP","mediaType":"application/zip","title":"Zipped File Geodatabase (Accessible on the EPA Intranet only)"},{"@type":"dcat:Distribution","accessURL":"https://igeo.epa.gov/arcgis/rest/services/OEI/FRS_ESF10/MapServer","describedByType":"application/octet-stream","mediaType":"text/html","title":"ArcGIS Server Map Services (Accessible on the EPA Intranet only)"}],"identifier":"https://edg.epa.gov/WAFer_harvest/ISO/frs-internet_FRS_ER_CHEMICALS_metadata.xml","isPartOf":"EPA Facility Registry Service Collection","issued":"2016-06-29T00:00:00.000+00:00","keyword":["Alaska","Puerto Rico","United States","Washington DC","American Samoa","Virgin Islands","Facilities","Permits","Contaminant","Compliance","Regulatory","Cleanup","Environment","Air","ESF10","ESF3"],"language":[],"license":"https://creativecommons.org/publicdomain/zero/1.0/","modified":"2016-06-29T00:00:00.000+00:00","publisher":{"@type":"org:Organization","name":"U.S. Environmental Protection Agency, Headquarters"},"spatial":"-12.68151645,6.65223303,-138.21454852,61.7110157","theme":["geospatial"],"title":"EPA Facility Registry Service (FRS): ER_CHEMICALS"},"description":"To improve public health and the environment, the United States Environmental Protection Agency (USEPA) collects information about facilities, sites, or places subject to environmental regulation or of environmental interest. These data are considered sensitive and are restricted to internal use only. The download file and map service are accessible only on the EPA intranet. EPA Category: Mission Sensitive, NARA Category: Critical Infrastructure.","distribution_titles":["Zipped File Geodatabase (Accessible on the EPA Intranet only)","ArcGIS Server Map Services (Accessible on the EPA Intranet only)"],"harvest_record":"https://catalog.data.gov/harvest_record/a82416dc-ff87-4f49-a911-2e536853352c","harvest_record_raw":"https://catalog.data.gov/harvest_record/a82416dc-ff87-4f49-a911-2e536853352c/raw","harvest_record_transformed":"https://catalog.data.gov/harvest_record/a82416dc-ff87-4f49-a911-2e536853352c/transformed","has_download":true,"has_spatial":true,"identifier":"https://edg.epa.gov/WAFer_harvest/ISO/frs-internet_FRS_ER_CHEMICALS_metadata.xml","keyword":["Alaska","Puerto Rico","United States","Washington DC","American Samoa","Virgin Islands","Facilities","Permits","Contaminant","Compliance","Regulatory","Cleanup","Environment","Air","ESF10","ESF3"],"last_harvested_date":"2026-09-04T19:22:45.383305","organization":{"aliases":["EPA"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"82b85475-f85d-404a-b95b-89d1a42e9f6b","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/epa.png","name":"U.S. Environmental Protection Agency","organization_type":"Federal Government","slug":"epa"},"parent_identifier":null,"popularity":4,"publisher":"U.S. Environmental Protection Agency, Headquarters","slug":"epa-facility-registry-service-frs-er_chemicals","spatial_centroid":{"lat":28.675746097999998,"lon":-62.894729278},"spatial_shape":{"coordinates":[[[-12.68151645,6.65223303],[-12.68151645,61.7110157],[-138.21454852,61.7110157],[-138.21454852,6.65223303],[-12.68151645,6.65223303]]],"type":"Polygon"},"theme":["geospatial"],"title":"EPA Facility Registry Service (FRS): ER_CHEMICALS","type":"dataset"},{"_score":10.995798,"_sort":[1788549764426,10.995798,3,"e88e8188-68ac-4d78-a133-487bd3f20b90"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","accrualPeriodicity":"R/P1M","contactPoint":{"@type":"vcard:Contact","fn":"U.S. Environmental Protection Agency, Headquarters","hasEmail":"mailto:frs_support@epa.gov"},"describedByType":"application/octet-stream","description":"This web feature service contains location and facility identification information from EPA's Facility Registry System (FRS) for the subset of facilities that link to the Comprehensive Environmental Response, Compensation, and Liability Information System (CERCLIS) non-NPL sites. Superfund is a program administered by the EPA to locate, investigate, and clean up the worst hazardous waste sites throughout the United States. Before Superfund, Americans were less aware of how dumping chemical wastes might affect public health and the environment. Hazardous wastes were often left in the open, where they seeped into the ground, flowed into rivers and lakes, and contaminated soil and groundwater. Consequently, where these practices were intensive or continuous, there were uncontrolled or abandoned hazardous waste sites. These sites include abandoned warehouses, manufacturing facilities, processing plants, and landfills. Citizen concern about the extent of this problem prompted Congress in 1980 to establish the Superfund Program to eliminate the health and environmental threats posed by hazardous waste sites. EPA administers the Superfund program in cooperation with individual states and tribal governmentsFRS integrates facility data from EPA's national program systems, other federal agencies, and State and tribal master facility records and provides EPA with a centrally managed, single source of comprehensive and authoritative information on facilities. This data set contains the subset of FRS integrated facilities that link to CERCLIS non-NPL facilities once the CERCLIS data has been integrated into the FRS database. Additional information on FRS is available at the EPA website https://www.epa.gov/enviro/facility-registry-service-frs. These data are considered sensitive and are restricted to internal use only. The download file and map service are accessible only on the EPA intranet. EPA Category: Mission Sensitive, NARA Category: Critical Infrastructure.","distribution":[{"@type":"dcat:Distribution","describedByType":"application/octet-stream","downloadURL":"https://v18ovhrtay724.aa.ad.epa.gov/FRS/downloads/ESF10.gdb.zip","format":"ZIP","mediaType":"application/zip","title":"Zipped File Geodatabase (Accessible on the EPA Intranet only)"},{"@type":"dcat:Distribution","accessURL":"https://igeo.epa.gov/arcgis/rest/services/OEI/FRS_ESF10/MapServer","describedByType":"application/octet-stream","mediaType":"text/html","title":"ArcGIS Server Map Services (Accessible on the EPA Intranet only)"}],"identifier":"https://edg.epa.gov/WAFer_harvest/ISO/frs-internet_FRS_ER_CERCLIS_metadata.xml","isPartOf":"EPA Facility Registry Service Collection","issued":"2016-06-29T00:00:00.000+00:00","keyword":["Iowa","Pennsylvania","Hawaii","Arizona","Utah","Montana","North Carolina","Rhode Island","conterminous United States (CONUS)","North Dakota","California","New Jersey","Washington","Mississippi","Tennessee","Indiana","Oregon","Michigan","Washington DC","Colorado","Minnesota","Wisconsin","Texas","Missouri","Arkansas","Nevada","Massachusetts","Virgin Islands","Oklahoma","Ohio","Maine","New Hampshire","Kansas","Louisiana","New Mexico","American Samoa","Idaho","Alaska","Illinois","Florida","Alabama","Maryland","Puerto Rico","South Carolina","Nebraska","Virginia","New York","Kentucky","Connecticut","United States (US) (USA)","Wyoming","West Virginia","South Dakota","District of Columbia","Delaware","Vermont","Georgia","020:072","Facilities","Remediation","Toxics","Regulatory","Emergency Response","Sites","Contaminant","Cleanup","Resources","Environmental Management","Compliance","Waste"],"language":[],"license":"https://creativecommons.org/publicdomain/zero/1.0/","modified":"2016-06-29T00:00:00.000+00:00","publisher":{"@type":"org:Organization","name":"U.S. EPA Office of Environmental Information (OEI)"},"temporal":"2020-12-12T00:00:00+00:00/2020-12-12T00:00:00+00:00","theme":["geospatial"],"title":"EPA Facility Registry Service (FRS): ER_CERCLIS"},"description":"This web feature service contains location and facility identification information from EPA's Facility Registry System (FRS) for the subset of facilities that link to the Comprehensive Environmental Response, Compensation, and Liability Information System (CERCLIS) non-NPL sites. Superfund is a program administered by the EPA to locate, investigate, and clean up the worst hazardous waste sites throughout the United States. Before Superfund, Americans were less aware of how dumping chemical wastes might affect public health and the environment. Hazardous wastes were often left in the open, where they seeped into the ground, flowed into rivers and lakes, and contaminated soil and groundwater. Consequently, where these practices were intensive or continuous, there were uncontrolled or abandoned hazardous waste sites. These sites include abandoned warehouses, manufacturing facilities, processing plants, and landfills. Citizen concern about the extent of this problem prompted Congress in 1980 to establish the Superfund Program to eliminate the health and environmental threats posed by hazardous waste sites. EPA administers the Superfund program in cooperation with individual states and tribal governmentsFRS integrates facility data from EPA's national program systems, other federal agencies, and State and tribal master facility records and provides EPA with a centrally managed, single source of comprehensive and authoritative information on facilities. This data set contains the subset of FRS integrated facilities that link to CERCLIS non-NPL facilities once the CERCLIS data has been integrated into the FRS database. Additional information on FRS is available at the EPA website https://www.epa.gov/enviro/facility-registry-service-frs. These data are considered sensitive and are restricted to internal use only. The download file and map service are accessible only on the EPA intranet. EPA Category: Mission Sensitive, NARA Category: Critical Infrastructure.","distribution_titles":["Zipped File Geodatabase (Accessible on the EPA Intranet only)","ArcGIS Server Map Services (Accessible on the EPA Intranet only)"],"harvest_record":"https://catalog.data.gov/harvest_record/193fe635-d31a-4c03-99ea-7d0bcf61f177","harvest_record_raw":"https://catalog.data.gov/harvest_record/193fe635-d31a-4c03-99ea-7d0bcf61f177/raw","harvest_record_transformed":"https://catalog.data.gov/harvest_record/193fe635-d31a-4c03-99ea-7d0bcf61f177/transformed","has_download":true,"has_spatial":true,"identifier":"https://edg.epa.gov/WAFer_harvest/ISO/frs-internet_FRS_ER_CERCLIS_metadata.xml","keyword":["Iowa","Pennsylvania","Hawaii","Arizona","Utah","Montana","North Carolina","Rhode Island","conterminous United States (CONUS)","North Dakota","California","New Jersey","Washington","Mississippi","Tennessee","Indiana","Oregon","Michigan","Washington DC","Colorado","Minnesota","Wisconsin","Texas","Missouri","Arkansas","Nevada","Massachusetts","Virgin Islands","Oklahoma","Ohio","Maine","New Hampshire","Kansas","Louisiana","New Mexico","American Samoa","Idaho","Alaska","Illinois","Florida","Alabama","Maryland","Puerto Rico","South Carolina","Nebraska","Virginia","New York","Kentucky","Connecticut","United States (US) (USA)","Wyoming","West Virginia","South Dakota","District of Columbia","Delaware","Vermont","Georgia","020:072","Facilities","Remediation","Toxics","Regulatory","Emergency Response","Sites","Contaminant","Cleanup","Resources","Environmental Management","Compliance","Waste"],"last_harvested_date":"2026-09-04T19:22:44.426588","organization":{"aliases":["EPA"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"82b85475-f85d-404a-b95b-89d1a42e9f6b","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/epa.png","name":"U.S. Environmental Protection Agency","organization_type":"Federal Government","slug":"epa"},"parent_identifier":null,"popularity":3,"publisher":"U.S. EPA Office of Environmental Information (OEI)","slug":"epa-facility-registry-service-frs-er_cerclis","spatial_centroid":null,"spatial_shape":null,"theme":["geospatial"],"title":"EPA Facility Registry Service (FRS): ER_CERCLIS","type":"dataset"},{"_score":8.741451,"_sort":[1788549279268,8.741451,1,"593a12b1-f5e6-4f2c-af88-235498fbd7c8"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Seth M. Munson","hasEmail":"mailto:smunson@usgs.gov"},"description":"This dataset includes the cover of three vegetation types: perennial grasses, creosote bush (Larrea tridentata), and leguminous trees (Prosopis velutina, Parkinsonia microphylla, Parkinsonia florida) in 1989, 1995, 1999, 2005, and 2009 across southern Arizona. Cover was determined using sub-pixel classifications of two Landsat scenes from path 36, row 38 (centered on latitude: 31.7470, longitude: -111.3981) and path 37, row 38 (31.7470, -112.9431) that encompass Tucson, AZ.","distribution":[{"@type":"dcat:Distribution","accessURL":"http://doi.org/10.5066/F7959FNF","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.d369daae-76ad-4e64-8dd2-fbc980696a1d.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_d369daae-76ad-4e64-8dd2-fbc980696a1d","keyword":["Sonoran Desert; southern Arizona","USGS:d369daae-76ad-4e64-8dd2-fbc980696a1d","aridity","biota","climate change","desert","environment","geospatial datasets","land degradation","remote sensing","shrub encroachment","southern Arizona"],"modified":"2026-09-02T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-113.8600, 31.3375, -110.4700, 32.3930","theme":["geospatial"],"title":"Shifts in Perennial grass in southern Arizona, 1989 - 2009"},"description":"This dataset includes the cover of three vegetation types: perennial grasses, creosote bush (Larrea tridentata), and leguminous trees (Prosopis velutina, Parkinsonia microphylla, Parkinsonia florida) in 1989, 1995, 1999, 2005, and 2009 across southern Arizona. Cover was determined using sub-pixel classifications of two Landsat scenes from path 36, row 38 (centered on latitude: 31.7470, longitude: -111.3981) and path 37, row 38 (31.7470, -112.9431) that encompass Tucson, AZ.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/1c2a3672-6875-4f4d-9bff-7743215057e4","harvest_record_raw":"https://catalog.data.gov/harvest_record/1c2a3672-6875-4f4d-9bff-7743215057e4/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_d369daae-76ad-4e64-8dd2-fbc980696a1d","keyword":["Sonoran Desert; southern Arizona","USGS:d369daae-76ad-4e64-8dd2-fbc980696a1d","aridity","biota","climate change","desert","environment","geospatial datasets","land degradation","remote sensing","shrub encroachment","southern Arizona"],"last_harvested_date":"2026-09-04T19:14:39.268728","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":1,"publisher":"U.S. Geological Survey","slug":"shifts-in-perennial-grass-in-southern-arizona-1989-2009","spatial_centroid":{"lat":31.7597,"lon":-112.50399999999999},"spatial_shape":{"coordinates":[[[-113.86,31.3375],[-113.86,32.393],[-110.47,32.393],[-110.47,31.3375],[-113.86,31.3375]]],"type":"Polygon"},"theme":["geospatial"],"title":"Shifts in Perennial grass in southern Arizona, 1989 - 2009","type":"dataset"},{"_score":9.232977,"_sort":[1788549207447,9.232977,0,"042584aa-2b32-4040-9e57-f8f6d294728d"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Alexandra Lutz","hasEmail":"mailto:alexandra.lutz@dri.edu"},"description":"This collection contains GSFLOW and R-RHESSys model input and output files. CSC_model_files contains the baseline Cleve Creek model, T-only change model, and T-P change model. Model_results.rar is from R-RHESSYS model of climate projections of drought during the next 30 years (2016-2035) for the Cleve Creek watershed in Nevada.  Within the .rar packaging are .dat files that contain outputs including net primary productivity (NPP), leaf area index (LAI), actual evapotranspiration (AET), soil\nmoisture, groundwater level, streamflow, snow pack (as snow water equivalent, SWE). \nGeographic information:  Site is Cleve Creek, a headwaters basin to Spring Valley in\nEastern Nevada. Lower left corner of model grid is 701984 m (east) and 4342483 m\n(north) NAD 83 zone 11.  The grid is oriented North-South and extends 143 rows and\n115 columns with each cell 100 m by 100 m.  NAD83, zone 11N, datumD_North_American1983.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P14HLZC4","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.56feafa1e4b0328dcb7dec33.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_56feafa1e4b0328dcb7dec33","keyword":["Cleve Creek","Great Basin","Nevada","Spring Valley","USGS:56feafa1e4b0328dcb7dec33","climate change","environment","hydrologic response","modeling","pre-SM502.8","vegetation response"],"modified":"2026-09-02T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-114.6607, 39.2054, -114.5276, 39.3369","theme":["geospatial"],"title":"Linking climate, hydrology and ecological changes at intermediate timescales in Cleve Creek, Eastern Nevada"},"description":"This collection contains GSFLOW and R-RHESSys model input and output files. CSC_model_files contains the baseline Cleve Creek model, T-only change model, and T-P change model. Model_results.rar is from R-RHESSYS model of climate projections of drought during the next 30 years (2016-2035) for the Cleve Creek watershed in Nevada.  Within the .rar packaging are .dat files that contain outputs including net primary productivity (NPP), leaf area index (LAI), actual evapotranspiration (AET), soil\nmoisture, groundwater level, streamflow, snow pack (as snow water equivalent, SWE). \nGeographic information:  Site is Cleve Creek, a headwaters basin to Spring Valley in\nEastern Nevada. Lower left corner of model grid is 701984 m (east) and 4342483 m\n(north) NAD 83 zone 11.  The grid is oriented North-South and extends 143 rows and\n115 columns with each cell 100 m by 100 m.  NAD83, zone 11N, datumD_North_American1983.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/ac06a926-51cd-4387-8007-412d10516645","harvest_record_raw":"https://catalog.data.gov/harvest_record/ac06a926-51cd-4387-8007-412d10516645/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_56feafa1e4b0328dcb7dec33","keyword":["Cleve Creek","Great Basin","Nevada","Spring Valley","USGS:56feafa1e4b0328dcb7dec33","climate change","environment","hydrologic response","modeling","pre-SM502.8","vegetation response"],"last_harvested_date":"2026-09-04T19:13:27.447811","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":0,"publisher":"U.S. Geological Survey","slug":"linking-climate-hydrology-and-ecological-changes-at-intermediate-timescales-in-cleve-creek","spatial_centroid":{"lat":39.257999999999996,"lon":-114.60746000000002},"spatial_shape":{"coordinates":[[[-114.6607,39.2054],[-114.6607,39.3369],[-114.5276,39.3369],[-114.5276,39.2054],[-114.6607,39.2054]]],"type":"Polygon"},"theme":["geospatial"],"title":"Linking climate, hydrology and ecological changes at intermediate timescales in Cleve Creek, Eastern Nevada","type":"dataset"},{"_score":9.752213,"_sort":[1788549187748,9.752213,7,"660a3934-2fd0-455f-923d-6abaf1b5ab2d"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Adam J Terando","hasEmail":"mailto:aterando@usgs.gov"},"description":"We compiled and analyzed a database of burn permits for prescribed fires conducted in Florida and Georgia from 2006-2016. The dataset contains the number of permitted burns and expected acres burned by county in the two states for every day in the 11 year period. Also included are the county-wide average daily weather conditions for temperature and relative humidity, calculated from the University of Idaho gridMet dataset.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P9YNSQZ2","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.5cfc103fe4b0312686a7f64b.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_5cfc103fe4b0312686a7f64b","keyword":["Florida","Georgia","USGS:5cfc103fe4b0312686a7f64b","autumn","controlled fires","environment","fires","prescribed fire","seasons","spring","summer","winter"],"modified":"2026-09-02T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-87.6929, 25.0454, -79.8267, 35.0296","theme":["geospatial"],"title":"Prescribed Fire Permit Records for Georgia and Florida"},"description":"We compiled and analyzed a database of burn permits for prescribed fires conducted in Florida and Georgia from 2006-2016. The dataset contains the number of permitted burns and expected acres burned by county in the two states for every day in the 11 year period. Also included are the county-wide average daily weather conditions for temperature and relative humidity, calculated from the University of Idaho gridMet dataset.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/9b61426c-17c9-45db-9eff-3f5806b76880","harvest_record_raw":"https://catalog.data.gov/harvest_record/9b61426c-17c9-45db-9eff-3f5806b76880/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_5cfc103fe4b0312686a7f64b","keyword":["Florida","Georgia","USGS:5cfc103fe4b0312686a7f64b","autumn","controlled fires","environment","fires","prescribed fire","seasons","spring","summer","winter"],"last_harvested_date":"2026-09-04T19:13:07.748212","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":7,"publisher":"U.S. Geological Survey","slug":"prescribed-fire-permit-records-for-georgia-and-florida","spatial_centroid":{"lat":29.039080000000002,"lon":-84.54642},"spatial_shape":{"coordinates":[[[-87.6929,25.0454],[-87.6929,35.0296],[-79.8267,35.0296],[-79.8267,25.0454],[-87.6929,25.0454]]],"type":"Polygon"},"theme":["geospatial"],"title":"Prescribed Fire Permit Records for Georgia and Florida","type":"dataset"},{"_score":6.7382774,"_sort":[1788549090676,6.7382774,0,"fabcb2e8-d955-434a-b866-c01c4ed89df4"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Climate Adaptation Science Centers","hasEmail":"mailto:casc-data@usgs.gov"},"description":"Snow and meteorological observations were collected over a range of water years (WY) by three research institutions and by citizen scientists to characterize forest effects on snow processes across the Pacific Northwest, USA. Fourteen total study sites cover the western slopes and crest of the Cascade Range in WA and OR, and central and northern ID. Each study location includes one or more paired forest and open area in which to compare snow observations. A range of forest canopy densities and data collection strategies are represented, including paired manual snow courses, snow pits, automated sensors, and time-lapse images of snow measurement poles. Analysis and synthesis of all of these sites are presented in the data citation. Location attributes are provided as metadata for each site.","distribution":[{"@type":"dcat:Distribution","accessURL":"http://doi.org/10.5066/F70C4SW3","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.cc7bb369-0031-4f6f-976f-6c2907030070.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_cc7bb369-0031-4f6f-976f-6c2907030070","keyword":["Cle Elum","Idaho","Kittatas County","McCall","McKenzie River","Mica Creek","Middle Fork Willamette","Olallie Meadows","Oregon","Ponderosa State Park","USGS:cc7bb369-0031-4f6f-976f-6c2907030070","Valley County","Washington","citizen science","environment","external research support","field inventory and monitoring","forest canopy density","meteorological observations","precipitation (atmospheric)","snow and ice cover","snow depth","snow observations","time-lapse photography"],"modified":"2026-09-02T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-122.3297, 43.6122, -115.5512, 47.5098","theme":["geospatial"],"title":"Observations of snow depth and meteorological variables in forests and nearby open areas at field sites in Washington, Oregon, and Idaho, USA"},"description":"Snow and meteorological observations were collected over a range of water years (WY) by three research institutions and by citizen scientists to characterize forest effects on snow processes across the Pacific Northwest, USA. Fourteen total study sites cover the western slopes and crest of the Cascade Range in WA and OR, and central and northern ID. Each study location includes one or more paired forest and open area in which to compare snow observations. A range of forest canopy densities and data collection strategies are represented, including paired manual snow courses, snow pits, automated sensors, and time-lapse images of snow measurement poles. Analysis and synthesis of all of these sites are presented in the data citation. Location attributes are provided as metadata for each site.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/c06f894f-3fce-4662-bfa1-1efa486ebbab","harvest_record_raw":"https://catalog.data.gov/harvest_record/c06f894f-3fce-4662-bfa1-1efa486ebbab/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_cc7bb369-0031-4f6f-976f-6c2907030070","keyword":["Cle Elum","Idaho","Kittatas County","McCall","McKenzie River","Mica Creek","Middle Fork Willamette","Olallie Meadows","Oregon","Ponderosa State Park","USGS:cc7bb369-0031-4f6f-976f-6c2907030070","Valley County","Washington","citizen science","environment","external research support","field inventory and monitoring","forest canopy density","meteorological observations","precipitation (atmospheric)","snow and ice cover","snow depth","snow observations","time-lapse photography"],"last_harvested_date":"2026-09-04T19:11:30.676685","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":0,"publisher":"U.S. Geological Survey","slug":"observations-of-snow-depth-and-meteorological-variables-in-forests-and-nearby-open-areas-a","spatial_centroid":{"lat":45.17124,"lon":-119.6183},"spatial_shape":{"coordinates":[[[-122.3297,43.6122],[-122.3297,47.5098],[-115.5512,47.5098],[-115.5512,43.6122],[-122.3297,43.6122]]],"type":"Polygon"},"theme":["geospatial"],"title":"Observations of snow depth and meteorological variables in forests and nearby open areas at field sites in Washington, Oregon, and Idaho, USA","type":"dataset"},{"_score":8.853937,"_sort":[1788548962618,8.853937,2,"33810f91-e44a-4b95-a564-9fb888bc7e24"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Anteneh A. Sarbanes","hasEmail":"mailto:asarbanes@usgs.gov"},"description":"Dynamic Surface Water Extent (DSWE) Annual Proportions data summarize occurrence of water on the land surface. DSWE Annual Proportions data are statistical summaries of the USGS Landsat Collection 2 Level-3 DSWE data product (C2-DSWE), \na raster dataset of per-pixel surface water inundation status based on the analysis of Landsat 4-9 satellite imagery. DSWE Annual Proportions data average occurrence of surface water extent over yearly time periods across the conterminous US in \nthe form of GeoTIFF rasters with 30m spatial resolution. DSWE Annual Proportions raster pixel values represent the portion of cloud, cloud shadow, and snow free Landsat observations that are classified as surface water inundation in C2-DSWE \nInterpreted with all Mask ('INWAM') layer. Each DSWE Annual Proportions GeoTIFF contains 5 raster bands: 3 corresponding to DSWE surface water classes (i.e., open, partial, and non-water); 1 representing total surface water (partial and open values combined); \nand 1 providing a per pixel count of valid DSWE input values. DSWE Annual Proportions data are processed and archived to the continental US Analysis Ready Data (ARD) tile scheme: https://landsat.usgs.gov/ard_tile.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P16Q2FUD","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.66da33ced34eef5af66d5548.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_66da33ced34eef5af66d5548","keyword":["CONUS","Conterminous United States","DSWE","DSWE Proportions","Drought","Flooding","Hydrology","Inundation","Lakes","Rivers","Surface water","USGS:66da33ced34eef5af66d5548","Water Resources","Wetlands","climatologyMeteorologyAtmosphere","environment","inlandWaters"],"modified":"2026-09-02T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-124.7330, 24.5150, -66.9500, 49.3840","theme":["geospatial"],"title":"Collection 2 Dynamic Surface Water Extent (DSWE) Proportions: CONUS Annual Proportions 1984-Present (ver. 2.0, August 2026)"},"description":"Dynamic Surface Water Extent (DSWE) Annual Proportions data summarize occurrence of water on the land surface. DSWE Annual Proportions data are statistical summaries of the USGS Landsat Collection 2 Level-3 DSWE data product (C2-DSWE), \na raster dataset of per-pixel surface water inundation status based on the analysis of Landsat 4-9 satellite imagery. DSWE Annual Proportions data average occurrence of surface water extent over yearly time periods across the conterminous US in \nthe form of GeoTIFF rasters with 30m spatial resolution. DSWE Annual Proportions raster pixel values represent the portion of cloud, cloud shadow, and snow free Landsat observations that are classified as surface water inundation in C2-DSWE \nInterpreted with all Mask ('INWAM') layer. Each DSWE Annual Proportions GeoTIFF contains 5 raster bands: 3 corresponding to DSWE surface water classes (i.e., open, partial, and non-water); 1 representing total surface water (partial and open values combined); \nand 1 providing a per pixel count of valid DSWE input values. DSWE Annual Proportions data are processed and archived to the continental US Analysis Ready Data (ARD) tile scheme: https://landsat.usgs.gov/ard_tile.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/576422b4-7a36-451a-8f59-07a82982a651","harvest_record_raw":"https://catalog.data.gov/harvest_record/576422b4-7a36-451a-8f59-07a82982a651/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_66da33ced34eef5af66d5548","keyword":["CONUS","Conterminous United States","DSWE","DSWE Proportions","Drought","Flooding","Hydrology","Inundation","Lakes","Rivers","Surface water","USGS:66da33ced34eef5af66d5548","Water Resources","Wetlands","climatologyMeteorologyAtmosphere","environment","inlandWaters"],"last_harvested_date":"2026-09-04T19:09:22.618234","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":2,"publisher":"U.S. Geological Survey","slug":"collection-2-dynamic-surface-water-extent-dswe-proportions-conus-annual-proportions-1984-p","spatial_centroid":{"lat":34.462599999999995,"lon":-101.61980000000001},"spatial_shape":{"coordinates":[[[-124.733,24.515],[-124.733,49.384],[-66.95,49.384],[-66.95,24.515],[-124.733,24.515]]],"type":"Polygon"},"theme":["geospatial"],"title":"Collection 2 Dynamic Surface Water Extent (DSWE) Proportions: CONUS Annual Proportions 1984-Present (ver. 2.0, August 2026)","type":"dataset"},{"_score":10.658567,"_sort":[1788548960037,10.658567,0,"4695e730-ca8c-4cde-9624-cf436b4c0d41"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Brandon J Sansom","hasEmail":"mailto:bsansom@usgs.gov"},"description":"This dataset contains the time- and space-averaged velocity data collected to characterize the hydraulics of the paddlewheel propulsion system of the U.S. Geological Survey (USGS), Columbia Environmental Research Center (CERC) eco-flume, a continuous loop, racetrack style flume. Four cross sections were established at 1, 2, 3, and 4 meters downstream from the paddlewheel footprint in each straight section of the eco-flume. At each cross section, three-component water velocity was measured using an Acoustic Doppler Velocimeter at a total of 80 point-locations in the cross section (8 locations in the transverse direction and 10 locations in the vertical direction). Velocity measurements were made at each point for a total of 120 seconds. Velocity measurements were time- and space-averaged using user-defined codes to examine the characteristic hydraulic properties at each cross section. Enclosed data files include: 1) Time_Space_Average_ADVdata.csv that describes the time- and space-averaged (spatially averaged across the transverse direction) ADV data at measurement each cross section,  2) EastChannel_0.1TV_4m_Contour.csv that describes an example of time-averaged ADV data within a single cross section in the east channel of the eco-flume at a target mean velocity of 0.1 meters per second, and 3) FlowSimilarity.csv that describes the flow similarity and uniformity of the paddlewheel propulsion system.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P14HCGDQ","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.6a970ae11ba49b45440e9d1d.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_6a970ae11ba49b45440e9d1d","keyword":["USGS:6a970ae11ba49b45440e9d1d","environment","hydraulic engineering","water resources"],"modified":"2026-09-02T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-92.284312, 38.910784, -92.274450, 38.912612","theme":["geospatial"],"title":"Hydraulic characterization of the paddlewheel propulsion system of the U.S. Geological Survey, Columbia Environmental Research Center eco-flume"},"description":"This dataset contains the time- and space-averaged velocity data collected to characterize the hydraulics of the paddlewheel propulsion system of the U.S. Geological Survey (USGS), Columbia Environmental Research Center (CERC) eco-flume, a continuous loop, racetrack style flume. Four cross sections were established at 1, 2, 3, and 4 meters downstream from the paddlewheel footprint in each straight section of the eco-flume. At each cross section, three-component water velocity was measured using an Acoustic Doppler Velocimeter at a total of 80 point-locations in the cross section (8 locations in the transverse direction and 10 locations in the vertical direction). Velocity measurements were made at each point for a total of 120 seconds. Velocity measurements were time- and space-averaged using user-defined codes to examine the characteristic hydraulic properties at each cross section. Enclosed data files include: 1) Time_Space_Average_ADVdata.csv that describes the time- and space-averaged (spatially averaged across the transverse direction) ADV data at measurement each cross section,  2) EastChannel_0.1TV_4m_Contour.csv that describes an example of time-averaged ADV data within a single cross section in the east channel of the eco-flume at a target mean velocity of 0.1 meters per second, and 3) FlowSimilarity.csv that describes the flow similarity and uniformity of the paddlewheel propulsion system.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/4c679769-7763-490f-9504-783d6b887977","harvest_record_raw":"https://catalog.data.gov/harvest_record/4c679769-7763-490f-9504-783d6b887977/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_6a970ae11ba49b45440e9d1d","keyword":["USGS:6a970ae11ba49b45440e9d1d","environment","hydraulic engineering","water resources"],"last_harvested_date":"2026-09-04T19:09:20.037077","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":0,"publisher":"U.S. Geological Survey","slug":"hydraulic-characterization-of-the-paddlewheel-propulsion-system-of-the-u-s-geological-surv","spatial_centroid":{"lat":38.911515200000004,"lon":-92.2803672},"spatial_shape":{"coordinates":[[[-92.284312,38.910784],[-92.284312,38.912612],[-92.27445,38.912612],[-92.27445,38.910784],[-92.284312,38.910784]]],"type":"Polygon"},"theme":["geospatial"],"title":"Hydraulic characterization of the paddlewheel propulsion system of the U.S. Geological Survey, Columbia Environmental Research Center eco-flume","type":"dataset"},{"_score":10.530857,"_sort":[1788548671946,10.530857,0,"7ddb4d13-53ff-46a9-a542-59d0f89e861d"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Brandon J Sansom","hasEmail":"mailto:bsansom@usgs.gov"},"description":"This project contains design parameters and an overview of the hydraulic characterization of the U.S. Geological Survey (USGS), Columbia Environmental Research Center (CERC) eco-flume. The eco-flume was designed in collaboration with the St. Anthony Falls Laboratory at the University of Minnesota to explore complex ecological phenomena that occur in natural rivers. The overall design was intended to provide experimental flexibility to include a wide range of hydraulic and water-quality variables to support investigation of a variety of transport and ecological phenomena in flowing environments. Datasets provided here describe the hydraulic characterization throughout the eco-flume of both the paddlewheel and jet pump propulsion systems. These data only represent baseline conditions for the eco-flume. Specific hydraulics will vary with experimental setup and needs, and therefore should be detailed accordingly across future studies.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P14HCGDQ","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.6a9702fe1ba49b45440e9bbb.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_6a9702fe1ba49b45440e9bbb","keyword":["USGS:6a9702fe1ba49b45440e9bbb","aquatic biology","biota","environment","hydrology","water resources"],"modified":"2026-09-02T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-92.284312, 38.910784, -92.274450, 38.912612","theme":["geospatial"],"title":"Supporting files to describe the design and parameterization of the U.S. Geological Survey, Columbia Environmental Research Center eco-flume"},"description":"This project contains design parameters and an overview of the hydraulic characterization of the U.S. Geological Survey (USGS), Columbia Environmental Research Center (CERC) eco-flume. The eco-flume was designed in collaboration with the St. Anthony Falls Laboratory at the University of Minnesota to explore complex ecological phenomena that occur in natural rivers. The overall design was intended to provide experimental flexibility to include a wide range of hydraulic and water-quality variables to support investigation of a variety of transport and ecological phenomena in flowing environments. Datasets provided here describe the hydraulic characterization throughout the eco-flume of both the paddlewheel and jet pump propulsion systems. These data only represent baseline conditions for the eco-flume. Specific hydraulics will vary with experimental setup and needs, and therefore should be detailed accordingly across future studies.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/e91141e7-3ed4-44e7-9a9c-63fe73a9c102","harvest_record_raw":"https://catalog.data.gov/harvest_record/e91141e7-3ed4-44e7-9a9c-63fe73a9c102/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_6a9702fe1ba49b45440e9bbb","keyword":["USGS:6a9702fe1ba49b45440e9bbb","aquatic biology","biota","environment","hydrology","water resources"],"last_harvested_date":"2026-09-04T19:04:31.946812","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":0,"publisher":"U.S. Geological Survey","slug":"supporting-files-to-describe-the-design-and-parameterization-of-the-u-s-geological-survey-","spatial_centroid":{"lat":38.911515200000004,"lon":-92.2803672},"spatial_shape":{"coordinates":[[[-92.284312,38.910784],[-92.284312,38.912612],[-92.27445,38.912612],[-92.27445,38.910784],[-92.284312,38.910784]]],"type":"Polygon"},"theme":["geospatial"],"title":"Supporting files to describe the design and parameterization of the U.S. Geological Survey, Columbia Environmental Research Center eco-flume","type":"dataset"},{"_score":9.444901,"_sort":[1788548208142,9.444901,2,"5ed45c4d-edef-45dd-9c5c-05fe1c52fed0"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Matt Germino","hasEmail":"mailto:mgermino@usgs.gov"},"description":"To test experimental warming effects, we used and enhanced the Snake River Plain (SRP) Warming Experiment. At Birds of Prey National Conservation Area (BOP NCA), a warming frame and control plot pair were established at five locations along a 4 km distance at 3000\u2019 ASL on loam soils with a mosaic of cheatgrass ( Bromus tectorum), Sandberg\u2019s bluegrass ( Poa secunda), and biotic soil crusts. This area is relatively disturbed that has high abundances of exotic annual grasses or naturalized restoration grasses. Plot sizes were 2.4 x 2.4 m and were installed in fall 2012. At 4800\u2019ASL on rocky loam soils in Hollister, five frames were arrayed with paired control plots across a 2 km transect at 4900\u2019 ASL in a Wyoming Big Sagebrush and squirreltail ( Elymus elymoides) and P. secunda community, starting in fall 2010 using 2.4 x 1.2 m frames. At Grand Teton National Park (GTNP) on cobbly alluvium soils in the Pilgrim Creek basin, we established 3 control and 3 warmed frames in a ~ acre area having low (little) sagebrush ( A. arbuscula ssp. thermopola) and a high abundance of native forbs and scarce grasses such arrowleaf ( Balsamorhiza) and buckwheat ( Eriogonum), in May 2010. The Teton site is pristine and was not fenced, but all other sites had 1.5 m tall barbed wire fences to exclude livestock and the BOP sites additionally had chicken wire fencing to exclude small mammals. Frames were removed just prior to and just following permanent winter snowpack accumulation at GTNP (only).","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P14FNDCN","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.a341e9e1-114c-4387-8d33-ac1396eb7823.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_a341e9e1-114c-4387-8d33-ac1396eb7823","keyword":["Big wyoming sagebrush","Great Basin","Idaho","Pacific Northwest","USGS:a341e9e1-114c-4387-8d33-ac1396eb7823","climate change","environment","sagebrush"],"modified":"2026-09-02T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-116.9698, 42.3265, -110.3676, 44.0554","theme":["geospatial"],"title":"Snake River Plain (SRP) Warming Experiment Data"},"description":"To test experimental warming effects, we used and enhanced the Snake River Plain (SRP) Warming Experiment. At Birds of Prey National Conservation Area (BOP NCA), a warming frame and control plot pair were established at five locations along a 4 km distance at 3000\u2019 ASL on loam soils with a mosaic of cheatgrass ( Bromus tectorum), Sandberg\u2019s bluegrass ( Poa secunda), and biotic soil crusts. This area is relatively disturbed that has high abundances of exotic annual grasses or naturalized restoration grasses. Plot sizes were 2.4 x 2.4 m and were installed in fall 2012. At 4800\u2019ASL on rocky loam soils in Hollister, five frames were arrayed with paired control plots across a 2 km transect at 4900\u2019 ASL in a Wyoming Big Sagebrush and squirreltail ( Elymus elymoides) and P. secunda community, starting in fall 2010 using 2.4 x 1.2 m frames. At Grand Teton National Park (GTNP) on cobbly alluvium soils in the Pilgrim Creek basin, we established 3 control and 3 warmed frames in a ~ acre area having low (little) sagebrush ( A. arbuscula ssp. thermopola) and a high abundance of native forbs and scarce grasses such arrowleaf ( Balsamorhiza) and buckwheat ( Eriogonum), in May 2010. The Teton site is pristine and was not fenced, but all other sites had 1.5 m tall barbed wire fences to exclude livestock and the BOP sites additionally had chicken wire fencing to exclude small mammals. Frames were removed just prior to and just following permanent winter snowpack accumulation at GTNP (only).","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/94ffd017-61ff-4974-a38b-255ae0acba21","harvest_record_raw":"https://catalog.data.gov/harvest_record/94ffd017-61ff-4974-a38b-255ae0acba21/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_a341e9e1-114c-4387-8d33-ac1396eb7823","keyword":["Big wyoming sagebrush","Great Basin","Idaho","Pacific Northwest","USGS:a341e9e1-114c-4387-8d33-ac1396eb7823","climate change","environment","sagebrush"],"last_harvested_date":"2026-09-04T18:56:48.142974","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":2,"publisher":"U.S. Geological Survey","slug":"snake-river-plain-srp-warming-experiment-data","spatial_centroid":{"lat":43.018060000000006,"lon":-114.32892},"spatial_shape":{"coordinates":[[[-116.9698,42.3265],[-116.9698,44.0554],[-110.3676,44.0554],[-110.3676,42.3265],[-116.9698,42.3265]]],"type":"Polygon"},"theme":["geospatial"],"title":"Snake River Plain (SRP) Warming Experiment Data","type":"dataset"},{"_score":9.059682,"_sort":[1788547625753,9.059682,0,"bdbb8404-e880-4961-bd21-34bdf8530311"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Climate Adaptation Science Centers","hasEmail":"mailto:casc-data@usgs.gov"},"description":"We established a Landsat-derived geospatial database of unburned islands within 2,298 fires across the Inland Northwestern US (including eastern Washington, eastern Oregon, and Idaho) from 1984-2014.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P13KEHM7","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.9af64af3-6a0d-40b9-9614-92f8e393be31.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_9af64af3-6a0d-40b9-9614-92f8e393be31","keyword":["Idaho","Oregon","USGS:9af64af3-6a0d-40b9-9614-92f8e393be31","Washington","ecology","environment","fires","geoscientificInformation","geospatial datasets","image collections","multispectral imaging","refugia","remote sensing"],"modified":"2026-09-02T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-122.8099, 41.8432, -110.2889, 49.0484","theme":["geospatial"],"title":"Unburned areas within fire perimeters across the Inland Northwestern USA from 1984 to 2014"},"description":"We established a Landsat-derived geospatial database of unburned islands within 2,298 fires across the Inland Northwestern US (including eastern Washington, eastern Oregon, and Idaho) from 1984-2014.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/52e40f48-2c17-4ba5-a42d-a25f65e6a965","harvest_record_raw":"https://catalog.data.gov/harvest_record/52e40f48-2c17-4ba5-a42d-a25f65e6a965/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_9af64af3-6a0d-40b9-9614-92f8e393be31","keyword":["Idaho","Oregon","USGS:9af64af3-6a0d-40b9-9614-92f8e393be31","Washington","ecology","environment","fires","geoscientificInformation","geospatial datasets","image collections","multispectral imaging","refugia","remote sensing"],"last_harvested_date":"2026-09-04T18:47:05.753902","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":0,"publisher":"U.S. Geological Survey","slug":"unburned-areas-within-fire-perimeters-across-the-inland-northwestern-usa-from-1984-to-2014","spatial_centroid":{"lat":44.725280000000005,"lon":-117.80149999999999},"spatial_shape":{"coordinates":[[[-122.8099,41.8432],[-122.8099,49.0484],[-110.2889,49.0484],[-110.2889,41.8432],[-122.8099,41.8432]]],"type":"Polygon"},"theme":["geospatial"],"title":"Unburned areas within fire perimeters across the Inland Northwestern USA from 1984 to 2014","type":"dataset"},{"_score":8.162897,"_sort":[1788547207507,8.162897,0,"1e40e492-9789-4a5c-b220-726527525906"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Josh Lawler","hasEmail":"mailto:jlawler@u.washington.edu"},"description":"These 1830 maps contain projected current and future change in habitat suitability for 366 species under the Third Generation Coupled Global Climate Model (CGCM 3.1) and Hadley Centre Coupled Model, version 3 (HADCM3). In support of the Pacific Northwest Climate Change Vulnerability Assessment (www.climatevulnerability.org), we developed a method to model habitat suitability in which we built correlative climate suitability models for 366 terrestrial animal species at a relatively coarse spatial resolution for the entire North American continent using species range maps and 23 bioclimatic variables. We then applied  the models to both current and projected future climate data downscaled to a moderately fine resolution for western North America. We refined the resulting climate suitability projections by applying a filter that limited suitability to areas in which suitable biomes were projected to be present. This map is part of a collection of projected current and future potential distributions of 366 terrestrial vertebrate species, including 12 amphibians, 237 birds, and 117 mammals, based on correlative bioclimatic models and projected changes in biomes.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P18VCFHG","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.6873f2e5-db10-4106-a6be-2c58b5da4190.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_6873f2e5-db10-4106-a6be-2c58b5da4190","keyword":["CGCM31","HADCM3","Hadley Centre Coupled Model","Third Generation Coupled Global Climate Model","USGS:6873f2e5-db10-4106-a6be-2c58b5da4190","biodiversity","climate change","environment","external research support","geospatial datasets","modeling","prediction","vulnerabilty assessment"],"modified":"2026-09-02T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-139.0458, 24.9472, -89.0375, 59.9556","theme":["geospatial"],"title":"Projected current future habitat suitability for 366 species using CGCM31 and HAD climate models (1961-2099)"},"description":"These 1830 maps contain projected current and future change in habitat suitability for 366 species under the Third Generation Coupled Global Climate Model (CGCM 3.1) and Hadley Centre Coupled Model, version 3 (HADCM3). In support of the Pacific Northwest Climate Change Vulnerability Assessment (www.climatevulnerability.org), we developed a method to model habitat suitability in which we built correlative climate suitability models for 366 terrestrial animal species at a relatively coarse spatial resolution for the entire North American continent using species range maps and 23 bioclimatic variables. We then applied  the models to both current and projected future climate data downscaled to a moderately fine resolution for western North America. We refined the resulting climate suitability projections by applying a filter that limited suitability to areas in which suitable biomes were projected to be present. This map is part of a collection of projected current and future potential distributions of 366 terrestrial vertebrate species, including 12 amphibians, 237 birds, and 117 mammals, based on correlative bioclimatic models and projected changes in biomes.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/4c77bf96-9a95-4887-8b5d-f270bafc16ab","harvest_record_raw":"https://catalog.data.gov/harvest_record/4c77bf96-9a95-4887-8b5d-f270bafc16ab/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_6873f2e5-db10-4106-a6be-2c58b5da4190","keyword":["CGCM31","HADCM3","Hadley Centre Coupled Model","Third Generation Coupled Global Climate Model","USGS:6873f2e5-db10-4106-a6be-2c58b5da4190","biodiversity","climate change","environment","external research support","geospatial datasets","modeling","prediction","vulnerabilty assessment"],"last_harvested_date":"2026-09-04T18:40:07.507539","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":0,"publisher":"U.S. Geological Survey","slug":"projected-current-future-habitat-suitability-for-366-species-using-cgcm31-and-ha-1961-2099","spatial_centroid":{"lat":38.950559999999996,"lon":-119.04248},"spatial_shape":{"coordinates":[[[-139.0458,24.9472],[-139.0458,59.9556],[-89.0375,59.9556],[-89.0375,24.9472],[-139.0458,24.9472]]],"type":"Polygon"},"theme":["geospatial"],"title":"Projected current future habitat suitability for 366 species using CGCM31 and HAD climate models (1961-2099)","type":"dataset"},{"_score":10.746274,"_sort":[1788546828331,10.746274,0,"97e94a14-637a-40dd-9069-8ffb64c9a4c5"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Brandon J Sansom","hasEmail":"mailto:bsansom@usgs.gov"},"description":"This dataset contains an example time series of mean water velocity in the U.S. Geological Survey (USGS), Columbia Environmental Research Center (CERC) eco-flume using the paddlewheel propulsion system. Mean water velocity was measured with an area velocity flow meter (AVFM) positioned approximately 6 meters downstream from the entrance to the east channel of the eco-flume. A velocity time series was measured for three target mean velocities (0.1, 0.2, and 0.3 meters per second), with measurements collected at 1 Hertz for a total of 90 minutes at each operating speed.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P14HCGDQ","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.6a970a501ba49b45440e9d10.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_6a970a501ba49b45440e9d10","keyword":["USGS:6a970a501ba49b45440e9d10","environment","hydraulic engineering","water resources"],"modified":"2026-09-02T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-92.284312, 38.910784, -92.274450, 38.912612","theme":["geospatial"],"title":"Example time series of mean water velocity using the paddlewheel propulsion system of the U.S. Geological Survey, Columbia Environmental Research Center eco-flume"},"description":"This dataset contains an example time series of mean water velocity in the U.S. Geological Survey (USGS), Columbia Environmental Research Center (CERC) eco-flume using the paddlewheel propulsion system. Mean water velocity was measured with an area velocity flow meter (AVFM) positioned approximately 6 meters downstream from the entrance to the east channel of the eco-flume. A velocity time series was measured for three target mean velocities (0.1, 0.2, and 0.3 meters per second), with measurements collected at 1 Hertz for a total of 90 minutes at each operating speed.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/4a8da1ae-a174-4a4f-8f67-6ce97f59a3a7","harvest_record_raw":"https://catalog.data.gov/harvest_record/4a8da1ae-a174-4a4f-8f67-6ce97f59a3a7/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_6a970a501ba49b45440e9d10","keyword":["USGS:6a970a501ba49b45440e9d10","environment","hydraulic engineering","water resources"],"last_harvested_date":"2026-09-04T18:33:48.331679","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":0,"publisher":"U.S. Geological Survey","slug":"example-time-series-of-mean-water-velocity-using-the-paddlewheel-propulsion-system-of-the-","spatial_centroid":{"lat":38.911515200000004,"lon":-92.2803672},"spatial_shape":{"coordinates":[[[-92.284312,38.910784],[-92.284312,38.912612],[-92.27445,38.912612],[-92.27445,38.910784],[-92.284312,38.910784]]],"type":"Polygon"},"theme":["geospatial"],"title":"Example time series of mean water velocity using the paddlewheel propulsion system of the U.S. Geological Survey, Columbia Environmental Research Center eco-flume","type":"dataset"},{"_score":9.21921,"_sort":[1788546568762,9.21921,0,"ffe2da68-8a93-40f5-ad3c-3a167fd3780f"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Climate Adaptation Science Center","hasEmail":"mailto:casc-data@usgs.gov"},"description":"This project creates a two-page monthly PDF climate report for forests within Region 3 of the United States Forest Service (USFS). Using geospatial polygon information, these reports summarize and visualize climate statistics for both the Forest- and Ranger District- boundaries. Users can select a Forest of interest and define custom season lengths that better align with local precipitation distribution and management schedules. By leveraging publicly available, open source climate data and a series of R-programming scripts, the project creates a decision support tool that presents timely seasonal climate information to range managers. This project was developed in conjunction with members of the USFS and is designed to aid range managers with stewardship of their land.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.21429/a5fr-7e59","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.08da7432-0331-400f-9a11-3e2ae1f5ee9c.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_08da7432-0331-400f-9a11-3e2ae1f5ee9c","keyword":["Arizona","New Mexico","USGS:08da7432-0331-400f-9a11-3e2ae1f5ee9c","climate change","environment","external research support","forests","geospatial","southwest","southwestern region"],"modified":"2026-09-02T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-115.1367, 31.2410, -102.0000, 37.1603","theme":["geospatial"],"title":"Data and Code to Generate Custom Climate Reports for National Forests in the Southwestern United States"},"description":"This project creates a two-page monthly PDF climate report for forests within Region 3 of the United States Forest Service (USFS). Using geospatial polygon information, these reports summarize and visualize climate statistics for both the Forest- and Ranger District- boundaries. Users can select a Forest of interest and define custom season lengths that better align with local precipitation distribution and management schedules. By leveraging publicly available, open source climate data and a series of R-programming scripts, the project creates a decision support tool that presents timely seasonal climate information to range managers. This project was developed in conjunction with members of the USFS and is designed to aid range managers with stewardship of their land.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/0a37db22-5513-4e9d-b603-adc545f3e52d","harvest_record_raw":"https://catalog.data.gov/harvest_record/0a37db22-5513-4e9d-b603-adc545f3e52d/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_08da7432-0331-400f-9a11-3e2ae1f5ee9c","keyword":["Arizona","New Mexico","USGS:08da7432-0331-400f-9a11-3e2ae1f5ee9c","climate change","environment","external research support","forests","geospatial","southwest","southwestern region"],"last_harvested_date":"2026-09-04T18:29:28.762330","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":0,"publisher":"U.S. Geological Survey","slug":"data-and-code-to-generate-custom-climate-reports-for-national-forests-in-the-southwestern-","spatial_centroid":{"lat":33.60872,"lon":-109.88202000000001},"spatial_shape":{"coordinates":[[[-115.1367,31.241],[-115.1367,37.1603],[-102.0,37.1603],[-102.0,31.241],[-115.1367,31.241]]],"type":"Polygon"},"theme":["geospatial"],"title":"Data and Code to Generate Custom Climate Reports for National Forests in the Southwestern United States","type":"dataset"},{"_score":8.057771,"_sort":[1788546467608,8.057771,0,"6ee2b714-88c1-48cf-bd61-9432e7395552"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Climate Adaptation Science Centers","hasEmail":"mailto:casc-data@usgs.gov"},"description":"Data points intensively sampling 46 North American biomes were used to predict the geographic distribution of biomes from climate variables using the Random Forests classification tree. Techniques were incorporated to accommodate a large number of classes and to predict the future occurrence of climates beyond the contemporary climatic range of the biomes. Errors of prediction from the statistical model averaged 3.7%, but for individual biomes, ranged from 0% to 21.5%. In validating the ability of the model to identify climates without analogs, 78% of 1528 locations outside North America and 81% of land area of the Caribbean Islands were predicted to have no analogs among the 46 biomes. Biome climates were projected into the future according to low and high greenhouse gas emission scenarios of three General Circulation Models for three periods, the decades surrounding 2030, 2060, and 2090. Prominent in the projections were (1) expansion of climates suitable for the tropical dry deciduous forests of Mexico, (2) expansion of climates typifying desertscrub biomes of western USA and northern Mexico, (3) stability of climates typifying the evergreen\u2013deciduous forests of eastern USA, and (4) northward expansion of climates suited to temperate forests, Great Plains grasslands, and montane forests to the detriment of taiga and tundra climates. Maps indicating either poor agreement among projections or climates without contemporary analogs identify geographic areas where land management programs would be most equivocal. Concentrating efforts and resources where projections are more certain can assure land managers a greater likelihood of success.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P146D9YQ","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.57475995e4b07e28b663d8dd.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_57475995e4b07e28b663d8dd","keyword":["British Columbia","Idaho","Montana","Random Forests classification tree","USGS:57475995e4b07e28b663d8dd","Washington","climate change","climate change impacts","climate niche modeling","environment","external research support","geospatial datasets","land management alternatives","pre-SM502.8","vegetation model"],"modified":"2026-09-02T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-125.5000, 46.5000, -114.0000, 53.0000","theme":["geospatial"],"title":"Biome Climatic Niche Model: North American vegetation model data for land-use planning in a changing climate"},"description":"Data points intensively sampling 46 North American biomes were used to predict the geographic distribution of biomes from climate variables using the Random Forests classification tree. Techniques were incorporated to accommodate a large number of classes and to predict the future occurrence of climates beyond the contemporary climatic range of the biomes. Errors of prediction from the statistical model averaged 3.7%, but for individual biomes, ranged from 0% to 21.5%. In validating the ability of the model to identify climates without analogs, 78% of 1528 locations outside North America and 81% of land area of the Caribbean Islands were predicted to have no analogs among the 46 biomes. Biome climates were projected into the future according to low and high greenhouse gas emission scenarios of three General Circulation Models for three periods, the decades surrounding 2030, 2060, and 2090. Prominent in the projections were (1) expansion of climates suitable for the tropical dry deciduous forests of Mexico, (2) expansion of climates typifying desertscrub biomes of western USA and northern Mexico, (3) stability of climates typifying the evergreen\u2013deciduous forests of eastern USA, and (4) northward expansion of climates suited to temperate forests, Great Plains grasslands, and montane forests to the detriment of taiga and tundra climates. Maps indicating either poor agreement among projections or climates without contemporary analogs identify geographic areas where land management programs would be most equivocal. Concentrating efforts and resources where projections are more certain can assure land managers a greater likelihood of success.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/53ad784f-d827-4966-95aa-e456b0ac71bd","harvest_record_raw":"https://catalog.data.gov/harvest_record/53ad784f-d827-4966-95aa-e456b0ac71bd/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_57475995e4b07e28b663d8dd","keyword":["British Columbia","Idaho","Montana","Random Forests classification tree","USGS:57475995e4b07e28b663d8dd","Washington","climate change","climate change impacts","climate niche modeling","environment","external research support","geospatial datasets","land management alternatives","pre-SM502.8","vegetation model"],"last_harvested_date":"2026-09-04T18:27:47.608978","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":0,"publisher":"U.S. Geological Survey","slug":"biome-climatic-niche-model-north-american-vegetation-model-data-for-land-use-planning-in-a","spatial_centroid":{"lat":49.1,"lon":-120.9},"spatial_shape":{"coordinates":[[[-125.5,46.5],[-125.5,53.0],[-114.0,53.0],[-114.0,46.5],[-125.5,46.5]]],"type":"Polygon"},"theme":["geospatial"],"title":"Biome Climatic Niche Model: North American vegetation model data for land-use planning in a changing climate","type":"dataset"},{"_score":7.327364,"_sort":[1788545997523,7.327364,0,"1e2d22a9-d76d-48a0-a6f2-51b6480ea0c0"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Oklahoma-Texas Water Science Center Public Information Officer","hasEmail":"mailto:gs-w-txpublic-info@usgs.gov"},"description":"The U.S. Geological Survey, in cooperation with the Bureau of Reclamation, used five scenarios created from a previously published numerical groundwater-flow model (1980\u20132013) and historical streamflow records (1980\u20132022) to investigate the relation between groundwater withdrawals from the North Fork Red River aquifer and inflows to Lake Altus from the North Fork Red River in western Oklahoma. The five scenarios were (1) a scaled-EPS groundwater-withdrawal scenario, (2) a scaled-reported groundwater-withdrawal scenario, (3) a zonal-scaled-reported groundwater-withdrawal scenario, (4) a historical drought-threshold scenario, and (5) a base-flow and evapotranspiration depletion scenario. This USGS data release contains all input and output files for the groundwater-flow simulations and streamflow and base-flow statistics described in the associated model documentation report (https://doi.org/10.3133/SIR20265047). Supporting geospatial data are provided that were used to display model outputs.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P13GQYDE","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.66bf823bd34e033882839672.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_66bf823bd34e033882839672","keyword":["Beckham County","Greer County","Groundwater Model","Jackson County","Kiowa County","Lake Altus","MODFLOW-NWT","North Fork Red River aquifer","Oklahoma","PEST++","Python","Roger Mills County","USGS:66bf823bd34e033882839672","base flow","environment","geoscientificInformation","groundwater","groundwater flow","hydrology","inlandWaters","modeling","precipitation (atmospheric)","streamflow","streamflow depletion","trends","usgsgroundwatermodel"],"modified":"2026-09-02T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-100.2268, 34.5693, -98.8713, 35.5128","theme":["geospatial"],"title":"MODFLOW-NWT model used to evaluate groundwater-withdrawal scenarios for the North Fork Red River aquifer upgradient from Lake Altus, western Oklahoma, 1980-2022, including streamflow, base-flow, and precipitation statistics"},"description":"The U.S. Geological Survey, in cooperation with the Bureau of Reclamation, used five scenarios created from a previously published numerical groundwater-flow model (1980\u20132013) and historical streamflow records (1980\u20132022) to investigate the relation between groundwater withdrawals from the North Fork Red River aquifer and inflows to Lake Altus from the North Fork Red River in western Oklahoma. The five scenarios were (1) a scaled-EPS groundwater-withdrawal scenario, (2) a scaled-reported groundwater-withdrawal scenario, (3) a zonal-scaled-reported groundwater-withdrawal scenario, (4) a historical drought-threshold scenario, and (5) a base-flow and evapotranspiration depletion scenario. This USGS data release contains all input and output files for the groundwater-flow simulations and streamflow and base-flow statistics described in the associated model documentation report (https://doi.org/10.3133/SIR20265047). Supporting geospatial data are provided that were used to display model outputs.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/a2c1dc68-243d-4c27-ba53-bc505c5198fb","harvest_record_raw":"https://catalog.data.gov/harvest_record/a2c1dc68-243d-4c27-ba53-bc505c5198fb/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_66bf823bd34e033882839672","keyword":["Beckham County","Greer County","Groundwater Model","Jackson County","Kiowa County","Lake Altus","MODFLOW-NWT","North Fork Red River aquifer","Oklahoma","PEST++","Python","Roger Mills County","USGS:66bf823bd34e033882839672","base flow","environment","geoscientificInformation","groundwater","groundwater flow","hydrology","inlandWaters","modeling","precipitation (atmospheric)","streamflow","streamflow depletion","trends","usgsgroundwatermodel"],"last_harvested_date":"2026-09-04T18:19:57.523804","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":0,"publisher":"U.S. Geological Survey","slug":"modflow-nwt-model-used-to-evaluate-groundwater-withdrawal-scenarios-for-the-north-fork-red","spatial_centroid":{"lat":34.9467,"lon":-99.6846},"spatial_shape":{"coordinates":[[[-100.2268,34.5693],[-100.2268,35.5128],[-98.8713,35.5128],[-98.8713,34.5693],[-100.2268,34.5693]]],"type":"Polygon"},"theme":["geospatial"],"title":"MODFLOW-NWT model used to evaluate groundwater-withdrawal scenarios for the North Fork Red River aquifer upgradient from Lake Altus, western Oklahoma, 1980-2022, including streamflow, base-flow, and precipitation statistics","type":"dataset"},{"_score":10.669376,"_sort":[1788545994476,10.669376,0,"521a142e-3d32-41b2-843c-d6d42f8e1425"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Brandon J Sansom","hasEmail":"mailto:bsansom@usgs.gov"},"description":"This dataset contains the velocity magnitude data produced from the computational fluid dynamic (CFD) model depicting flow in the U.S. Geological Survey, Columbia Environmental Research Center eco-flume to simulate the paddlewheel propulsion system. A three-dimensional model was built using Ansys Fluent Software and a momentum source was used to drive the flow and represent the paddlewheel propulsion. The model results were used to assess overall design criteria and evaluate flow uniformity and flow symmetry in the eco-flume.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P14HCGDQ","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.6a9724471ba49b45440ea82d.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_6a9724471ba49b45440ea82d","keyword":["USGS:6a9724471ba49b45440ea82d","environment","hydraulic engineering","water resources"],"modified":"2026-09-02T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-92.284312, 38.910784, -92.274450, 38.912612","theme":["geospatial"],"title":"Computational fluid dynamic (CFD) modeling results of the paddlewheel propulsion system of the U.S. Geological Survey, Columbia Environmental Research Center eco-flume"},"description":"This dataset contains the velocity magnitude data produced from the computational fluid dynamic (CFD) model depicting flow in the U.S. Geological Survey, Columbia Environmental Research Center eco-flume to simulate the paddlewheel propulsion system. A three-dimensional model was built using Ansys Fluent Software and a momentum source was used to drive the flow and represent the paddlewheel propulsion. The model results were used to assess overall design criteria and evaluate flow uniformity and flow symmetry in the eco-flume.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/0e033189-5426-49aa-be47-c9765797fdb2","harvest_record_raw":"https://catalog.data.gov/harvest_record/0e033189-5426-49aa-be47-c9765797fdb2/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_6a9724471ba49b45440ea82d","keyword":["USGS:6a9724471ba49b45440ea82d","environment","hydraulic engineering","water resources"],"last_harvested_date":"2026-09-04T18:19:54.476518","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":0,"publisher":"U.S. Geological Survey","slug":"computational-fluid-dynamic-cfd-modeling-results-of-the-paddlewheel-propulsion-system-of-t","spatial_centroid":{"lat":38.911515200000004,"lon":-92.2803672},"spatial_shape":{"coordinates":[[[-92.284312,38.910784],[-92.284312,38.912612],[-92.27445,38.912612],[-92.27445,38.910784],[-92.284312,38.910784]]],"type":"Polygon"},"theme":["geospatial"],"title":"Computational fluid dynamic (CFD) modeling results of the paddlewheel propulsion system of the U.S. Geological Survey, Columbia Environmental Research Center eco-flume","type":"dataset"},{"_score":7.754089,"_sort":[1788545801978,7.754089,0,"64ce589d-64a3-45fd-b984-bdd54b87f9f1"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Climate Adaptation Science Centers","hasEmail":"mailto:casc-data@usgs.gov"},"description":"Projected current and future potential distribution for several vertebrate species, based on correlative bioclimatic models and projected changes in vegetation biomes. Bioclimatic models were built using the Random Forest algorithm. Projected changes in vegetation were also modeled using the Random Forest algorithm but were produced by Rehfeldt et al. (2012). Projected current distribution is based on the average climate conditions for the years 1961-1990. Projected future distributions are based on average climate conditions for the years 2070-2099 using downscaled (30-second or ~1-kilometer resolution) climate projections from two Global Circulation Models: CGCM3.1 (T47) and UKMO-HadCM3. Both projections use the A2 emissions scenario and are from the CMIP3 (Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report) family of climate simulations.\nDue to changing climatic conditions, species ranges are expected to shift throughout the course of this century. Modeling subsequent shifts in suitable habitat for animal species, and the resulting changes in species assemblages, represent critical information for resource planners and managers. Developing robust suitability models for large geographic areas can be challenging, in part due to insufficient sampling data and to computational limits associated with modeling large geographies at a fine-grained spatial resolution. To overcome these challenges, I developed a method to model habitat suitability in which I built correlative climate suitability models for 366 terrestrial animal species at a relatively coarse spatial resolution for the entire North American continent using species range maps and 23 bioclimatic variables. I then applied the models to both current and projected future climate data downscaled to a moderately fine resolution for western North America. I refined the resulting climate suitability projections by applying a filter that limited suitability to areas in which suitable biomes were projected to be present. I verified my modeling results using an independent species occurrence data set, finding a median accuracy rate of 70%. I found that incorporating information about biomes into the models resulted in projections of larger climate-driven changes in suitability\u2014on average a difference of about 10%. My results also indicate that study species are more likely to see climate-driven losses than gains in habitat suitability. The percentage of study species projected to undergo a significant net decrease in habitat suitability was double the percentage projected to experience a net increase. These results highlight the shortcomings of many broad-scale models and highlight the need to take finer scale vegetation patterns into account. They also indicate that while many animal species could potentially benefit from climate-change induced increases in habitat suitability, the majority of species may suffer from substantial decreases, complicating future conservation efforts.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P13QNMZS","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.9901eac2-ba5e-40a5-bf2a-3c919d8f9b14.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_9901eac2-ba5e-40a5-bf2a-3c919d8f9b14","keyword":["Bioclimatic Model","British Columbia","Climate Adaptation","Climate Change","Climatic Niche Model","Idaho","Montana","Range Shift Model","Species Distribution Model","USGS:9901eac2-ba5e-40a5-bf2a-3c919d8f9b14","Washington","climate change","environment","external research support","geospatial datasets","pre-SM502.8"],"modified":"2026-09-02T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-125.5042, 46.4958, -113.9958, 53.0042","theme":["geospatial"],"title":"Projected habitat suitability for several vertebrate species in the Pacific Northwest based on projected climatic suitability, projected vegetation, and current  land use"},"description":"Projected current and future potential distribution for several vertebrate species, based on correlative bioclimatic models and projected changes in vegetation biomes. Bioclimatic models were built using the Random Forest algorithm. Projected changes in vegetation were also modeled using the Random Forest algorithm but were produced by Rehfeldt et al. (2012). Projected current distribution is based on the average climate conditions for the years 1961-1990. Projected future distributions are based on average climate conditions for the years 2070-2099 using downscaled (30-second or ~1-kilometer resolution) climate projections from two Global Circulation Models: CGCM3.1 (T47) and UKMO-HadCM3. Both projections use the A2 emissions scenario and are from the CMIP3 (Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report) family of climate simulations.\nDue to changing climatic conditions, species ranges are expected to shift throughout the course of this century. Modeling subsequent shifts in suitable habitat for animal species, and the resulting changes in species assemblages, represent critical information for resource planners and managers. Developing robust suitability models for large geographic areas can be challenging, in part due to insufficient sampling data and to computational limits associated with modeling large geographies at a fine-grained spatial resolution. To overcome these challenges, I developed a method to model habitat suitability in which I built correlative climate suitability models for 366 terrestrial animal species at a relatively coarse spatial resolution for the entire North American continent using species range maps and 23 bioclimatic variables. I then applied the models to both current and projected future climate data downscaled to a moderately fine resolution for western North America. I refined the resulting climate suitability projections by applying a filter that limited suitability to areas in which suitable biomes were projected to be present. I verified my modeling results using an independent species occurrence data set, finding a median accuracy rate of 70%. I found that incorporating information about biomes into the models resulted in projections of larger climate-driven changes in suitability\u2014on average a difference of about 10%. My results also indicate that study species are more likely to see climate-driven losses than gains in habitat suitability. The percentage of study species projected to undergo a significant net decrease in habitat suitability was double the percentage projected to experience a net increase. These results highlight the shortcomings of many broad-scale models and highlight the need to take finer scale vegetation patterns into account. They also indicate that while many animal species could potentially benefit from climate-change induced increases in habitat suitability, the majority of species may suffer from substantial decreases, complicating future conservation efforts.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/d949c686-9ef5-4f75-ad89-007d4028a748","harvest_record_raw":"https://catalog.data.gov/harvest_record/d949c686-9ef5-4f75-ad89-007d4028a748/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_9901eac2-ba5e-40a5-bf2a-3c919d8f9b14","keyword":["Bioclimatic Model","British Columbia","Climate Adaptation","Climate Change","Climatic Niche Model","Idaho","Montana","Range Shift Model","Species Distribution Model","USGS:9901eac2-ba5e-40a5-bf2a-3c919d8f9b14","Washington","climate change","environment","external research support","geospatial datasets","pre-SM502.8"],"last_harvested_date":"2026-09-04T18:16:41.978232","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":0,"publisher":"U.S. Geological Survey","slug":"projected-habitat-suitability-for-several-vertebrate-species-in-the-pacific-northwest-base","spatial_centroid":{"lat":49.09916,"lon":-120.90083999999999},"spatial_shape":{"coordinates":[[[-125.5042,46.4958],[-125.5042,53.0042],[-113.9958,53.0042],[-113.9958,46.4958],[-125.5042,46.4958]]],"type":"Polygon"},"theme":["geospatial"],"title":"Projected habitat suitability for several vertebrate species in the Pacific Northwest based on projected climatic suitability, projected vegetation, and current  land use","type":"dataset"},{"_score":8.006668,"_sort":[1788545500083,8.006668,0,"8b2631e5-876b-488b-8922-8b5c5ef43508"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Climate Adaptation Science Centers","hasEmail":"mailto:casc-data@usgs.gov"},"description":"Collection of model inputs and outputs examining different combinations of management and climate scenarios run in southeastern Oregon. The objectives of this project are to explore how climate and land management might interact to shape future vegetation and wildlife habitat, and determine what management actions will likely maximize habitats for key species. Climate scenarios include no climate change, HadGEM global circulation model, representative concentration pathway 8.5, NorESM global circulation model, representative concentration pathway 8.5 (NorESM), MRI global circulation model, representative concentration pathway 8.5 (MRI).","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P142KWFC","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.a1f4de45-06b1-46af-90e1-e52c5d49026a.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_a1f4de45-06b1-46af-90e1-e52c5d49026a","keyword":["Great Basin","Pacific Northwest","Southeast Oregon","USGS:a1f4de45-06b1-46af-90e1-e52c5d49026a","biota","climate change","environment","external research support","geospatial datasets","habitats","land management","modeling","state and transition modeling","vegetation change","vulnerability assessment","wildlife habitat"],"modified":"2026-09-02T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-121.6463, 41.9478, -116.6953, 45.3066","theme":["geospatial"],"title":"Future Sage-Grouse Habitat Scenarios, Southeast Oregon Study Area, 2007-2096"},"description":"Collection of model inputs and outputs examining different combinations of management and climate scenarios run in southeastern Oregon. The objectives of this project are to explore how climate and land management might interact to shape future vegetation and wildlife habitat, and determine what management actions will likely maximize habitats for key species. Climate scenarios include no climate change, HadGEM global circulation model, representative concentration pathway 8.5, NorESM global circulation model, representative concentration pathway 8.5 (NorESM), MRI global circulation model, representative concentration pathway 8.5 (MRI).","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/6f6feaf6-b140-43b2-889b-1aefcedfc2fe","harvest_record_raw":"https://catalog.data.gov/harvest_record/6f6feaf6-b140-43b2-889b-1aefcedfc2fe/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_a1f4de45-06b1-46af-90e1-e52c5d49026a","keyword":["Great Basin","Pacific Northwest","Southeast Oregon","USGS:a1f4de45-06b1-46af-90e1-e52c5d49026a","biota","climate change","environment","external research support","geospatial datasets","habitats","land management","modeling","state and transition modeling","vegetation change","vulnerability assessment","wildlife habitat"],"last_harvested_date":"2026-09-04T18:11:40.083649","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":0,"publisher":"U.S. Geological Survey","slug":"future-sage-grouse-habitat-scenarios-southeast-oregon-study-area-2007-2096","spatial_centroid":{"lat":43.29132,"lon":-119.66590000000001},"spatial_shape":{"coordinates":[[[-121.6463,41.9478],[-121.6463,45.3066],[-116.6953,45.3066],[-116.6953,41.9478],[-121.6463,41.9478]]],"type":"Polygon"},"theme":["geospatial"],"title":"Future Sage-Grouse Habitat Scenarios, Southeast Oregon Study Area, 2007-2096","type":"dataset"},{"_score":34.462994,"_sort":[1788545243074,34.462994,0,"80b00b6f-1247-4b1e-8cae-96fd25b249de"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Climate Adaptation Science Center","hasEmail":"mailto:casc-data@usgs.gov"},"description":"Projected change from historical (1950-2005)  in several hydrometerological variables under three Global Circulation Models for two time periods (2050s and 2080s) under RCP 8.5. This metadata record documents multiple individual datasets, specifically the change from historical (1950-2005) for 12 hydrometerological variables projected by 3 Global Circulation Models (GCM) over 2 future time periods, for one Representative Concentration Pathway (RCP 8.5)\nThe variables are:\nWater Deficit, Spring (March-May)\nWater Deficit, Summer (July-September)\nPotential Evapotranspiration, Spring (March-May)\nPotential Evapotranspiration, Summer (July-September)\nTotal Runoff, Summer (June-August)\nTotal Runoff, Spring (March-May)\nSoil Moisture, Summer (July-September)\nEvapotranspiration, Spring (March-May)\nEvapotranspiration, Summer (July-September)\nLength of the Snow Season\nSpring (April 1st) Snowpack\nLate Spring (May 1st) Snowpack\nPercentage of Winter Precipitation Captured in April 1st Snowpack\nThe three GCMs  are:\nCanESM2\nCNRM-CM5\nCCSM4\nThe two time periods are:\n2050s (2040-2069)\n2080s (2070-2099)","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P14BFQDH","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.1cc1aaa5-1180-4d94-96fc-e9d9a1ee2e0b.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_1cc1aaa5-1180-4d94-96fc-e9d9a1ee2e0b","keyword":["USGS:1cc1aaa5-1180-4d94-96fc-e9d9a1ee2e0b","biota","climate change","climate projections","climatologyMeteorologyAtmosphere","ecosystem services","external research support","geospatial datasets","pre-SM502.8"],"modified":"2026-09-02T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-124.4531, 42.0330, -111.6211, 49.2678","theme":["geospatial"],"title":"Integrated scenarios of the future Northwest U.S. environment: hydrometerological projections for 2050s and 2080s, CMIP5 models, RCP 8.5"},"description":"Projected change from historical (1950-2005)  in several hydrometerological variables under three Global Circulation Models for two time periods (2050s and 2080s) under RCP 8.5. This metadata record documents multiple individual datasets, specifically the change from historical (1950-2005) for 12 hydrometerological variables projected by 3 Global Circulation Models (GCM) over 2 future time periods, for one Representative Concentration Pathway (RCP 8.5)\nThe variables are:\nWater Deficit, Spring (March-May)\nWater Deficit, Summer (July-September)\nPotential Evapotranspiration, Spring (March-May)\nPotential Evapotranspiration, Summer (July-September)\nTotal Runoff, Summer (June-August)\nTotal Runoff, Spring (March-May)\nSoil Moisture, Summer (July-September)\nEvapotranspiration, Spring (March-May)\nEvapotranspiration, Summer (July-September)\nLength of the Snow Season\nSpring (April 1st) Snowpack\nLate Spring (May 1st) Snowpack\nPercentage of Winter Precipitation Captured in April 1st Snowpack\nThe three GCMs  are:\nCanESM2\nCNRM-CM5\nCCSM4\nThe two time periods are:\n2050s (2040-2069)\n2080s (2070-2099)","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/95e4bba0-298b-4c87-aad8-eb0fba3b9a53","harvest_record_raw":"https://catalog.data.gov/harvest_record/95e4bba0-298b-4c87-aad8-eb0fba3b9a53/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_1cc1aaa5-1180-4d94-96fc-e9d9a1ee2e0b","keyword":["USGS:1cc1aaa5-1180-4d94-96fc-e9d9a1ee2e0b","biota","climate change","climate projections","climatologyMeteorologyAtmosphere","ecosystem services","external research support","geospatial datasets","pre-SM502.8"],"last_harvested_date":"2026-09-04T18:07:23.074186","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":0,"publisher":"U.S. Geological Survey","slug":"integrated-scenarios-of-the-future-northwest-u-s-environment-hydrometerological-projection","spatial_centroid":{"lat":44.92692,"lon":-119.3203},"spatial_shape":{"coordinates":[[[-124.4531,42.033],[-124.4531,49.2678],[-111.6211,49.2678],[-111.6211,42.033],[-124.4531,42.033]]],"type":"Polygon"},"theme":["geospatial"],"title":"Integrated scenarios of the future Northwest U.S. environment: hydrometerological projections for 2050s and 2080s, CMIP5 models, RCP 8.5","type":"dataset"},{"_score":10.669376,"_sort":[1788545052113,10.669376,0,"f3f0d653-5967-45b0-983a-5b7aac83bd51"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Brandon J Sansom","hasEmail":"mailto:bsansom@usgs.gov"},"description":"This dataset contains the time-averaged velocity data collected to characterize the hydraulics of the jet propulsion system of the U.S. Geological Survey (USGS), Columbia Environmental Research Center (CERC) eco-flume. Acoustic Doppler Velocimeter (ADV) measurements were taken at select locations throughout the eco-flume and at select jet pump operating speeds to provide a baseline assessment of the hydraulics produced by the jet pumps.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P14HCGDQ","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.6a970c111ba49b45440e9d26.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_6a970c111ba49b45440e9d26","keyword":["USGS:6a970c111ba49b45440e9d26","environment","hydraulic engineering","water resources"],"modified":"2026-09-02T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-92.284312, 38.910784, -92.274450, 38.912612","theme":["geospatial"],"title":"Hydraulic characterization of the jet propulsion system of the U.S. Geological Survey, Columbia Environmental Research Center eco-flume"},"description":"This dataset contains the time-averaged velocity data collected to characterize the hydraulics of the jet propulsion system of the U.S. Geological Survey (USGS), Columbia Environmental Research Center (CERC) eco-flume. Acoustic Doppler Velocimeter (ADV) measurements were taken at select locations throughout the eco-flume and at select jet pump operating speeds to provide a baseline assessment of the hydraulics produced by the jet pumps.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/57e8fbd8-c580-47b5-9d02-a26c8b5f4d89","harvest_record_raw":"https://catalog.data.gov/harvest_record/57e8fbd8-c580-47b5-9d02-a26c8b5f4d89/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_6a970c111ba49b45440e9d26","keyword":["USGS:6a970c111ba49b45440e9d26","environment","hydraulic engineering","water resources"],"last_harvested_date":"2026-09-04T18:04:12.113088","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":0,"publisher":"U.S. Geological Survey","slug":"hydraulic-characterization-of-the-jet-propulsion-system-of-the-u-s-geological-survey-colum","spatial_centroid":{"lat":38.911515200000004,"lon":-92.2803672},"spatial_shape":{"coordinates":[[[-92.284312,38.910784],[-92.284312,38.912612],[-92.27445,38.912612],[-92.27445,38.910784],[-92.284312,38.910784]]],"type":"Polygon"},"theme":["geospatial"],"title":"Hydraulic characterization of the jet propulsion system of the U.S. Geological Survey, Columbia Environmental Research Center eco-flume","type":"dataset"},{"_score":7.8278427,"_sort":[1788544920446,7.8278427,0,"2687a69f-2d9b-4e7e-8915-5f1a6e2b60f0"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Sarah Lewis, College of Earth, Ocean, and Atmospheric Sciences, Oregon\n                        State University","hasEmail":"mailto:sarah.lewis@oregonstate.edu"},"description":"Daily observed (historical) and RHESSys simulated streamflow under 3 climate change scenarios for eight Oregon watersheds. RHESSys and SnowModel simulated daily snow water equivalent (SWE) values.  Eight Oregon watersheds; 4 within the upper McKenzie River Basin (Anderson, Boulder, McKenzie at Clear Lake, and Lookout), 3 within the Metolius River Basin (Canyon, Jefferson and Jack) and Shitike Creek.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P13BYWQJ","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.60064b2c-fce8-4625-9e55-8bf6eb1388e4.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_60064b2c-fce8-4625-9e55-8bf6eb1388e4","keyword":["Anderson Creek","Boulder Creek","Canyon Creek","Central Oregon","Jack Creek","Oregon","Regional Hydro-Ecologic Simulation System (RHESSys)","USGS:60064b2c-fce8-4625-9e55-8bf6eb1388e4","environment","external research support","modeled discharge","modeling","projections","snow water equivalent (SWE)"],"modified":"2026-08-26T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"theme":["geospatial"],"title":"Daily observed (historical) and RHESSys simulated streamflow under three climate change scenarios for eight Oregon watersheds"},"description":"Daily observed (historical) and RHESSys simulated streamflow under 3 climate change scenarios for eight Oregon watersheds. RHESSys and SnowModel simulated daily snow water equivalent (SWE) values.  Eight Oregon watersheds; 4 within the upper McKenzie River Basin (Anderson, Boulder, McKenzie at Clear Lake, and Lookout), 3 within the Metolius River Basin (Canyon, Jefferson and Jack) and Shitike Creek.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/f318fb3b-8e27-44a3-adbc-f2e2c7f2a089","harvest_record_raw":"https://catalog.data.gov/harvest_record/f318fb3b-8e27-44a3-adbc-f2e2c7f2a089/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_60064b2c-fce8-4625-9e55-8bf6eb1388e4","keyword":["Anderson Creek","Boulder Creek","Canyon Creek","Central Oregon","Jack Creek","Oregon","Regional Hydro-Ecologic Simulation System (RHESSys)","USGS:60064b2c-fce8-4625-9e55-8bf6eb1388e4","environment","external research support","modeled discharge","modeling","projections","snow water equivalent (SWE)"],"last_harvested_date":"2026-09-04T18:02:00.446462","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":0,"publisher":"U.S. Geological Survey","slug":"daily-observed-historical-and-rhessys-simulated-streamflow-under-three-climate-change-scen","spatial_centroid":null,"spatial_shape":null,"theme":["geospatial"],"title":"Daily observed (historical) and RHESSys simulated streamflow under three climate change scenarios for eight Oregon watersheds","type":"dataset"},{"_score":10.274181,"_sort":[1788462381781,10.274181,0,"ae5aa0bc-d449-404a-ae2e-783c05b24e2f"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Claudine Tobalske","hasEmail":"mailto:claudine.tobalske@umontana.edu"},"description":"Training points collected in the field between 2012 and 2013 were grouped into 18 classes: Forested Burn (66), Foothill Woodland Steppe Transition (73), Greasewood Flat (73), Greasewood Steppe (239), Greasewood Sage Steppe (277), Great Plains Badlands (166), Great Plains Riparian (255), Low Density Sage Steppe (776), Medium Density Sage Steppe (783), Mixed Grass Prairie (555), Mixed Grass Prairie Burned (278), Ponderosa Pine Woodland and Shrubland (512), Riparian Floodplain (223), Semi-Desert Grassland (103), Sparsely Vegetated Mixed Shrub (252), Silver Sage Flat (70) , Silver Sage Steppe (64), and Water (246). When insufficient field data were available for a class, we augmented it through photointerpretation of 15 cm aerial imagery, using expert knowledge and field experience to guide us.  The final dataset had 5,011 training points.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P13GLFEK","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.b6e48afd-b70a-4d4a-b76f-9dd9dcc181dc.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_b6e48afd-b70a-4d4a-b76f-9dd9dcc181dc","keyword":["USGS:b6e48afd-b70a-4d4a-b76f-9dd9dcc181dc","environment","external research support","geospatial datasets"],"modified":"2026-09-01T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-109.2243, 47.2329, -106.4084, 48.2505","theme":["geospatial"],"title":"Training Points for Landcover Classification of the Charles M. Russell National Wildlife Refuge"},"description":"Training points collected in the field between 2012 and 2013 were grouped into 18 classes: Forested Burn (66), Foothill Woodland Steppe Transition (73), Greasewood Flat (73), Greasewood Steppe (239), Greasewood Sage Steppe (277), Great Plains Badlands (166), Great Plains Riparian (255), Low Density Sage Steppe (776), Medium Density Sage Steppe (783), Mixed Grass Prairie (555), Mixed Grass Prairie Burned (278), Ponderosa Pine Woodland and Shrubland (512), Riparian Floodplain (223), Semi-Desert Grassland (103), Sparsely Vegetated Mixed Shrub (252), Silver Sage Flat (70) , Silver Sage Steppe (64), and Water (246). When insufficient field data were available for a class, we augmented it through photointerpretation of 15 cm aerial imagery, using expert knowledge and field experience to guide us.  The final dataset had 5,011 training points.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/f60f4b54-fce0-4d49-b651-b62a2f43cd6f","harvest_record_raw":"https://catalog.data.gov/harvest_record/f60f4b54-fce0-4d49-b651-b62a2f43cd6f/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_b6e48afd-b70a-4d4a-b76f-9dd9dcc181dc","keyword":["USGS:b6e48afd-b70a-4d4a-b76f-9dd9dcc181dc","environment","external research support","geospatial datasets"],"last_harvested_date":"2026-09-03T19:06:21.781360","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":0,"publisher":"U.S. Geological Survey","slug":"training-points-for-landcover-classification-of-the-charles-m-russell-national-wildlife-re","spatial_centroid":{"lat":47.63994,"lon":-108.09794},"spatial_shape":{"coordinates":[[[-109.2243,47.2329],[-109.2243,48.2505],[-106.4084,48.2505],[-106.4084,47.2329],[-109.2243,47.2329]]],"type":"Polygon"},"theme":["geospatial"],"title":"Training Points for Landcover Classification of the Charles M. Russell National Wildlife Refuge","type":"dataset"},{"_score":9.684088,"_sort":[1788462361439,9.684088,0,"01bce610-0348-4f91-a767-cbb5264e0973"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Neil Terry","hasEmail":"mailto:nterry@usgs.gov"},"description":"This data release contains near surface geophysical data (frequency domain electromagnetics [FDEM], direct current electrical resistivity tomography [ERT], ground penetrating radar [GPR], magnetometry [MAG], and passive seismic horizontal to vertical spectral ratio [HVSR]) data collected at the Havasu Landing marina and hardware store (Chemehuevi Tribe Territory) in March 2022. Raw data, processed inversions (electrical conductivity versus depth), data dictionaries and README files for each instrument are contained in the attached files.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P1EUK84J","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.679954c7d34ea8c18376ebc3.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_679954c7d34ea8c18376ebc3","keyword":["California","Havasu Lake","Hydrogeology","USGS:679954c7d34ea8c18376ebc3","Water Resources","electromagnetic surveying","environment","geophysics","geoscientificInformation","groundwater","groundwater quality"],"modified":"2026-09-01T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-114.409, 34.4819, -114.4045, 34.4844","theme":["geospatial"],"title":"Geophysical data from the Chemehuevi Tribe Havasu Lake, California Havasu Landing Resort marina (CHEM001) and hardware store (CHEM004) LUST sites"},"description":"This data release contains near surface geophysical data (frequency domain electromagnetics [FDEM], direct current electrical resistivity tomography [ERT], ground penetrating radar [GPR], magnetometry [MAG], and passive seismic horizontal to vertical spectral ratio [HVSR]) data collected at the Havasu Landing marina and hardware store (Chemehuevi Tribe Territory) in March 2022. Raw data, processed inversions (electrical conductivity versus depth), data dictionaries and README files for each instrument are contained in the attached files.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/693d9917-e42c-4bcf-8ef9-d4f3ffcf56b9","harvest_record_raw":"https://catalog.data.gov/harvest_record/693d9917-e42c-4bcf-8ef9-d4f3ffcf56b9/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_679954c7d34ea8c18376ebc3","keyword":["California","Havasu Lake","Hydrogeology","USGS:679954c7d34ea8c18376ebc3","Water Resources","electromagnetic surveying","environment","geophysics","geoscientificInformation","groundwater","groundwater quality"],"last_harvested_date":"2026-09-03T19:06:01.439241","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":0,"publisher":"U.S. Geological Survey","slug":"geophysical-data-from-the-chemehuevi-tribe-havasu-lake-california-havasu-landing-resort-ma","spatial_centroid":{"lat":34.4829,"lon":-114.40720000000002},"spatial_shape":{"coordinates":[[[-114.409,34.4819],[-114.409,34.4844],[-114.4045,34.4844],[-114.4045,34.4819],[-114.409,34.4819]]],"type":"Polygon"},"theme":["geospatial"],"title":"Geophysical data from the Chemehuevi Tribe Havasu Lake, California Havasu Landing Resort marina (CHEM001) and hardware store (CHEM004) LUST sites","type":"dataset"},{"_score":9.6728,"_sort":[1788461807890,9.6728,0,"9d110451-4318-4b3f-b233-2c04d8f7bc79"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Peter A. Bieniek","hasEmail":"mailto:pbieniek@alaska.edu"},"description":"This database contains the daily historical fire weather indices averaged over 21 Alaska Predictive Service Areas (PSAs) at elevations at or below 600m for 1979-2017. All indices were computed using meteorological data from the 20km dynamically downscaled ERA-Interim reanalysis.The fire weather indices here are:\n-Evaporative Demand Drought Index (EDDI) for 1, 15, 52, and 90-day -Standardized Precipitation Evapotranspiration Index (SPEI) for 1, 15, 52, and 90-day \n-Reference Evapotranspiration (et0) used to compute EDDI \n-Precipitation minus et0 used to compute SPEI \n-Vapor Pressure Deficit (VPD) \n-Growing Season Index (GSI) for daily and 21-day moving average","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P1428CGK","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.da3da7ae-dde3-4829-b087-d3cbe95de8bd.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_da3da7ae-dde3-4829-b087-d3cbe95de8bd","keyword":["USGS:da3da7ae-dde3-4829-b087-d3cbe95de8bd","climate change","environment","external research support","fire","historical","weather","wildland"],"modified":"2026-09-01T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-179.9900, 50.1500, -129.7200, 72.2000","theme":["geospatial"],"title":"Daily historical fire weather indices averaged over 21 Alaska Predictive Service Areas (PSAs) at elevations at or below 600m for 1979-2017"},"description":"This database contains the daily historical fire weather indices averaged over 21 Alaska Predictive Service Areas (PSAs) at elevations at or below 600m for 1979-2017. All indices were computed using meteorological data from the 20km dynamically downscaled ERA-Interim reanalysis.The fire weather indices here are:\n-Evaporative Demand Drought Index (EDDI) for 1, 15, 52, and 90-day -Standardized Precipitation Evapotranspiration Index (SPEI) for 1, 15, 52, and 90-day \n-Reference Evapotranspiration (et0) used to compute EDDI \n-Precipitation minus et0 used to compute SPEI \n-Vapor Pressure Deficit (VPD) \n-Growing Season Index (GSI) for daily and 21-day moving average","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/dc4f8e4d-11a1-45a2-b09b-5a1534b73358","harvest_record_raw":"https://catalog.data.gov/harvest_record/dc4f8e4d-11a1-45a2-b09b-5a1534b73358/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_da3da7ae-dde3-4829-b087-d3cbe95de8bd","keyword":["USGS:da3da7ae-dde3-4829-b087-d3cbe95de8bd","climate change","environment","external research support","fire","historical","weather","wildland"],"last_harvested_date":"2026-09-03T18:56:47.890676","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":0,"publisher":"U.S. Geological Survey","slug":"daily-historical-fire-weather-indices-averaged-over-21-alaska-predictive-service-1979-2017","spatial_centroid":{"lat":58.970000000000006,"lon":-159.882},"spatial_shape":{"coordinates":[[[-179.99,50.15],[-179.99,72.2],[-129.72,72.2],[-129.72,50.15],[-179.99,50.15]]],"type":"Polygon"},"theme":["geospatial"],"title":"Daily historical fire weather indices averaged over 21 Alaska Predictive Service Areas (PSAs) at elevations at or below 600m for 1979-2017","type":"dataset"},{"_score":7.846841,"_sort":[1788461656853,7.846841,0,"1aff20fe-1c31-4d7f-9e2f-6c06c6697a0c"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Trevor F. Partridge","hasEmail":"mailto:tpartridge@usgs.gov"},"description":"This dataset contains model input and output files for WRF-Hydro simulations over three wildfire-impacted basins in the western United States: Mill Creek Basin in Montana (Chippy Creek Fire, 2007), North Inlet of Grand Lake in Colorado (East Troublesome Fire, 2020), and East Fork of the Jemez River in New Mexico (Las Conchas Fire, 2011). Each domain includes simulations for three scenarios\u2014a two-year pre-fire period, a two-year post-fire period, and a two-year counterfactual no-fire period\u2014designed to assess hydrologic response to wildfire disturbance. The modeling framework integrates burn severity land cover classes into a modified version of WRF-Hydro v5.2, calibrated using the PEST++ iterative Ensemble Smoother (iES). Simulations use the NOAH-MP land surface model at 1 km resolution with 250 m routing, and are forced with data from the CONUS404 reanalysis.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P14VMLBW","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.680ba981d4be02201034d4f6.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_680ba981d4be02201034d4f6","keyword":["Colorado","Grand Lake","Jemez River","Mill Creek Basin","Montana","New Mexico","USGS:680ba981d4be02201034d4f6","WRF-Hydro","biota","environment","fires","geoscientificInformation","hydrologic models","inlandWaters","inverse modeling","mathematical modeling","snow and ice cover","surface water","water cycle","western United States"],"modified":"2026-09-01T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-116.6309, 34.9580, -104.7656, 49.0379","theme":["geospatial"],"title":"WRF-Hydro model datasets for simulating post-wildfire hydrologic response in three snow-dominated basins in the western United States"},"description":"This dataset contains model input and output files for WRF-Hydro simulations over three wildfire-impacted basins in the western United States: Mill Creek Basin in Montana (Chippy Creek Fire, 2007), North Inlet of Grand Lake in Colorado (East Troublesome Fire, 2020), and East Fork of the Jemez River in New Mexico (Las Conchas Fire, 2011). Each domain includes simulations for three scenarios\u2014a two-year pre-fire period, a two-year post-fire period, and a two-year counterfactual no-fire period\u2014designed to assess hydrologic response to wildfire disturbance. The modeling framework integrates burn severity land cover classes into a modified version of WRF-Hydro v5.2, calibrated using the PEST++ iterative Ensemble Smoother (iES). Simulations use the NOAH-MP land surface model at 1 km resolution with 250 m routing, and are forced with data from the CONUS404 reanalysis.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/f7dffdb9-3026-4225-b48f-3cbe6f03ed5e","harvest_record_raw":"https://catalog.data.gov/harvest_record/f7dffdb9-3026-4225-b48f-3cbe6f03ed5e/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_680ba981d4be02201034d4f6","keyword":["Colorado","Grand Lake","Jemez River","Mill Creek Basin","Montana","New Mexico","USGS:680ba981d4be02201034d4f6","WRF-Hydro","biota","environment","fires","geoscientificInformation","hydrologic models","inlandWaters","inverse modeling","mathematical modeling","snow and ice cover","surface water","water cycle","western United States"],"last_harvested_date":"2026-09-03T18:54:16.853636","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":0,"publisher":"U.S. Geological Survey","slug":"wrf-hydro-model-datasets-for-simulating-post-wildfire-hydrologic-response-in-three-snow-do","spatial_centroid":{"lat":40.58996,"lon":-111.88478},"spatial_shape":{"coordinates":[[[-116.6309,34.958],[-116.6309,49.0379],[-104.7656,49.0379],[-104.7656,34.958],[-116.6309,34.958]]],"type":"Polygon"},"theme":["geospatial"],"title":"WRF-Hydro model datasets for simulating post-wildfire hydrologic response in three snow-dominated basins in the western United States","type":"dataset"},{"_score":9.554555,"_sort":[1788461012641,9.554555,0,"19a80eab-0209-4cfa-9b61-1676694c7456"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Neil Terry","hasEmail":"mailto:nterry@usgs.gov"},"description":"This data release contains borehole geophysical data (natural gamma, electromagnetic induction (EMI), fluid electrical conductivity, and fluid temperature) and driller's log information (soil texture and descriptions) from several wells and borings at the Havasu Landing Resort marina and hardware store (Chemehuevi Tribe Territory) site. Thirteen wells have both geophysical logging data and driller's log texture information, while an additional eleven wells have driller's log information only.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P14DD8XC","description":"Landing page for access to the data","format":"XML","mediaType":"application/http","title":"Digital Data"},{"@type":"dcat:Distribution","description":"The metadata original format","downloadURL":"https://data.usgs.gov/datacatalog/metadata/USGS.679c2e8cd34ea8c183773a4c.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_679c2e8cd34ea8c183773a4c","keyword":["California","Havasu Lake","Hydrogeology","USGS:679c2e8cd34ea8c183773a4c","Water Resources","electromagnetic surveying","environment","geophysics","geoscientificInformation","groundwater","groundwater quality"],"modified":"2026-09-01T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-114.409, 34.4819, -114.4045, 34.4844","theme":["geospatial"],"title":"Borehole geophysical data from the Chemehuevi Tribe Havasu Lake, California Havasu Landing Resort marina (CHEM001) and hardware store (CHEM004) LUST sites"},"description":"This data release contains borehole geophysical data (natural gamma, electromagnetic induction (EMI), fluid electrical conductivity, and fluid temperature) and driller's log information (soil texture and descriptions) from several wells and borings at the Havasu Landing Resort marina and hardware store (Chemehuevi Tribe Territory) site. Thirteen wells have both geophysical logging data and driller's log texture information, while an additional eleven wells have driller's log information only.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/06a98e97-85b2-41d3-a5c9-90d128a53a93","harvest_record_raw":"https://catalog.data.gov/harvest_record/06a98e97-85b2-41d3-a5c9-90d128a53a93/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_679c2e8cd34ea8c183773a4c","keyword":["California","Havasu Lake","Hydrogeology","USGS:679c2e8cd34ea8c183773a4c","Water Resources","electromagnetic surveying","environment","geophysics","geoscientificInformation","groundwater","groundwater quality"],"last_harvested_date":"2026-09-03T18:43:32.641504","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"143529f7-2eef-4a07-b227-93ac9e84fad8","logo":"https://raw.githubusercontent.com/GSA/logo/master/doi.png","name":"Department of the Interior","organization_type":"Federal Government","slug":"doi"},"parent_identifier":null,"popularity":0,"publisher":"U.S. Geological Survey","slug":"borehole-geophysical-data-from-the-chemehuevi-tribe-havasu-lake-california-havasu-landing-","spatial_centroid":{"lat":34.4829,"lon":-114.40720000000002},"spatial_shape":{"coordinates":[[[-114.409,34.4819],[-114.409,34.4844],[-114.4045,34.4844],[-114.4045,34.4819],[-114.409,34.4819]]],"type":"Polygon"},"theme":["geospatial"],"title":"Borehole geophysical data from the Chemehuevi Tribe Havasu Lake, California Havasu Landing Resort marina (CHEM001) and hardware store (CHEM004) LUST sites","type":"dataset"},{"_score":8.342478,"_sort":[1788460654533,8.342478,1,"30913801-247e-4c30-917b-874f48fae3e1"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["021:15"],"contactPoint":{"@type":"vcard:Contact","fn":"Elina Zlotchenko","hasEmail":"mailto:Elina.Zlotchenko@dot.gov"},"description":"Part of Wyoming Department of Transportation Connected Vehicle Pilot Phase 4. Test case WV2IMCT-1 Verify V2I communication for log file offload.","distribution":[{"@type":"dcat:Distribution","describedBy":"https://data.transportation.gov/api/views/yjfw-8zsx/columns.json","describedByType":"application/json","downloadURL":"https://data.transportation.gov/api/v3/views/yjfw-8zsx/query.json?accessType=DOWNLOAD","mediaType":"application/json"},{"@type":"dcat:Distribution","describedBy":"https://data.transportation.gov/api/views/yjfw-8zsx/columns.xml","describedByType":"application/xml","downloadURL":"https://data.transportation.gov/api/v3/views/yjfw-8zsx/query.xml?accessType=DOWNLOAD","mediaType":"application/xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.transportation.gov/api/v3/views/yjfw-8zsx/export.csv?accessType=DOWNLOAD","mediaType":"text/csv"},{"@type":"dcat:Distribution","downloadURL":"https://data.transportation.gov/api/v3/views/yjfw-8zsx/export.kml?accessType=DOWNLOAD","mediaType":"application/vnd.google-earth.kml+xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.transportation.gov/api/v3/views/yjfw-8zsx/export.kmz?accessType=DOWNLOAD","mediaType":"application/vnd.google-earth.kmz"},{"@type":"dcat:Distribution","downloadURL":"https://data.transportation.gov/api/v3/views/yjfw-8zsx/query.geojson?accessType=DOWNLOAD","mediaType":"application/geo+json"}],"identifier":"https://data.transportation.gov/api/views/yjfw-8zsx","issued":"2024-07-19","keyword":["connected equipment","connected vehicle","connected vehicle data","connected vehicle environment","connected vehicle message","connected vehicles","on-board equipment","on-board unit","road side unit","roadside equipment","vehicle data","vehicle to infrastructure","vehicle to vehicle"],"landingPage":"https://data.transportation.gov/d/yjfw-8zsx","license":"http://www.usa.gov/publicdomain/label/1.0/","modified":"2026-09-03","programCode":["021:042"],"publisher":{"@type":"org:Organization","name":"Federal Highway Administration"},"spatial":"Wyoming","theme":["Automobiles"],"title":"LTE-V2X Wyoming Connected Vehicle Pilot test ID WV2IMCT-1"},"description":"Part of Wyoming Department of Transportation Connected Vehicle Pilot Phase 4. Test case WV2IMCT-1 Verify V2I communication for log file offload.","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/fd7c816b-5eed-4c6a-b9bb-00ce523a11f3","harvest_record_raw":"https://catalog.data.gov/harvest_record/fd7c816b-5eed-4c6a-b9bb-00ce523a11f3/raw","has_download":true,"has_spatial":true,"identifier":"https://data.transportation.gov/api/views/yjfw-8zsx","keyword":["connected equipment","connected vehicle","connected vehicle data","connected vehicle environment","connected vehicle message","connected vehicles","on-board equipment","on-board unit","road side unit","roadside equipment","vehicle data","vehicle to infrastructure","vehicle to vehicle"],"last_harvested_date":"2026-09-03T18:37:34.533337","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"c549d5ce-2b93-4397-ab76-aa2b31d9983a","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/dot.png","name":"Department of Transportation","organization_type":"Federal Government","slug":"dot"},"parent_identifier":null,"popularity":1,"publisher":"Federal Highway Administration","slug":"lte-v2x-wyoming-connected-vehicle-pilot-test-id-wv2imct-1","spatial_centroid":null,"spatial_shape":null,"theme":["Automobiles"],"title":"LTE-V2X Wyoming Connected Vehicle Pilot test ID WV2IMCT-1","type":"dataset"},{"_score":16.292671,"_sort":[1788460654128,16.292671,1,"b266f890-e6ea-4021-aa1a-cd6f914b8041"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","accrualPeriodicity":"R/P1Y","agencyDataSeriesURL":"http://www.nhtsa.gov/Laws+&+Regulations/Guidance+Documents","agencyProgramURL":"http://www.nhtsa.gov/Laws+&+Regulations/Guidance+Documents","analysisUnit":"Regulations","bureauCode":["021:18"],"categoryDesignation":"Research","collectionInstrument":"Transportation","contactPoint":{"@type":"vcard:Contact","fn":"NHTSA-Datahub","hasEmail":"mailto:NHTSA-Datahub@dot.gov"},"dataQuality":true,"description":"A list of Significant Guidance documents, which include guidance document disseminated to regulated entities or the general public that may reasonably be anticipated to lead to an annual effect on the economy of $100 million or more or adversely affect in a material way the economy, a sector of the economy, productivity, competition, jobs, the environment, public health or safety, or State, local, or tribal governments or communities; create a serious inconsistency or otherwise interfere with an action taken or planned by another agency; materially alter the budgetary impact of entitlements, grants, user fees, or loan programs or the rights and obligations of recipients thereof; or raise novel legal or policy issues arising out of legal mandates, the President's priorities, or the principles set forth in Executive Order 12866, as further amended.","distribution":[{"@type":"dcat:Distribution","downloadURL":"http://www.nhtsa.gov/Laws+&+Regulations/Guidance+Documents","mediaType":"text/html"}],"identifier":"319.2","isPartOf":"DOT-319","issued":"2011-01-18","keyword":["data.gov","law","significant guidance","transportation"],"landingPage":"https://data.transportation.gov/d/yiqj-3kme","language":["en-US"],"license":"https://project-open-data.cio.gov/unknown-license/","modified":"2026-09-03","phone":"202-366-4308","programCode":["021:000"],"publisher":{"@type":"org:Organization","name":"National Highway Traffic Safety Administration"},"references":["http://www.nhtsa.gov/Laws+&+Regulations/Guidance+Documents"],"temporal":"R/2006-01-01/P1Y","theme":["Transportation"],"title":"Significant Guidance Issued by the National Highway Traffic Safety Administration -"},"description":"A list of Significant Guidance documents, which include guidance document disseminated to regulated entities or the general public that may reasonably be anticipated to lead to an annual effect on the economy of $100 million or more or adversely affect in a material way the economy, a sector of the economy, productivity, competition, jobs, the environment, public health or safety, or State, local, or tribal governments or communities; create a serious inconsistency or otherwise interfere with an action taken or planned by another agency; materially alter the budgetary impact of entitlements, grants, user fees, or loan programs or the rights and obligations of recipients thereof; or raise novel legal or policy issues arising out of legal mandates, the President's priorities, or the principles set forth in Executive Order 12866, as further amended.","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/5073eabd-a973-4bca-9b30-a79f4da49932","harvest_record_raw":"https://catalog.data.gov/harvest_record/5073eabd-a973-4bca-9b30-a79f4da49932/raw","has_download":true,"has_spatial":false,"identifier":"319.2","keyword":["data.gov","law","significant guidance","transportation"],"last_harvested_date":"2026-09-03T18:37:34.128297","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"c549d5ce-2b93-4397-ab76-aa2b31d9983a","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/dot.png","name":"Department of Transportation","organization_type":"Federal Government","slug":"dot"},"parent_identifier":"DOT-319","popularity":1,"publisher":"National Highway Traffic Safety Administration","slug":"significant-guidance-issued-by-the-national-highway-traffic-safety-administration-77904","spatial_centroid":null,"spatial_shape":null,"theme":["Transportation"],"title":"Significant Guidance Issued by the National Highway Traffic Safety Administration -","type":"dataset"},{"_score":16.18334,"_sort":[1788460644438,16.18334,1,"76d5107c-7f9b-403d-ad13-79b075fcc687"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","accrualPeriodicity":"irregular","agencyDataSeriesURL":"http://www.fmcsa.dot.gov/rules-regulations/administration/fmcsr/fmcsrguide.aspx%3Fsection_type=G","agencyProgramURL":"http://www.fmcsa.dot.gov/rules-regulations/administration/fmcsr/fmcsrguide.aspx%3Fsection_type=G","analysisUnit":"Regulations","bureauCode":["021:17"],"categoryDesignation":"Research","collectionInstrument":"Transportation","contactPoint":{"@type":"vcard:Contact","fn":"FMCSA CDO","hasEmail":"mailto:fmcsa.cdo@dot.gov"},"dataQuality":true,"description":"A list of Significant Guidance documents, which include guidance document disseminated to regulated entities or the general public that may reasonably be anticipated to lead to an annual effect on the economy of $100 million or more or adversely affect in a material way the economy, a sector of the economy, productivity, competition, jobs, the environment, public health or safety, or State, local, or tribal governments or communities; create a serious inconsistency or otherwise interfere with an action taken or planned by another agency; materially alter the budgetary impact of entitlements, grants, user fees, or loan programs or the rights and obligations of recipients thereof; or raise novel legal or policy issues arising out of legal mandates, the President's priorities, or the principles set forth in Executive Order 12866, as further amended.","distribution":[{"@type":"dcat:Distribution","downloadURL":"http://www.fmcsa.dot.gov/rules-regulations/administration/fmcsr/fmcsrguide.aspx%3Fsection_type=G","mediaType":"text/html"}],"identifier":"DOT-305","issued":"2011-01-18","keyword":["data.gov","law","significant guidance","transportation"],"landingPage":"https://data.transportation.gov/d/x8z7-jjwa","language":["en-US"],"license":"https://project-open-data.cio.gov/unknown-license/","modified":"2026-09-03","phone":"202-493-0215","programCode":["021:000"],"publisher":{"@type":"org:Organization","name":"Federal Motor Carrier Safety Administration"},"references":["http://www.fmcsa.dot.gov/rules-regulations/administration/fmcsr/fmcsrguide.aspx%3Fsection_type=G"],"temporal":"2007-01-01/2011-01-18","theme":["Transportation"],"title":"Significant Guidance Issued by the Federal Motor Carrier Safety Administration"},"description":"A list of Significant Guidance documents, which include guidance document disseminated to regulated entities or the general public that may reasonably be anticipated to lead to an annual effect on the economy of $100 million or more or adversely affect in a material way the economy, a sector of the economy, productivity, competition, jobs, the environment, public health or safety, or State, local, or tribal governments or communities; create a serious inconsistency or otherwise interfere with an action taken or planned by another agency; materially alter the budgetary impact of entitlements, grants, user fees, or loan programs or the rights and obligations of recipients thereof; or raise novel legal or policy issues arising out of legal mandates, the President's priorities, or the principles set forth in Executive Order 12866, as further amended.","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/c0efaf3a-b166-4131-85ee-d2582890f0ca","harvest_record_raw":"https://catalog.data.gov/harvest_record/c0efaf3a-b166-4131-85ee-d2582890f0ca/raw","has_download":true,"has_spatial":false,"identifier":"DOT-305","keyword":["data.gov","law","significant guidance","transportation"],"last_harvested_date":"2026-09-03T18:37:24.438121","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"c549d5ce-2b93-4397-ab76-aa2b31d9983a","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/dot.png","name":"Department of Transportation","organization_type":"Federal Government","slug":"dot"},"parent_identifier":null,"popularity":1,"publisher":"Federal Motor Carrier Safety Administration","slug":"significant-guidance-issued-by-the-federal-motor-carrier-safety-administration-3f75a","spatial_centroid":null,"spatial_shape":null,"theme":["Transportation"],"title":"Significant Guidance Issued by the Federal Motor Carrier Safety Administration","type":"dataset"},{"_score":6.8461018,"_sort":[1788460622493,6.8461018,14,"dc706379-af1f-4eb8-bc37-2e324d989751"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["021:15"],"contactPoint":{"@type":"vcard:Contact","fn":"Hyungjun Park","hasEmail":"mailto:hyungjun.park@dot.gov"},"description":"The main dataset is a 9 MB file of trajectory data (I294_L2_final.csv) that contains position, speed, and acceleration data for small and large automated (L2) and non-automated vehicles on a highway in a suburban environment. Supporting files include aerial reference images for twelve distinct data collection \u201cRuns\u201d (I294_L2_Run_X_ref_image_with_lanes.png, where X equals 5, 28, 30, 36, 38, and 42 for southbound runs and 23, 29, 31, 33, 35, and 41 for northbound runs). Associated centerline files are also provided for each \u201cRun\u201d (I-294-L2-Run_X-geometry-with-ramps.csv). In each centerline file, x and y coordinates (in meters) marking each lane centerline are provided. The origin point of the reference image is located at the top left corner. Additionally, in each centerline file, an indicator variable is used for each lane to define the following types of road sections: 0=no ramp, 1=on-ramps, 2=off-ramps, and 3=weaving segments. The number attached to each column header is the numerical ID assigned for the specific lane (see \u201cTGSIM \u2013 Centerline Data Dictionary \u2013 I294 L2.csv\u201d for more details).  The dataset defines eight lanes (four lanes in each direction) using these centerline files. Images that map the lanes of interest to the numerical lane IDs referenced in the trajectory dataset are stored in the folder titled \u201cAnnotation on Regions.zip\u201d. The southbound lanes are shown visually in I294_L2_lane-2.png through I294_L2_lane-5.png and the northbound lanes are shown visually in I294_L2_lane2.png through I294_L2_lane5.png.\n\nThis dataset was collected as part of the Third Generation Simulation Data (TGSIM): A Closer Look at the Impacts of Automated Driving Systems on Human Behavior project. During the project, six trajectory datasets capable of characterizing human-automated vehicle interactions under a diverse set of scenarios in highway and city environments were collected and processed. For more information, see the project report found here: https://rosap.ntl.bts.gov/view/dot/74647. This dataset, which is one of the six collected as part of the TGSIM project, contains data collected using one high-resolution 8K camera mounted on a helicopter that followed two SAE Level 2 ADAS-equipped vehicles through automated lane change maneuvers and as part of a string once the desired lane was achieved and ACC was enabled. The helicopter then followed the string of vehicles (which sometimes broke from the sting due to large following distances) northbound through the 4.8 km section of highway at an altitude of 300 meters. The goal of the data collection effort was to collect data related to human drivers' responses to automated lane changes and as part of a string. The road segment has four lanes in each direction and covers a major on-ramp and one off-ramp in the southbound direction and one on-ramp as well as two off-ramps in the northbound direction. The segment of highway is operated by Illinois Tollway and contains a high percentage of heavy vehicles. The camera captured footage during the evening rush hour (3:00 PM-5:00 PM CT) on a cloudy day.\n\nAs part of this dataset, the following files were provided:\n<ul><li>I294_L2_final.csv contains the numerical data to be used for analysis that includes vehicle level trajectory data at every 0.1 second. Vehicle size (small or large), width, length, and whether the vehicle was one of the L2 test vehicles (\"yes\" or \"no\") are provided with instantaneous location, speed, and acceleration data. All distance measurements (width, length, location) were converted from pixels to meters using the following conversion factor: 1 pixel = 0.3-meter conversion.</li>\n<li>I294_L2_Run_X_ref_image_with_lanes.png are the aerial reference images that define the geographic region and associated roadway segments of interest (see bounding boxes on northbound and southbound lanes) for each run X.</li>\n<li>I294_L2_Run_X-geometry-with-ramps.csv contain the coordinates that define the lane centerlines for each Run X. T","distribution":[{"@type":"dcat:Distribution","describedBy":"https://data.transportation.gov/api/views/tpsq-zrwa/columns.json","describedByType":"application/json","downloadURL":"https://data.transportation.gov/api/v3/views/tpsq-zrwa/query.json?accessType=DOWNLOAD","mediaType":"application/json"},{"@type":"dcat:Distribution","describedBy":"https://data.transportation.gov/api/views/tpsq-zrwa/columns.xml","describedByType":"application/xml","downloadURL":"https://data.transportation.gov/api/v3/views/tpsq-zrwa/query.xml?accessType=DOWNLOAD","mediaType":"application/xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.transportation.gov/api/v3/views/tpsq-zrwa/export.csv?accessType=DOWNLOAD","mediaType":"text/csv"}],"identifier":"https://data.transportation.gov/api/views/tpsq-zrwa","issued":"2024-11-04","keyword":["aerial videography","automated vehicles","category: vehicle safety","human-automated vehicle interactions","infrastructure-based videography","intelligent transportation systems (its)","its joint program office (jpo)","multi-modal trajectories","subcategory: autonomous vehicle safety systems","tgsim","third generation simulation","vehicle trajectory data"],"landingPage":"https://data.transportation.gov/d/tpsq-zrwa","license":"http://www.usa.gov/publicdomain/label/1.0/","modified":"2026-09-03","programCode":["021:042"],"publisher":{"@type":"org:Organization","name":"Federal Highway Administration"},"spatial":"I-90/I94 in Chicago, IL; I-294 near Hinsdale, IL; I-395 in Washington DC; George Washington University Campus, Washington DC (Foggy Bottom)","theme":["Automobiles"],"title":"Third Generation Simulation Data (TGSIM) I-294 L2 Trajectories"},"description":"The main dataset is a 9 MB file of trajectory data (I294_L2_final.csv) that contains position, speed, and acceleration data for small and large automated (L2) and non-automated vehicles on a highway in a suburban environment. Supporting files include aerial reference images for twelve distinct data collection \u201cRuns\u201d (I294_L2_Run_X_ref_image_with_lanes.png, where X equals 5, 28, 30, 36, 38, and 42 for southbound runs and 23, 29, 31, 33, 35, and 41 for northbound runs). Associated centerline files are also provided for each \u201cRun\u201d (I-294-L2-Run_X-geometry-with-ramps.csv). In each centerline file, x and y coordinates (in meters) marking each lane centerline are provided. The origin point of the reference image is located at the top left corner. Additionally, in each centerline file, an indicator variable is used for each lane to define the following types of road sections: 0=no ramp, 1=on-ramps, 2=off-ramps, and 3=weaving segments. The number attached to each column header is the numerical ID assigned for the specific lane (see \u201cTGSIM \u2013 Centerline Data Dictionary \u2013 I294 L2.csv\u201d for more details).  The dataset defines eight lanes (four lanes in each direction) using these centerline files. Images that map the lanes of interest to the numerical lane IDs referenced in the trajectory dataset are stored in the folder titled \u201cAnnotation on Regions.zip\u201d. The southbound lanes are shown visually in I294_L2_lane-2.png through I294_L2_lane-5.png and the northbound lanes are shown visually in I294_L2_lane2.png through I294_L2_lane5.png.\n\nThis dataset was collected as part of the Third Generation Simulation Data (TGSIM): A Closer Look at the Impacts of Automated Driving Systems on Human Behavior project. During the project, six trajectory datasets capable of characterizing human-automated vehicle interactions under a diverse set of scenarios in highway and city environments were collected and processed. For more information, see the project report found here: https://rosap.ntl.bts.gov/view/dot/74647. This dataset, which is one of the six collected as part of the TGSIM project, contains data collected using one high-resolution 8K camera mounted on a helicopter that followed two SAE Level 2 ADAS-equipped vehicles through automated lane change maneuvers and as part of a string once the desired lane was achieved and ACC was enabled. The helicopter then followed the string of vehicles (which sometimes broke from the sting due to large following distances) northbound through the 4.8 km section of highway at an altitude of 300 meters. The goal of the data collection effort was to collect data related to human drivers' responses to automated lane changes and as part of a string. The road segment has four lanes in each direction and covers a major on-ramp and one off-ramp in the southbound direction and one on-ramp as well as two off-ramps in the northbound direction. The segment of highway is operated by Illinois Tollway and contains a high percentage of heavy vehicles. The camera captured footage during the evening rush hour (3:00 PM-5:00 PM CT) on a cloudy day.\n\nAs part of this dataset, the following files were provided:\n<ul><li>I294_L2_final.csv contains the numerical data to be used for analysis that includes vehicle level trajectory data at every 0.1 second. Vehicle size (small or large), width, length, and whether the vehicle was one of the L2 test vehicles (\"yes\" or \"no\") are provided with instantaneous location, speed, and acceleration data. All distance measurements (width, length, location) were converted from pixels to meters using the following conversion factor: 1 pixel = 0.3-meter conversion.</li>\n<li>I294_L2_Run_X_ref_image_with_lanes.png are the aerial reference images that define the geographic region and associated roadway segments of interest (see bounding boxes on northbound and southbound lanes) for each run X.</li>\n<li>I294_L2_Run_X-geometry-with-ramps.csv contain the coordinates that define the lane centerlines for each Run X. T","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/874f0009-0c88-4d6f-8848-23e165a8328c","harvest_record_raw":"https://catalog.data.gov/harvest_record/874f0009-0c88-4d6f-8848-23e165a8328c/raw","has_download":true,"has_spatial":true,"identifier":"https://data.transportation.gov/api/views/tpsq-zrwa","keyword":["aerial videography","automated vehicles","category: vehicle safety","human-automated vehicle interactions","infrastructure-based videography","intelligent transportation systems (its)","its joint program office (jpo)","multi-modal trajectories","subcategory: autonomous vehicle safety systems","tgsim","third generation simulation","vehicle trajectory data"],"last_harvested_date":"2026-09-03T18:37:02.493892","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"c549d5ce-2b93-4397-ab76-aa2b31d9983a","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/dot.png","name":"Department of Transportation","organization_type":"Federal Government","slug":"dot"},"parent_identifier":null,"popularity":14,"publisher":"Federal Highway Administration","slug":"third-generation-simulation-data-tgsim-i-294-l2-trajectories","spatial_centroid":null,"spatial_shape":null,"theme":["Automobiles"],"title":"Third Generation Simulation Data (TGSIM) I-294 L2 Trajectories","type":"dataset"},{"_score":8.761225,"_sort":[1788460615274,8.761225,2,"ba92701d-9614-4a1b-976d-992b1f3b36ac"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","accrualPeriodicity":"irregular","agencyDataSeriesURL":"http://www.ops.fhwa.dot.gov/freight/freight_analysis/faf/","agencyProgramURL":"http://www.ops.fhwa.dot.gov/freight/freight_analysis/faf/","analysisUnit":"Region","bureauCode":["021:15"],"categoryDesignation":"Research","collectionInstrument":"Forecast developed using commodity flow survey","contactPoint":{"@type":"vcard:Contact","fn":"Office of Freight Management and Operations","hasEmail":"mailto:FreightFeedback@dot.gov"},"dataQuality":true,"describedBy":"https://faf.ornl.gov/faf6/data/FAF6%20User%20Guide.pdf","describedByType":"application/pdf","description":"The Freight Analysis Framework (FAF) integrates data from a variety of sources to create a comprehensive picture of freight movement among states and major metropolitan areas by all modes of transportation. With data from the 2007 Commodity Flow Survey and additional sources, FAF version 3 (FAF3) provides estimates for tonnage, value, and domestic ton-miles by region of origin and destination, commodity type, and mode for 2007, the most recent year, and forecasts through 2040. Also included are state-to-state flows for these years plus 1997 and 2002, summary statistics, and flows by truck assigned to the highway network for 2007 and 2040.","distribution":[{"@type":"dcat:Distribution","downloadURL":"https://faf.ornl.gov/faf6/data/FAF6.zip","mediaType":"application/zip","title":"Regions Boundary Layer"}],"identifier":"286.2","isPartOf":"DOT-286","issued":"2013-03-20","keyword":["commodity","consumption","domestic","economic activity","energy","environment","export","exposure","flow","forecast","freight","import","infrastructure","risk","safety","ton-miles","tons","transportation","trend","trucks","value","wear"],"landingPage":"https://www.bts.gov/faf","language":["en-US"],"license":"https://www.usa.gov/government-works","modified":"2026-09-03","phone":"202-366-6993","primaryITInvestmentUII":"021-844694854","programCode":["021:009"],"publisher":{"@type":"org:Organization","name":"Federal Highway Administration"},"spatial":"Region. Domestic regions are defined here: http://www.ops.fhwa.dot.gov/freight/freight_analysis/faf/faf3/userguide/index.htm#t3 and foreign regions are defined here: http://www.ops.fhwa.dot.gov/freight/freight_analysis/faf/faf3/userguide/index.htm#t4","temporal":"2007-01-01/2040-12-31","theme":["Transportation"],"title":"Freight Analysis Framework - Regions Boundary Layer"},"description":"The Freight Analysis Framework (FAF) integrates data from a variety of sources to create a comprehensive picture of freight movement among states and major metropolitan areas by all modes of transportation. With data from the 2007 Commodity Flow Survey and additional sources, FAF version 3 (FAF3) provides estimates for tonnage, value, and domestic ton-miles by region of origin and destination, commodity type, and mode for 2007, the most recent year, and forecasts through 2040. Also included are state-to-state flows for these years plus 1997 and 2002, summary statistics, and flows by truck assigned to the highway network for 2007 and 2040.","distribution_titles":["Regions Boundary Layer"],"harvest_record":"https://catalog.data.gov/harvest_record/44a28704-6024-4d96-8185-872f7c2bfa82","harvest_record_raw":"https://catalog.data.gov/harvest_record/44a28704-6024-4d96-8185-872f7c2bfa82/raw","has_download":true,"has_spatial":true,"identifier":"286.2","keyword":["commodity","consumption","domestic","economic activity","energy","environment","export","exposure","flow","forecast","freight","import","infrastructure","risk","safety","ton-miles","tons","transportation","trend","trucks","value","wear"],"last_harvested_date":"2026-09-03T18:36:55.274465","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"c549d5ce-2b93-4397-ab76-aa2b31d9983a","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/dot.png","name":"Department of Transportation","organization_type":"Federal Government","slug":"dot"},"parent_identifier":"DOT-286","popularity":2,"publisher":"Federal Highway Administration","slug":"freight-analysis-framework-regions-boundary-layer","spatial_centroid":null,"spatial_shape":null,"theme":["Transportation"],"title":"Freight Analysis Framework - Regions Boundary Layer","type":"dataset"},{"_score":19.737812,"_sort":[1788460613765,19.737812,5,"7355d0b0-5009-4ce9-b071-15f37c891191"],"dcat":{"@type":"dcat:Dataset","accessLevel":"non-public","accrualPeriodicity":"R/PT1S","bureauCode":["021:18"],"categoryDesignation":"Research","collectionInstrument":"Transportation","contactPoint":{"@type":"vcard:Contact","fn":"NHTSA-Datahub","hasEmail":"mailto:NHTSA-Datahub@dot.gov"},"dataQuality":false,"description":"Artemis provides an efficient means to identify serious safety defects early in the vehicle equipment and component production cycle and influences safety recalls promoting a safer environment for drivers and passengers across the nation. Artemis consists of the overall datasets that are defaulted to supported non-public internal use.","distribution":[{"@type":"dcat:Distribution","downloadURL":"https://www.transportation.gov/mission/data-inventory-not-available","mediaType":"text/html"}],"identifier":"26.0","issued":"2018-12-17","keyword":["complaints","compliance","defects","investigations","recalls","regulations","safety"],"landingPage":"https://data.transportation.gov/d/s4at-4na4","language":["en-US"],"license":"https://project-open-data.cio.gov/unknown-license/","modified":"2026-09-03","phone":"202-366-0154","primaryITInvestmentUII":"021-777552743","programCode":["021:031"],"publisher":{"@type":"org:Organization","name":"National Highway Traffic Safety Administration"},"rights":"Public subsets of information contained in these systems is provided through other NHTSA systems and interfaces.","theme":["Transportation"],"title":"Artemis-Vehicles Information System -"},"description":"Artemis provides an efficient means to identify serious safety defects early in the vehicle equipment and component production cycle and influences safety recalls promoting a safer environment for drivers and passengers across the nation. Artemis consists of the overall datasets that are defaulted to supported non-public internal use.","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/5a08a539-d3a3-41cf-9691-f011381dc482","harvest_record_raw":"https://catalog.data.gov/harvest_record/5a08a539-d3a3-41cf-9691-f011381dc482/raw","has_download":true,"has_spatial":false,"identifier":"26.0","keyword":["complaints","compliance","defects","investigations","recalls","regulations","safety"],"last_harvested_date":"2026-09-03T18:36:53.765639","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"c549d5ce-2b93-4397-ab76-aa2b31d9983a","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/dot.png","name":"Department of Transportation","organization_type":"Federal Government","slug":"dot"},"parent_identifier":null,"popularity":5,"publisher":"National Highway Traffic Safety Administration","slug":"artemis-vehicles-information-system","spatial_centroid":null,"spatial_shape":null,"theme":["Transportation"],"title":"Artemis-Vehicles Information System -","type":"dataset"},{"_score":15.92443,"_sort":[1788460611290,15.92443,2,"1da1f199-1afa-4d55-94d6-88f20df8215f"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","accrualPeriodicity":"irregular","agencyDataSeriesURL":"http://regs.dot.gov/OSTsignificantguiddocs.htm","agencyProgramURL":"http://regs.dot.gov/","analysisUnit":"Regulations","bureauCode":["021:04"],"categoryDesignation":"Other","collectionInstrument":"Transportation","contactPoint":{"@type":"vcard:Contact","fn":"DOT Socrata","hasEmail":"mailto:Socrata@dot.gov"},"dataQuality":true,"description":"A list of Significant Guidance documents, which include guidance document disseminated to regulated entities or the general public that may reasonably be anticipated to lead to an annual effect on the economy of $100 million or more or adversely affect in a material way the economy, a sector of the economy, productivity, competition, jobs, the environment, public health or safety, or State, local, or tribal governments or communities; create a serious inconsistency or otherwise interfere with an action taken or planned by another agency; materially alter the budgetary impact of entitlements, grants, user fees, or loan programs or the rights and obligations of recipients thereof; or raise novel legal or policy issues arising out of legal mandates, the President's priorities, or the principles set forth in Executive Order 12866, as further amended.","distribution":[{"@type":"dcat:Distribution","downloadURL":"http://regs.dot.gov/OSTsignificantguiddocs.htm","mediaType":"text/html"}],"identifier":"276.1","isPartOf":"DOT-276","issued":"2011-01-18","keyword":["data.gov","law","significant guidance","transportation"],"landingPage":"https://data.transportation.gov/d/rvyy-fhds","language":["en-US"],"license":"http://www.usa.gov/publicdomain/label/1.0/","modified":"2026-09-03","phone":"202-366-4308","programCode":["021:000"],"publisher":{"@type":"org:Organization","name":"Office of the Secretary of Transportation"},"references":["http://regs.dot.gov/"],"spatial":"N/A","temporal":"1995-01-01/2013-12-31","theme":["Transportation"],"title":"Significant Guidance Issued by the Office of the Secretary of Transportation -"},"description":"A list of Significant Guidance documents, which include guidance document disseminated to regulated entities or the general public that may reasonably be anticipated to lead to an annual effect on the economy of $100 million or more or adversely affect in a material way the economy, a sector of the economy, productivity, competition, jobs, the environment, public health or safety, or State, local, or tribal governments or communities; create a serious inconsistency or otherwise interfere with an action taken or planned by another agency; materially alter the budgetary impact of entitlements, grants, user fees, or loan programs or the rights and obligations of recipients thereof; or raise novel legal or policy issues arising out of legal mandates, the President's priorities, or the principles set forth in Executive Order 12866, as further amended.","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/b41f4128-8bb2-461c-aa55-3955bdb8c802","harvest_record_raw":"https://catalog.data.gov/harvest_record/b41f4128-8bb2-461c-aa55-3955bdb8c802/raw","has_download":true,"has_spatial":true,"identifier":"276.1","keyword":["data.gov","law","significant guidance","transportation"],"last_harvested_date":"2026-09-03T18:36:51.290079","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"c549d5ce-2b93-4397-ab76-aa2b31d9983a","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/dot.png","name":"Department of Transportation","organization_type":"Federal Government","slug":"dot"},"parent_identifier":"DOT-276","popularity":2,"publisher":"Office of the Secretary of Transportation","slug":"significant-guidance-issued-by-the-office-of-the-secretary-of-transportation-883bc","spatial_centroid":null,"spatial_shape":null,"theme":["Transportation"],"title":"Significant Guidance Issued by the Office of the Secretary of Transportation -","type":"dataset"},{"_score":17.526241,"_sort":[1788460597737,17.526241,2,"8ac980dd-6e1b-4875-bebf-5cf40f638818"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["021:15"],"contactPoint":{"@type":"vcard:Contact","fn":"Elina.Zlotchenko","hasEmail":"mailto:Elina.Zlotchenko@dot.gov"},"description":"This dataset contains V2X data collected from the Utah Connected Vehicle Data Ecosystem Program. We have submitted 7 days of Signal Status Message (SSM) in J2735 standards from 3 intersections in Orem, UT. This includes: (1) vehicles equipped with OBUs (Onboard Units) for real-time V2X (Vehicle-to-Everything) data transmission and reception, (2) road-side units (RSUs) capable of capturing, transmitting, and processing data from the transportation environment, and (3) a secure, scalable cloud platform for aggregating, analyzing, and visualizing transportation data.","distribution":[{"@type":"dcat:Distribution","describedBy":"https://data.transportation.gov/api/views/psyb-ymuy/columns.json","describedByType":"application/json","downloadURL":"https://data.transportation.gov/api/v3/views/psyb-ymuy/query.json?accessType=DOWNLOAD","mediaType":"application/json"},{"@type":"dcat:Distribution","describedBy":"https://data.transportation.gov/api/views/psyb-ymuy/columns.xml","describedByType":"application/xml","downloadURL":"https://data.transportation.gov/api/v3/views/psyb-ymuy/query.xml?accessType=DOWNLOAD","mediaType":"application/xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.transportation.gov/api/v3/views/psyb-ymuy/export.csv?accessType=DOWNLOAD","mediaType":"text/csv"}],"identifier":"https://data.transportation.gov/api/views/psyb-ymuy","issued":"2025-07-07","keyword":["basic safety message (bsm)","connected vehicle data","intelligent transportation systems (its)","its joint program office (jpo)","signal phase and timing (spat)","transit signal priority (tsp)"],"landingPage":"https://data.transportation.gov/d/psyb-ymuy","license":"http://www.usa.gov/publicdomain/label/1.0/","modified":"2026-09-03","programCode":["021:042"],"publisher":{"@type":"org:Organization","name":"US Department of Transportation"},"theme":["Transit"],"title":"SSM from UDOT and Panasonic Connected Vehicle Data Ecosystem Program"},"description":"This dataset contains V2X data collected from the Utah Connected Vehicle Data Ecosystem Program. We have submitted 7 days of Signal Status Message (SSM) in J2735 standards from 3 intersections in Orem, UT. This includes: (1) vehicles equipped with OBUs (Onboard Units) for real-time V2X (Vehicle-to-Everything) data transmission and reception, (2) road-side units (RSUs) capable of capturing, transmitting, and processing data from the transportation environment, and (3) a secure, scalable cloud platform for aggregating, analyzing, and visualizing transportation data.","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/0759ebc2-ed69-4d71-926f-88c5e5d0d5ca","harvest_record_raw":"https://catalog.data.gov/harvest_record/0759ebc2-ed69-4d71-926f-88c5e5d0d5ca/raw","has_download":true,"has_spatial":false,"identifier":"https://data.transportation.gov/api/views/psyb-ymuy","keyword":["basic safety message (bsm)","connected vehicle data","intelligent transportation systems (its)","its joint program office (jpo)","signal phase and timing (spat)","transit signal priority (tsp)"],"last_harvested_date":"2026-09-03T18:36:37.737144","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"c549d5ce-2b93-4397-ab76-aa2b31d9983a","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/dot.png","name":"Department of Transportation","organization_type":"Federal Government","slug":"dot"},"parent_identifier":null,"popularity":2,"publisher":"US Department of Transportation","slug":"ssm-from-udot-and-panasonic-connected-vehicle-data-ecosystem-program","spatial_centroid":null,"spatial_shape":null,"theme":["Transit"],"title":"SSM from UDOT and Panasonic Connected Vehicle Data Ecosystem Program","type":"dataset"},{"_score":17.258152,"_sort":[1788460593616,17.258152,3,"c2c0010c-e6c9-40c8-ad41-69007fa8cef2"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["021:15"],"contactPoint":{"@type":"vcard:Contact","fn":"Elina Zlotchenko","hasEmail":"mailto:Elina.Zlotchenko@dot.gov"},"description":"This dataset contains V2X data collected from the Utah Connected Vehicle Data Ecosystem Program. We have submitted 7 days of deduplicated Signal Request Messages (SRMs) in J2735 standards from 3 intersections in Orem, UT. This includes: (1) vehicles equipped with OBUs (Onboard Units) for real-time V2X (Vehicle-to-Everything) data transmission and reception, (2) road-side units (RSUs) capable of capturing, transmitting, and processing data from the transportation environment, and (3) a secure, scalable cloud platform for aggregating, analyzing, and visualizing transportation data.","distribution":[{"@type":"dcat:Distribution","describedBy":"https://data.transportation.gov/api/views/p7d5-hrve/columns.json","describedByType":"application/json","downloadURL":"https://data.transportation.gov/api/v3/views/p7d5-hrve/query.json?accessType=DOWNLOAD","mediaType":"application/json"},{"@type":"dcat:Distribution","describedBy":"https://data.transportation.gov/api/views/p7d5-hrve/columns.xml","describedByType":"application/xml","downloadURL":"https://data.transportation.gov/api/v3/views/p7d5-hrve/query.xml?accessType=DOWNLOAD","mediaType":"application/xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.transportation.gov/api/v3/views/p7d5-hrve/export.csv?accessType=DOWNLOAD","mediaType":"text/csv"}],"identifier":"https://data.transportation.gov/api/views/p7d5-hrve","issued":"2025-07-07","keyword":["basic safety message (bsm)","connected vehicle data","intelligent transportation systems (its)","its joint program office (jpo)","signal phase and timing (spat)","transit signal priority (tsp)","vehicle to infrastructure (v2i)"],"landingPage":"https://data.transportation.gov/d/p7d5-hrve","license":"http://www.usa.gov/publicdomain/label/1.0/","modified":"2026-09-03","programCode":["021:042"],"publisher":{"@type":"org:Organization","name":"US Department of Transportation"},"spatial":"Orem, UT","theme":["Transit"],"title":"SRM from UDOT and Panasonic Connected Vehicle Data Ecosystem Program"},"description":"This dataset contains V2X data collected from the Utah Connected Vehicle Data Ecosystem Program. We have submitted 7 days of deduplicated Signal Request Messages (SRMs) in J2735 standards from 3 intersections in Orem, UT. This includes: (1) vehicles equipped with OBUs (Onboard Units) for real-time V2X (Vehicle-to-Everything) data transmission and reception, (2) road-side units (RSUs) capable of capturing, transmitting, and processing data from the transportation environment, and (3) a secure, scalable cloud platform for aggregating, analyzing, and visualizing transportation data.","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/a44d50ec-b4c1-48ad-a6a0-25e0597d1cb5","harvest_record_raw":"https://catalog.data.gov/harvest_record/a44d50ec-b4c1-48ad-a6a0-25e0597d1cb5/raw","has_download":true,"has_spatial":true,"identifier":"https://data.transportation.gov/api/views/p7d5-hrve","keyword":["basic safety message (bsm)","connected vehicle data","intelligent transportation systems (its)","its joint program office (jpo)","signal phase and timing (spat)","transit signal priority (tsp)","vehicle to infrastructure (v2i)"],"last_harvested_date":"2026-09-03T18:36:33.616439","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"c549d5ce-2b93-4397-ab76-aa2b31d9983a","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/dot.png","name":"Department of Transportation","organization_type":"Federal Government","slug":"dot"},"parent_identifier":null,"popularity":3,"publisher":"US Department of Transportation","slug":"srm-from-udot-and-panasonic-connected-vehicle-data-ecosystem-program","spatial_centroid":null,"spatial_shape":null,"theme":["Transit"],"title":"SRM from UDOT and Panasonic Connected Vehicle Data Ecosystem Program","type":"dataset"},{"_score":16.320547,"_sort":[1788460593198,16.320547,2,"823c81b3-d33c-43a0-8fe5-82883a3594d5"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","accrualPeriodicity":"irregular","agencyDataSeriesURL":"http://www.fmcsa.dot.gov/rules-regulations/administration/fmcsr/fmcsrguide.aspx%3Fsection_type=G","agencyProgramURL":"http://www.fmcsa.dot.gov/rules-regulations/administration/fmcsr/fmcsrguide.aspx%3Fsection_type=G","analysisUnit":"Regulations","bureauCode":["021:17"],"categoryDesignation":"Research","collectionInstrument":"Transportation","contactPoint":{"@type":"vcard:Contact","fn":"FMCSA CDO","hasEmail":"mailto:fmcsa.cdo@dot.gov"},"dataQuality":true,"description":"A list of Significant Guidance documents, which include guidance document disseminated to regulated entities or the general public that may reasonably be anticipated to lead to an annual effect on the economy of $100 million or more or adversely affect in a material way the economy, a sector of the economy, productivity, competition, jobs, the environment, public health or safety, or State, local, or tribal governments or communities; create a serious inconsistency or otherwise interfere with an action taken or planned by another agency; materially alter the budgetary impact of entitlements, grants, user fees, or loan programs or the rights and obligations of recipients thereof; or raise novel legal or policy issues arising out of legal mandates, the President's priorities, or the principles set forth in Executive Order 12866, as further amended.","distribution":[{"@type":"dcat:Distribution","downloadURL":"http://www.fmcsa.dot.gov/rules-regulations/administration/fmcsr/fmcsrguide.aspx%3Fsection_type=G","mediaType":"text/html"}],"identifier":"305.2","isPartOf":"DOT-305","issued":"2011-01-18","keyword":["data.gov","law","significant guidance","transportation"],"landingPage":"https://data.transportation.gov/d/p4kt-vnkq","language":["en-US"],"license":"https://project-open-data.cio.gov/unknown-license/","modified":"2026-09-03","phone":"202-493-0215","programCode":["021:000"],"publisher":{"@type":"org:Organization","name":"Federal Motor Carrier Safety Administration"},"references":["http://www.fmcsa.dot.gov/rules-regulations/administration/fmcsr/fmcsrguide.aspx%3Fsection_type=G"],"temporal":"2007-01-01/2011-01-18","theme":["Transportation"],"title":"Significant Guidance Issued by the Federal Motor Carrier Safety Administration -"},"description":"A list of Significant Guidance documents, which include guidance document disseminated to regulated entities or the general public that may reasonably be anticipated to lead to an annual effect on the economy of $100 million or more or adversely affect in a material way the economy, a sector of the economy, productivity, competition, jobs, the environment, public health or safety, or State, local, or tribal governments or communities; create a serious inconsistency or otherwise interfere with an action taken or planned by another agency; materially alter the budgetary impact of entitlements, grants, user fees, or loan programs or the rights and obligations of recipients thereof; or raise novel legal or policy issues arising out of legal mandates, the President's priorities, or the principles set forth in Executive Order 12866, as further amended.","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/ad150bf2-b54e-4efd-b18d-3365df9c2aed","harvest_record_raw":"https://catalog.data.gov/harvest_record/ad150bf2-b54e-4efd-b18d-3365df9c2aed/raw","has_download":true,"has_spatial":false,"identifier":"305.2","keyword":["data.gov","law","significant guidance","transportation"],"last_harvested_date":"2026-09-03T18:36:33.198870","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"c549d5ce-2b93-4397-ab76-aa2b31d9983a","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/dot.png","name":"Department of Transportation","organization_type":"Federal Government","slug":"dot"},"parent_identifier":"DOT-305","popularity":2,"publisher":"Federal Motor Carrier Safety Administration","slug":"significant-guidance-issued-by-the-federal-motor-carrier-safety-administration-f7163","spatial_centroid":null,"spatial_shape":null,"theme":["Transportation"],"title":"Significant Guidance Issued by the Federal Motor Carrier Safety Administration -","type":"dataset"},{"_score":16.25143,"_sort":[1788460587390,16.25143,2,"0fa1b89d-1c90-44b1-88d8-b2379738e8c9"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","accrualPeriodicity":"irregular","agencyDataSeriesURL":"http://regs.dot.gov/OSTsignificantguiddocs.htm","agencyProgramURL":"http://regs.dot.gov/","analysisUnit":"Regulations","bureauCode":["021:04"],"categoryDesignation":"Other","collectionInstrument":"Transportation","contactPoint":{"@type":"vcard:Contact","fn":"DOT Socrata","hasEmail":"mailto:Socrata@dot.gov"},"dataQuality":true,"description":"A list of Significant Guidance documents, which include guidance document disseminated to regulated entities or the general public that may reasonably be anticipated to lead to an annual effect on the economy of $100 million or more or adversely affect in a material way the economy, a sector of the economy, productivity, competition, jobs, the environment, public health or safety, or State, local, or tribal governments or communities; create a serious inconsistency or otherwise interfere with an action taken or planned by another agency; materially alter the budgetary impact of entitlements, grants, user fees, or loan programs or the rights and obligations of recipients thereof; or raise novel legal or policy issues arising out of legal mandates, the President's priorities, or the principles set forth in Executive Order 12866, as further amended.","distribution":[{"@type":"dcat:Distribution","downloadURL":"http://regs.dot.gov/OSTsignificantguiddocs.htm","mediaType":"text/html"}],"identifier":"276.2","isPartOf":"DOT-276","issued":"2011-01-18","keyword":["data.gov","law","significant guidance","transportation"],"landingPage":"https://data.transportation.gov/d/ney2-64e6","language":["en-US"],"license":"http://www.usa.gov/publicdomain/label/1.0/","modified":"2026-09-03","phone":"202-366-4308","programCode":["021:000"],"publisher":{"@type":"org:Organization","name":"Office of the Secretary of Transportation"},"references":["http://regs.dot.gov/"],"spatial":"N/A","temporal":"1995-01-01/2013-12-31","theme":["Transportation"],"title":"Significant Guidance Issued by the Office of the Secretary of Transportation -"},"description":"A list of Significant Guidance documents, which include guidance document disseminated to regulated entities or the general public that may reasonably be anticipated to lead to an annual effect on the economy of $100 million or more or adversely affect in a material way the economy, a sector of the economy, productivity, competition, jobs, the environment, public health or safety, or State, local, or tribal governments or communities; create a serious inconsistency or otherwise interfere with an action taken or planned by another agency; materially alter the budgetary impact of entitlements, grants, user fees, or loan programs or the rights and obligations of recipients thereof; or raise novel legal or policy issues arising out of legal mandates, the President's priorities, or the principles set forth in Executive Order 12866, as further amended.","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/58db230c-7251-4b37-80c6-5c69db2c7fc2","harvest_record_raw":"https://catalog.data.gov/harvest_record/58db230c-7251-4b37-80c6-5c69db2c7fc2/raw","has_download":true,"has_spatial":true,"identifier":"276.2","keyword":["data.gov","law","significant guidance","transportation"],"last_harvested_date":"2026-09-03T18:36:27.390775","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"c549d5ce-2b93-4397-ab76-aa2b31d9983a","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/dot.png","name":"Department of Transportation","organization_type":"Federal Government","slug":"dot"},"parent_identifier":"DOT-276","popularity":2,"publisher":"Office of the Secretary of Transportation","slug":"significant-guidance-issued-by-the-office-of-the-secretary-of-transportation-d9f4a","spatial_centroid":null,"spatial_shape":null,"theme":["Transportation"],"title":"Significant Guidance Issued by the Office of the Secretary of Transportation -","type":"dataset"},{"_score":16.320547,"_sort":[1788460586963,16.320547,1,"e5ff2b70-bc3e-4502-abbc-23c403b9eef4"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","accrualPeriodicity":"R/P1Y","agencyDataSeriesURL":"http://www.nhtsa.gov/Laws+&+Regulations/Guidance+Documents","agencyProgramURL":"http://www.nhtsa.gov/Laws+&+Regulations/Guidance+Documents","analysisUnit":"Regulations","bureauCode":["021:18"],"categoryDesignation":"Research","collectionInstrument":"Transportation","contactPoint":{"@type":"vcard:Contact","fn":"NHTSA-Datahub","hasEmail":"mailto:NHTSA-Datahub@dot.gov"},"dataQuality":true,"description":"A list of Significant Guidance documents, which include guidance document disseminated to regulated entities or the general public that may reasonably be anticipated to lead to an annual effect on the economy of $100 million or more or adversely affect in a material way the economy, a sector of the economy, productivity, competition, jobs, the environment, public health or safety, or State, local, or tribal governments or communities; create a serious inconsistency or otherwise interfere with an action taken or planned by another agency; materially alter the budgetary impact of entitlements, grants, user fees, or loan programs or the rights and obligations of recipients thereof; or raise novel legal or policy issues arising out of legal mandates, the President's priorities, or the principles set forth in Executive Order 12866, as further amended.","distribution":[{"@type":"dcat:Distribution","downloadURL":"http://www.nhtsa.gov/Laws+&+Regulations/Guidance+Documents","mediaType":"text/html"}],"identifier":"319.1","isPartOf":"DOT-319","issued":"2011-01-18","keyword":["data.gov","law","significant guidance","transportation"],"landingPage":"https://data.transportation.gov/d/ndu9-g4hs","language":["en-US"],"license":"https://project-open-data.cio.gov/unknown-license/","modified":"2026-09-03","phone":"202-366-4308","programCode":["021:000"],"publisher":{"@type":"org:Organization","name":"National Highway Traffic Safety Administration"},"references":["http://www.nhtsa.gov/Laws+&+Regulations/Guidance+Documents"],"temporal":"R/2006-01-01/P1Y","theme":["Transportation"],"title":"Significant Guidance Issued by the National Highway Traffic Safety Administration -"},"description":"A list of Significant Guidance documents, which include guidance document disseminated to regulated entities or the general public that may reasonably be anticipated to lead to an annual effect on the economy of $100 million or more or adversely affect in a material way the economy, a sector of the economy, productivity, competition, jobs, the environment, public health or safety, or State, local, or tribal governments or communities; create a serious inconsistency or otherwise interfere with an action taken or planned by another agency; materially alter the budgetary impact of entitlements, grants, user fees, or loan programs or the rights and obligations of recipients thereof; or raise novel legal or policy issues arising out of legal mandates, the President's priorities, or the principles set forth in Executive Order 12866, as further amended.","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/528791b9-92dc-453c-b9ba-b6d0a2277a36","harvest_record_raw":"https://catalog.data.gov/harvest_record/528791b9-92dc-453c-b9ba-b6d0a2277a36/raw","has_download":true,"has_spatial":false,"identifier":"319.1","keyword":["data.gov","law","significant guidance","transportation"],"last_harvested_date":"2026-09-03T18:36:26.963386","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"c549d5ce-2b93-4397-ab76-aa2b31d9983a","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/dot.png","name":"Department of Transportation","organization_type":"Federal Government","slug":"dot"},"parent_identifier":"DOT-319","popularity":1,"publisher":"National Highway Traffic Safety Administration","slug":"significant-guidance-issued-by-the-national-highway-traffic-safety-administration-6f740","spatial_centroid":null,"spatial_shape":null,"theme":["Transportation"],"title":"Significant Guidance Issued by the National Highway Traffic Safety Administration -","type":"dataset"},{"_score":16.320547,"_sort":[1788460581366,16.320547,0,"d47f351b-f602-4258-9491-6d9413e1f5c3"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","accrualPeriodicity":"R/P1Y","agencyDataSeriesURL":"http://www.nhtsa.gov/Laws+&+Regulations/Guidance+Documents","agencyProgramURL":"http://www.nhtsa.gov/Laws+&+Regulations/Guidance+Documents","analysisUnit":"Regulations","bureauCode":["021:18"],"categoryDesignation":"Research","collectionInstrument":"Transportation","contactPoint":{"@type":"vcard:Contact","fn":"NHTSA-Datahub","hasEmail":"mailto:NHTSA-Datahub@dot.gov"},"dataQuality":true,"description":"A list of Significant Guidance documents, which include guidance document disseminated to regulated entities or the general public that may reasonably be anticipated to lead to an annual effect on the economy of $100 million or more or adversely affect in a material way the economy, a sector of the economy, productivity, competition, jobs, the environment, public health or safety, or State, local, or tribal governments or communities; create a serious inconsistency or otherwise interfere with an action taken or planned by another agency; materially alter the budgetary impact of entitlements, grants, user fees, or loan programs or the rights and obligations of recipients thereof; or raise novel legal or policy issues arising out of legal mandates, the President's priorities, or the principles set forth in Executive Order 12866, as further amended.","distribution":[{"@type":"dcat:Distribution","downloadURL":"http://www.nhtsa.gov/Laws+&+Regulations/Guidance+Documents","mediaType":"text/html"}],"identifier":"DOT-319","issued":"2011-01-18","keyword":["data.gov","law","significant guidance","transportation"],"landingPage":"https://data.transportation.gov/d/mc7k-mvnn","language":["en-US"],"license":"https://project-open-data.cio.gov/unknown-license/","modified":"2026-09-03","phone":"202-366-4308","programCode":["021:000"],"publisher":{"@type":"org:Organization","name":"National Highway Traffic Safety Administration"},"references":["http://www.nhtsa.gov/Laws+&+Regulations/Guidance+Documents"],"temporal":"R/2006-01-01/P1Y","theme":["Transportation"],"title":"Significant Guidance Issued by the National Highway Traffic Safety Administration"},"description":"A list of Significant Guidance documents, which include guidance document disseminated to regulated entities or the general public that may reasonably be anticipated to lead to an annual effect on the economy of $100 million or more or adversely affect in a material way the economy, a sector of the economy, productivity, competition, jobs, the environment, public health or safety, or State, local, or tribal governments or communities; create a serious inconsistency or otherwise interfere with an action taken or planned by another agency; materially alter the budgetary impact of entitlements, grants, user fees, or loan programs or the rights and obligations of recipients thereof; or raise novel legal or policy issues arising out of legal mandates, the President's priorities, or the principles set forth in Executive Order 12866, as further amended.","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/e1cb50f0-6edf-43bb-9f18-f219832a6be9","harvest_record_raw":"https://catalog.data.gov/harvest_record/e1cb50f0-6edf-43bb-9f18-f219832a6be9/raw","has_download":true,"has_spatial":false,"identifier":"DOT-319","keyword":["data.gov","law","significant guidance","transportation"],"last_harvested_date":"2026-09-03T18:36:21.366757","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"c549d5ce-2b93-4397-ab76-aa2b31d9983a","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/dot.png","name":"Department of Transportation","organization_type":"Federal Government","slug":"dot"},"parent_identifier":null,"popularity":0,"publisher":"National Highway Traffic Safety Administration","slug":"significant-guidance-issued-by-the-national-highway-traffic-safety-administration","spatial_centroid":null,"spatial_shape":null,"theme":["Transportation"],"title":"Significant Guidance Issued by the National Highway Traffic Safety Administration","type":"dataset"},{"_score":7.4724655,"_sort":[1788460581027,7.4724655,2,"b778c38d-30a3-4967-bf16-0b45ae5d60ee"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["021:15"],"contactPoint":{"@type":"vcard:Contact","fn":"Elina Zlotchenko","hasEmail":"mailto:elina.zlotchenko@dot.gov"},"description":"Test case WFCW-1 Results - FCW Stopped Vehicle Rep 2","distribution":[{"@type":"dcat:Distribution","describedBy":"https://data.transportation.gov/api/views/manf-4hb6/columns.json","describedByType":"application/json","downloadURL":"https://data.transportation.gov/api/v3/views/manf-4hb6/query.json?accessType=DOWNLOAD","mediaType":"application/json"},{"@type":"dcat:Distribution","describedBy":"https://data.transportation.gov/api/views/manf-4hb6/columns.xml","describedByType":"application/xml","downloadURL":"https://data.transportation.gov/api/v3/views/manf-4hb6/query.xml?accessType=DOWNLOAD","mediaType":"application/xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.transportation.gov/api/v3/views/manf-4hb6/export.csv?accessType=DOWNLOAD","mediaType":"text/csv"},{"@type":"dcat:Distribution","downloadURL":"https://data.transportation.gov/api/v3/views/manf-4hb6/export.kml?accessType=DOWNLOAD","mediaType":"application/vnd.google-earth.kml+xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.transportation.gov/api/v3/views/manf-4hb6/export.kmz?accessType=DOWNLOAD","mediaType":"application/vnd.google-earth.kmz"},{"@type":"dcat:Distribution","downloadURL":"https://data.transportation.gov/api/v3/views/manf-4hb6/query.geojson?accessType=DOWNLOAD","mediaType":"application/geo+json"}],"identifier":"https://data.transportation.gov/api/views/manf-4hb6","issued":"2024-09-06","keyword":["connected equipment","connected vehicle","connected vehicle data","connected vehicle environment","connected vehicle message","connected vehicles","cvp","intelligent transportation systems (its)","its joint program office (jpo)","on-board equipment","on-board unit","road side unit","roadside equipment","vehicle data","vehicle to infrastructure","vehicle to vehicle"],"landingPage":"https://data.transportation.gov/d/manf-4hb6","license":"http://www.usa.gov/publicdomain/label/1.0/","modified":"2026-09-03","programCode":["021:042"],"publisher":{"@type":"org:Organization","name":"Federal Highway Administration"},"spatial":"Wyoming","theme":["Automobiles"],"title":"LTE-V2X Wyoming Connected Vehicle Pilot test ID WFCW-1 Rep 2"},"description":"Test case WFCW-1 Results - FCW Stopped Vehicle Rep 2","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/4e988e19-e752-4dc6-ae63-916f5bcee951","harvest_record_raw":"https://catalog.data.gov/harvest_record/4e988e19-e752-4dc6-ae63-916f5bcee951/raw","has_download":true,"has_spatial":true,"identifier":"https://data.transportation.gov/api/views/manf-4hb6","keyword":["connected equipment","connected vehicle","connected vehicle data","connected vehicle environment","connected vehicle message","connected vehicles","cvp","intelligent transportation systems (its)","its joint program office (jpo)","on-board equipment","on-board unit","road side unit","roadside equipment","vehicle data","vehicle to infrastructure","vehicle to vehicle"],"last_harvested_date":"2026-09-03T18:36:21.027713","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"c549d5ce-2b93-4397-ab76-aa2b31d9983a","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/dot.png","name":"Department of Transportation","organization_type":"Federal Government","slug":"dot"},"parent_identifier":null,"popularity":2,"publisher":"Federal Highway Administration","slug":"lte-v2x-wyoming-connected-vehicle-pilot-test-id-wfcw-1-rep-2","spatial_centroid":null,"spatial_shape":null,"theme":["Automobiles"],"title":"LTE-V2X Wyoming Connected Vehicle Pilot test ID WFCW-1 Rep 2","type":"dataset"},{"_score":8.2433195,"_sort":[1788460575582,8.2433195,5,"0efed27e-9254-467c-bb23-596a291e754e"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["021:15"],"contactPoint":{"@type":"vcard:Contact","fn":"Elina Zlotchenko","hasEmail":"mailto:Elina.Zlotchenko@dot.gov"},"description":"Part of Wyoming Department of Transportation Connected Vehicle Pilot Phase 4. Verify that OBUs use different LTE-V2X Configuration Profiles based on the vehicle's speed.\nHost and remote vehicles travelling below 120 kmph\nHost and remote vehicles travelling above 120 kmph","distribution":[{"@type":"dcat:Distribution","describedBy":"https://data.transportation.gov/api/views/kaak-2432/columns.json","describedByType":"application/json","downloadURL":"https://data.transportation.gov/api/v3/views/kaak-2432/query.json?accessType=DOWNLOAD","mediaType":"application/json"},{"@type":"dcat:Distribution","describedBy":"https://data.transportation.gov/api/views/kaak-2432/columns.xml","describedByType":"application/xml","downloadURL":"https://data.transportation.gov/api/v3/views/kaak-2432/query.xml?accessType=DOWNLOAD","mediaType":"application/xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.transportation.gov/api/v3/views/kaak-2432/export.csv?accessType=DOWNLOAD","mediaType":"text/csv"},{"@type":"dcat:Distribution","downloadURL":"https://data.transportation.gov/api/v3/views/kaak-2432/export.kml?accessType=DOWNLOAD","mediaType":"application/vnd.google-earth.kml+xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.transportation.gov/api/v3/views/kaak-2432/export.kmz?accessType=DOWNLOAD","mediaType":"application/vnd.google-earth.kmz"},{"@type":"dcat:Distribution","downloadURL":"https://data.transportation.gov/api/v3/views/kaak-2432/query.geojson?accessType=DOWNLOAD","mediaType":"application/geo+json"}],"identifier":"https://data.transportation.gov/api/views/kaak-2432","issued":"2024-07-19","keyword":["connected equipment","connected vehicle","connected vehicle data","connected vehicle environment","connected vehicle message","connected vehicles","on-board equipment","on-board unit","road side unit","roadside equipment","vehicle data","vehicle to infrastructure","vehicle to vehicle"],"landingPage":"https://data.transportation.gov/d/kaak-2432","license":"http://www.usa.gov/publicdomain/label/1.0/","modified":"2026-09-03","programCode":["021:042"],"publisher":{"@type":"org:Organization","name":"Federal Highway Administration"},"spatial":"Wyoming","theme":["Automobiles"],"title":"LTE-V2X Wyoming Connected Vehicle Pilot test ID WV2IMCT-1 Vehicle 2 80 mph"},"description":"Part of Wyoming Department of Transportation Connected Vehicle Pilot Phase 4. Verify that OBUs use different LTE-V2X Configuration Profiles based on the vehicle's speed.\nHost and remote vehicles travelling below 120 kmph\nHost and remote vehicles travelling above 120 kmph","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/d2133946-c54f-46a5-a06f-dbde90e88c2b","harvest_record_raw":"https://catalog.data.gov/harvest_record/d2133946-c54f-46a5-a06f-dbde90e88c2b/raw","has_download":true,"has_spatial":true,"identifier":"https://data.transportation.gov/api/views/kaak-2432","keyword":["connected equipment","connected vehicle","connected vehicle data","connected vehicle environment","connected vehicle message","connected vehicles","on-board equipment","on-board unit","road side unit","roadside equipment","vehicle data","vehicle to infrastructure","vehicle to vehicle"],"last_harvested_date":"2026-09-03T18:36:15.582019","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"c549d5ce-2b93-4397-ab76-aa2b31d9983a","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/dot.png","name":"Department of Transportation","organization_type":"Federal Government","slug":"dot"},"parent_identifier":null,"popularity":5,"publisher":"Federal Highway Administration","slug":"lte-v2x-wyoming-connected-vehicle-pilot-test-id-wv2imct-1-vehicle-2-80-mph","spatial_centroid":null,"spatial_shape":null,"theme":["Automobiles"],"title":"LTE-V2X Wyoming Connected Vehicle Pilot test ID WV2IMCT-1 Vehicle 2 80 mph","type":"dataset"},{"_score":70.053734,"_sort":[1788460570956,70.053734,8,"5eae5790-968e-4749-9fb7-bc455da5d744"],"dcat":{"@type":"dcat:Dataset","accessLevel":"restricted public","accrualPeriodicity":"R/PT1S","agencyDataSeriesURL":"https://wxde.fhwa.dot.gov/","agencyProgramURL":"https://ops.fhwa.dot.gov/weather/index.asp","bureauCode":["021:15"],"categoryDesignation":"Research","collectionInstrument":"Transportation","contactPoint":{"@type":"vcard:Contact","fn":"Office of Transportation Operations","hasEmail":"mailto:david.johnson@dot.gov"},"dataQuality":true,"describedBy":"https://wxde.fhwa.dot.gov/auth2/metadata.jsp","description":"The Weather Data Environment (WxDE) collects and shares transportation-related weather data with a particular focus on weather data related to connected vehicle applications. The WxDE collects data in real time from both fixed environmental sensor stations and mobile sources. The WxDE computes value-added enhancements to this data, such as checking the quality of observed data and inferring weather parameters from vehicle data (e.g., inferring precipitation based on windshield wiper activation). The WxDE archives both collected and computed data. The WxDE supports subscriptions for access to real-time data in near real time generated by individual weather-related connected vehicle projects.","distribution":[{"@type":"dcat:Distribution","downloadURL":"https://wxde.fhwa.dot.gov/#","mediaType":"text/html","title":"Data Description"}],"identifier":"2068.2","isPartOf":"DOT-2068","issued":"2013-01-01","keyword":["clarus","connected vehicle","ess","road weather","rwis","weather","wxde"],"landingPage":"https://wxde.fhwa.dot.gov/","language":["en-US"],"license":"https://www.usa.gov/government-works","modified":"2026-09-03","programCode":["021:011"],"publisher":{"@type":"org:Organization","name":"Federal Highway Administration"},"references":["https://wxde.fhwa.dot.gov/frequentlyAskedQuestions.jsp"],"theme":["Transportation"],"title":"Weather Data Environment"},"description":"The Weather Data Environment (WxDE) collects and shares transportation-related weather data with a particular focus on weather data related to connected vehicle applications. The WxDE collects data in real time from both fixed environmental sensor stations and mobile sources. The WxDE computes value-added enhancements to this data, such as checking the quality of observed data and inferring weather parameters from vehicle data (e.g., inferring precipitation based on windshield wiper activation). The WxDE archives both collected and computed data. The WxDE supports subscriptions for access to real-time data in near real time generated by individual weather-related connected vehicle projects.","distribution_titles":["Data Description"],"harvest_record":"https://catalog.data.gov/harvest_record/6ff4829f-9fe1-49b2-8c26-6bf2b6f850de","harvest_record_raw":"https://catalog.data.gov/harvest_record/6ff4829f-9fe1-49b2-8c26-6bf2b6f850de/raw","has_download":true,"has_spatial":false,"identifier":"2068.2","keyword":["clarus","connected vehicle","ess","road weather","rwis","weather","wxde"],"last_harvested_date":"2026-09-03T18:36:10.956051","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"c549d5ce-2b93-4397-ab76-aa2b31d9983a","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/dot.png","name":"Department of Transportation","organization_type":"Federal Government","slug":"dot"},"parent_identifier":"DOT-2068","popularity":8,"publisher":"Federal Highway Administration","slug":"weather-data-environment-data-catalog","spatial_centroid":null,"spatial_shape":null,"theme":["Transportation"],"title":"Weather Data Environment","type":"dataset"},{"_score":17.648876,"_sort":[1788460565843,17.648876,3,"bf4a0f4e-4f13-49a8-b079-8628a6183f6d"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["021:15"],"contactPoint":{"@type":"vcard:Contact","fn":"Elina Zlotchenko","hasEmail":"mailto:Elina.Zlotchenko@dot.gov"},"description":"This dataset contains V2X data collected from the Utah Connected Vehicle Data Ecosystem Program. We have submitted 7 days of Signal Phase and Timing Messages (SPaT) in J2735 standards from 3 intersections in Orem, UT. This includes: (1) vehicles equipped with OBUs (Onboard Units) for real-time V2X (Vehicle-to-Everything) data transmission and reception, (2) road-side units (RSUs) capable of capturing, transmitting, and processing data from the transportation environment, and (3) a secure, scalable cloud platform for aggregating, analyzing, and visualizing transportation data.","distribution":[{"@type":"dcat:Distribution","describedBy":"https://data.transportation.gov/api/views/iq8k-ytf6/columns.json","describedByType":"application/json","downloadURL":"https://data.transportation.gov/api/v3/views/iq8k-ytf6/query.json?accessType=DOWNLOAD","mediaType":"application/json"},{"@type":"dcat:Distribution","describedBy":"https://data.transportation.gov/api/views/iq8k-ytf6/columns.xml","describedByType":"application/xml","downloadURL":"https://data.transportation.gov/api/v3/views/iq8k-ytf6/query.xml?accessType=DOWNLOAD","mediaType":"application/xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.transportation.gov/api/v3/views/iq8k-ytf6/export.csv?accessType=DOWNLOAD","mediaType":"text/csv"}],"identifier":"https://data.transportation.gov/api/views/iq8k-ytf6","issued":"2025-07-07","keyword":["connected vehicle data","intelligent transportation systems (its)","its joint program office (jpo)","signal phase and timing (spat)","transit signal priority (tsp)","vehicle to infrastructure (v2i)"],"landingPage":"https://data.transportation.gov/d/iq8k-ytf6","license":"http://www.usa.gov/publicdomain/label/1.0/","modified":"2026-09-03","programCode":["021:042"],"publisher":{"@type":"org:Organization","name":"US Department of Transportation"},"theme":["Transit"],"title":"SPaT from UDOT and Panasonic Connected Vehicle Data Ecosystem Program"},"description":"This dataset contains V2X data collected from the Utah Connected Vehicle Data Ecosystem Program. We have submitted 7 days of Signal Phase and Timing Messages (SPaT) in J2735 standards from 3 intersections in Orem, UT. This includes: (1) vehicles equipped with OBUs (Onboard Units) for real-time V2X (Vehicle-to-Everything) data transmission and reception, (2) road-side units (RSUs) capable of capturing, transmitting, and processing data from the transportation environment, and (3) a secure, scalable cloud platform for aggregating, analyzing, and visualizing transportation data.","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/8cb4fd41-6b3e-4796-8fef-098a9af6b8bd","harvest_record_raw":"https://catalog.data.gov/harvest_record/8cb4fd41-6b3e-4796-8fef-098a9af6b8bd/raw","has_download":true,"has_spatial":false,"identifier":"https://data.transportation.gov/api/views/iq8k-ytf6","keyword":["connected vehicle data","intelligent transportation systems (its)","its joint program office (jpo)","signal phase and timing (spat)","transit signal priority (tsp)","vehicle to infrastructure (v2i)"],"last_harvested_date":"2026-09-03T18:36:05.843934","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"c549d5ce-2b93-4397-ab76-aa2b31d9983a","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/dot.png","name":"Department of Transportation","organization_type":"Federal Government","slug":"dot"},"parent_identifier":null,"popularity":3,"publisher":"US Department of Transportation","slug":"spat-from-udot-and-panasonic-connected-vehicle-data-ecosystem-program","spatial_centroid":null,"spatial_shape":null,"theme":["Transit"],"title":"SPaT from UDOT and Panasonic Connected Vehicle Data Ecosystem Program","type":"dataset"},{"_score":8.310768,"_sort":[1788460559767,8.310768,1,"6f213e1f-25db-41c8-8ea9-8bec0e1a354c"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["021:15"],"contactPoint":{"@type":"vcard:Contact","fn":"Elina Zlotchenko","hasEmail":"mailto:Elina.Zlotchenko@dot.gov"},"description":"Part of the Wyoming Department of Transportation Connected Vehicle Pilot Phase 4. Verify that OBUs use different LTE-V2X Configuration Profiles based on the vehicle's speed.\nHost and remote vehicles travelling below 120 kmph\nHost and remote vehicles travelling above 120 kmph","distribution":[{"@type":"dcat:Distribution","describedBy":"https://data.transportation.gov/api/views/hgck-kgan/columns.json","describedByType":"application/json","downloadURL":"https://data.transportation.gov/api/v3/views/hgck-kgan/query.json?accessType=DOWNLOAD","mediaType":"application/json"},{"@type":"dcat:Distribution","describedBy":"https://data.transportation.gov/api/views/hgck-kgan/columns.xml","describedByType":"application/xml","downloadURL":"https://data.transportation.gov/api/v3/views/hgck-kgan/query.xml?accessType=DOWNLOAD","mediaType":"application/xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.transportation.gov/api/v3/views/hgck-kgan/export.csv?accessType=DOWNLOAD","mediaType":"text/csv"}],"identifier":"https://data.transportation.gov/api/views/hgck-kgan","issued":"2024-07-19","keyword":["connected equipment","connected vehicle","connected vehicle data","connected vehicle environment","connected vehicle message","connected vehicles","on-board equipment","on-board unit","road side unit","roadside equipment","vehicle data","vehicle to infrastructure","vehicle to vehicle"],"landingPage":"https://data.transportation.gov/d/hgck-kgan","license":"http://www.usa.gov/publicdomain/label/1.0/","modified":"2026-09-03","programCode":["021:042"],"publisher":{"@type":"org:Organization","name":"Federal Highway Administration"},"spatial":"Wyoming","theme":["Automobiles"],"title":"LTE-V2X Wyoming Connected Vehicle Pilot test ID WV2IMCT-1 BSM count"},"description":"Part of the Wyoming Department of Transportation Connected Vehicle Pilot Phase 4. Verify that OBUs use different LTE-V2X Configuration Profiles based on the vehicle's speed.\nHost and remote vehicles travelling below 120 kmph\nHost and remote vehicles travelling above 120 kmph","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/fe81f1b1-cb45-4093-a29a-6dbb2030b660","harvest_record_raw":"https://catalog.data.gov/harvest_record/fe81f1b1-cb45-4093-a29a-6dbb2030b660/raw","has_download":true,"has_spatial":true,"identifier":"https://data.transportation.gov/api/views/hgck-kgan","keyword":["connected equipment","connected vehicle","connected vehicle data","connected vehicle environment","connected vehicle message","connected vehicles","on-board equipment","on-board unit","road side unit","roadside equipment","vehicle data","vehicle to infrastructure","vehicle to vehicle"],"last_harvested_date":"2026-09-03T18:35:59.767909","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"c549d5ce-2b93-4397-ab76-aa2b31d9983a","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/dot.png","name":"Department of Transportation","organization_type":"Federal Government","slug":"dot"},"parent_identifier":null,"popularity":1,"publisher":"Federal Highway Administration","slug":"lte-v2x-wyoming-connected-vehicle-pilot-test-id-wv2imct-1-bsm-count","spatial_centroid":null,"spatial_shape":null,"theme":["Automobiles"],"title":"LTE-V2X Wyoming Connected Vehicle Pilot test ID WV2IMCT-1 BSM count","type":"dataset"},{"_score":8.2433195,"_sort":[1788460548271,8.2433195,3,"afe5c4b8-699a-498b-a870-82acb8eb05a2"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["021:15"],"contactPoint":{"@type":"vcard:Contact","fn":"Elina Zlotchenko","hasEmail":"mailto:Elina.Zlotchenko@dot.gov"},"description":"Part of Wyoming Department of Transportation Connected Vehicle Pilot Phase 4. Verify that OBUs use different LTE-V2X Configuration Profiles based on the vehicle's speed.\nHost and remote vehicles travelling below 120 kmph\nHost and remote vehicles travelling above 120 kmph","distribution":[{"@type":"dcat:Distribution","describedBy":"https://data.transportation.gov/api/views/fib6-v7nq/columns.json","describedByType":"application/json","downloadURL":"https://data.transportation.gov/api/v3/views/fib6-v7nq/query.json?accessType=DOWNLOAD","mediaType":"application/json"},{"@type":"dcat:Distribution","describedBy":"https://data.transportation.gov/api/views/fib6-v7nq/columns.xml","describedByType":"application/xml","downloadURL":"https://data.transportation.gov/api/v3/views/fib6-v7nq/query.xml?accessType=DOWNLOAD","mediaType":"application/xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.transportation.gov/api/v3/views/fib6-v7nq/export.csv?accessType=DOWNLOAD","mediaType":"text/csv"},{"@type":"dcat:Distribution","downloadURL":"https://data.transportation.gov/api/v3/views/fib6-v7nq/export.kml?accessType=DOWNLOAD","mediaType":"application/vnd.google-earth.kml+xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.transportation.gov/api/v3/views/fib6-v7nq/export.kmz?accessType=DOWNLOAD","mediaType":"application/vnd.google-earth.kmz"},{"@type":"dcat:Distribution","downloadURL":"https://data.transportation.gov/api/v3/views/fib6-v7nq/query.geojson?accessType=DOWNLOAD","mediaType":"application/geo+json"}],"identifier":"https://data.transportation.gov/api/views/fib6-v7nq","issued":"2024-07-19","keyword":["connected equipment","connected vehicle","connected vehicle data","connected vehicle environment","connected vehicle message","connected vehicles","on-board equipment","on-board unit","road side unit","roadside equipment","vehicle data","vehicle to infrastructure","vehicle to vehicle"],"landingPage":"https://data.transportation.gov/d/fib6-v7nq","license":"http://www.usa.gov/publicdomain/label/1.0/","modified":"2026-09-03","programCode":["021:042"],"publisher":{"@type":"org:Organization","name":"Federal Highway Administration"},"spatial":"Wyoming","theme":["Automobiles"],"title":"LTE-V2X Wyoming Connected Vehicle Pilot test ID WV2IMCT-1 Vehicle 1 70 mph"},"description":"Part of Wyoming Department of Transportation Connected Vehicle Pilot Phase 4. Verify that OBUs use different LTE-V2X Configuration Profiles based on the vehicle's speed.\nHost and remote vehicles travelling below 120 kmph\nHost and remote vehicles travelling above 120 kmph","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/0935ec1f-9e23-467e-a90c-d506f588a9d7","harvest_record_raw":"https://catalog.data.gov/harvest_record/0935ec1f-9e23-467e-a90c-d506f588a9d7/raw","has_download":true,"has_spatial":true,"identifier":"https://data.transportation.gov/api/views/fib6-v7nq","keyword":["connected equipment","connected vehicle","connected vehicle data","connected vehicle environment","connected vehicle message","connected vehicles","on-board equipment","on-board unit","road side unit","roadside equipment","vehicle data","vehicle to infrastructure","vehicle to vehicle"],"last_harvested_date":"2026-09-03T18:35:48.271753","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"c549d5ce-2b93-4397-ab76-aa2b31d9983a","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/dot.png","name":"Department of Transportation","organization_type":"Federal Government","slug":"dot"},"parent_identifier":null,"popularity":3,"publisher":"Federal Highway Administration","slug":"lte-v2x-wyoming-connected-vehicle-pilot-test-id-wv2imct-1-vehicle-1-70-mph","spatial_centroid":null,"spatial_shape":null,"theme":["Automobiles"],"title":"LTE-V2X Wyoming Connected Vehicle Pilot test ID WV2IMCT-1 Vehicle 1 70 mph","type":"dataset"},{"_score":16.292671,"_sort":[1788460547985,16.292671,5,"225b50b1-8697-4860-bbdb-799f59b79941"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","accrualPeriodicity":"irregular","agencyDataSeriesURL":"https://www.phmsa.dot.gov/guidance","agencyProgramURL":"https://www.phmsa.dot.gov/guidance","analysisUnit":"Regulations","bureauCode":["021:50"],"categoryDesignation":"Research","collectionInstrument":"Transportation","contactPoint":{"@type":"vcard:Contact","fn":"HMIC","hasEmail":"mailto:PHMSA_Guidance@dot.gov"},"dataQuality":true,"description":"A list of Significant Guidance documents, which include guidance document disseminated to regulated entities or the general public that may reasonably be anticipated to lead to an annual effect on the economy of $100 million or more or adversely affect in a material way the economy, a sector of the economy, productivity, competition, jobs, the environment, public health or safety, or State, local, or tribal governments or communities; create a serious inconsistency or otherwise interfere with an action taken or planned by another agency; materially alter the budgetary impact of entitlements, grants, user fees, or loan programs or the rights and obligations of recipients thereof; or raise novel legal or policy issues arising out of legal mandates, the President's priorities, or the principles set forth in Executive Order 12866, as further amended.","distribution":[{"@type":"dcat:Distribution","downloadURL":"https://www.phmsa.dot.gov/guidance","mediaType":"text/html"}],"identifier":"DOT-326","issued":"2011-01-18","keyword":["data.gov","law","phmsa","significant guidance","transportation"],"landingPage":"https://data.transportation.gov/d/fhz7-hztw","language":["en-US"],"license":"http://www.usa.gov/publicdomain/label/1.0/","modified":"2026-09-03","phone":"202-366-4308","programCode":["021:000"],"publisher":{"@type":"org:Organization","name":"Pipeline and Hazardous Materials Safety Administration"},"references":["https://www.phmsa.dot.gov/guidance"],"temporal":"2005-01-01/2011-01-18","theme":["Transportation"],"title":"Significant Guidance on Hazardous Materials Safety Issued by the Pipeline and Hazardous Materials Safety Administration"},"description":"A list of Significant Guidance documents, which include guidance document disseminated to regulated entities or the general public that may reasonably be anticipated to lead to an annual effect on the economy of $100 million or more or adversely affect in a material way the economy, a sector of the economy, productivity, competition, jobs, the environment, public health or safety, or State, local, or tribal governments or communities; create a serious inconsistency or otherwise interfere with an action taken or planned by another agency; materially alter the budgetary impact of entitlements, grants, user fees, or loan programs or the rights and obligations of recipients thereof; or raise novel legal or policy issues arising out of legal mandates, the President's priorities, or the principles set forth in Executive Order 12866, as further amended.","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/6e2d1762-fd35-49f5-ad69-94fe7ec92144","harvest_record_raw":"https://catalog.data.gov/harvest_record/6e2d1762-fd35-49f5-ad69-94fe7ec92144/raw","has_download":true,"has_spatial":false,"identifier":"DOT-326","keyword":["data.gov","law","phmsa","significant guidance","transportation"],"last_harvested_date":"2026-09-03T18:35:47.985641","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"c549d5ce-2b93-4397-ab76-aa2b31d9983a","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/dot.png","name":"Department of Transportation","organization_type":"Federal Government","slug":"dot"},"parent_identifier":null,"popularity":5,"publisher":"Pipeline and Hazardous Materials Safety Administration","slug":"significant-guidance-on-hazardous-materials-safety-issued-by-the-pipeline-and-hazardous-ma","spatial_centroid":null,"spatial_shape":null,"theme":["Transportation"],"title":"Significant Guidance on Hazardous Materials Safety Issued by the Pipeline and Hazardous Materials Safety Administration","type":"dataset"},{"_score":17.600376,"_sort":[1788460544509,17.600376,3,"fe915e70-1711-4a3a-a594-a6ff7050831f"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["021:15"],"contactPoint":{"@type":"vcard:Contact","fn":"Elina Zlotchenko","hasEmail":"mailto:Elina.Zlotchenko@dot.gov"},"description":"This dataset contains V2X data collected from the Utah Connected Vehicle Data Ecosystem Program. We have submitted 7 days of deduplicated Basic Safety Messages (BSMs) in J2735 standards from 3 intersections in Orem, UT.This includes: (1) vehicles equipped with OBUs (Onboard Units) for real-time V2X (Vehicle-to-Everything) data transmission and reception, (2) road-side units (RSUs) capable of capturing, transmitting, and processing data from the transportation environment, and (3) a secure, scalable cloud platform for aggregating, analyzing, and visualizing transportation data.","distribution":[{"@type":"dcat:Distribution","describedBy":"https://data.transportation.gov/api/views/ev64-jn8c/columns.json","describedByType":"application/json","downloadURL":"https://data.transportation.gov/api/v3/views/ev64-jn8c/query.json?accessType=DOWNLOAD","mediaType":"application/json"},{"@type":"dcat:Distribution","describedBy":"https://data.transportation.gov/api/views/ev64-jn8c/columns.xml","describedByType":"application/xml","downloadURL":"https://data.transportation.gov/api/v3/views/ev64-jn8c/query.xml?accessType=DOWNLOAD","mediaType":"application/xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.transportation.gov/api/v3/views/ev64-jn8c/export.csv?accessType=DOWNLOAD","mediaType":"text/csv"}],"identifier":"https://data.transportation.gov/api/views/ev64-jn8c","issued":"2025-07-07","keyword":["basic safety message (bsm)","connected vehicle data","intelligent transportation systems (its)","its joint program office (jpo)","signal phase and timing (spat)","transit signal priority (tsp)"],"landingPage":"https://data.transportation.gov/d/ev64-jn8c","license":"http://www.usa.gov/publicdomain/label/1.0/","modified":"2026-09-03","programCode":["021:042"],"publisher":{"@type":"org:Organization","name":"US Department of Transportation"},"theme":["Transit"],"title":"BSM from UDOT and Panasonic Connected Vehicle Data Ecosystem Program"},"description":"This dataset contains V2X data collected from the Utah Connected Vehicle Data Ecosystem Program. We have submitted 7 days of deduplicated Basic Safety Messages (BSMs) in J2735 standards from 3 intersections in Orem, UT.This includes: (1) vehicles equipped with OBUs (Onboard Units) for real-time V2X (Vehicle-to-Everything) data transmission and reception, (2) road-side units (RSUs) capable of capturing, transmitting, and processing data from the transportation environment, and (3) a secure, scalable cloud platform for aggregating, analyzing, and visualizing transportation data.","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/a1eea30a-3a8f-491b-9b70-be66cf7b7d3e","harvest_record_raw":"https://catalog.data.gov/harvest_record/a1eea30a-3a8f-491b-9b70-be66cf7b7d3e/raw","has_download":true,"has_spatial":false,"identifier":"https://data.transportation.gov/api/views/ev64-jn8c","keyword":["basic safety message (bsm)","connected vehicle data","intelligent transportation systems (its)","its joint program office (jpo)","signal phase and timing (spat)","transit signal priority (tsp)"],"last_harvested_date":"2026-09-03T18:35:44.509932","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"c549d5ce-2b93-4397-ab76-aa2b31d9983a","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/dot.png","name":"Department of Transportation","organization_type":"Federal Government","slug":"dot"},"parent_identifier":null,"popularity":3,"publisher":"US Department of Transportation","slug":"bsm-from-udot-and-panasonic-connected-vehicle-data-ecosystem-program","spatial_centroid":null,"spatial_shape":null,"theme":["Transit"],"title":"BSM from UDOT and Panasonic Connected Vehicle Data Ecosystem Program","type":"dataset"},{"_score":8.160547,"_sort":[1788460529403,8.160547,3,"31c10844-4bf0-4c1b-a798-03f7b60947b2"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["021:15"],"contactPoint":{"@type":"vcard:Contact","fn":"Elina Zlotchenko","hasEmail":"mailto:Elina.Zlotchenko@dot.gov"},"description":"Part of Wyoming Department of Transportation Connected Vehicle Pilot Phase 4. Verify that OBUs use different LTE-V2X Configuration Profiles based on the vehicle's speed.\nHost and remote vehicles travelling below 120 kmph\nHost and remote vehicles travelling above 120 kmph","distribution":[{"@type":"dcat:Distribution","describedBy":"https://data.transportation.gov/api/views/czer-epuy/columns.json","describedByType":"application/json","downloadURL":"https://data.transportation.gov/api/v3/views/czer-epuy/query.json?accessType=DOWNLOAD","mediaType":"application/json"},{"@type":"dcat:Distribution","describedBy":"https://data.transportation.gov/api/views/czer-epuy/columns.xml","describedByType":"application/xml","downloadURL":"https://data.transportation.gov/api/v3/views/czer-epuy/query.xml?accessType=DOWNLOAD","mediaType":"application/xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.transportation.gov/api/v3/views/czer-epuy/export.csv?accessType=DOWNLOAD","mediaType":"text/csv"},{"@type":"dcat:Distribution","downloadURL":"https://data.transportation.gov/api/v3/views/czer-epuy/export.kml?accessType=DOWNLOAD","mediaType":"application/vnd.google-earth.kml+xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.transportation.gov/api/v3/views/czer-epuy/export.kmz?accessType=DOWNLOAD","mediaType":"application/vnd.google-earth.kmz"},{"@type":"dcat:Distribution","downloadURL":"https://data.transportation.gov/api/v3/views/czer-epuy/query.geojson?accessType=DOWNLOAD","mediaType":"application/geo+json"}],"identifier":"https://data.transportation.gov/api/views/czer-epuy","issued":"2024-07-19","keyword":["connected equipment","connected vehicle","connected vehicle data","connected vehicle environment","connected vehicle message","connected vehicles","on-board equipment","on-board unit","road side unit","roadside equipment","vehicle data","vehicle to infrastructure","vehicle to vehicle"],"landingPage":"https://data.transportation.gov/d/czer-epuy","license":"http://www.usa.gov/publicdomain/label/1.0/","modified":"2026-09-02","programCode":["021:042"],"publisher":{"@type":"org:Organization","name":"Federal Highway Administration"},"spatial":"Wyoming","theme":["Automobiles"],"title":"LTE-V2X Wyoming Connected Vehicle Pilot test ID WV2IMCT-1 Vehicle 2 70 mph"},"description":"Part of Wyoming Department of Transportation Connected Vehicle Pilot Phase 4. Verify that OBUs use different LTE-V2X Configuration Profiles based on the vehicle's speed.\nHost and remote vehicles travelling below 120 kmph\nHost and remote vehicles travelling above 120 kmph","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/8376629c-9315-4bd7-9ce1-11c953081b7e","harvest_record_raw":"https://catalog.data.gov/harvest_record/8376629c-9315-4bd7-9ce1-11c953081b7e/raw","has_download":true,"has_spatial":true,"identifier":"https://data.transportation.gov/api/views/czer-epuy","keyword":["connected equipment","connected vehicle","connected vehicle data","connected vehicle environment","connected vehicle message","connected vehicles","on-board equipment","on-board unit","road side unit","roadside equipment","vehicle data","vehicle to infrastructure","vehicle to vehicle"],"last_harvested_date":"2026-09-03T18:35:29.403685","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"c549d5ce-2b93-4397-ab76-aa2b31d9983a","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/dot.png","name":"Department of Transportation","organization_type":"Federal Government","slug":"dot"},"parent_identifier":null,"popularity":3,"publisher":"Federal Highway Administration","slug":"lte-v2x-wyoming-connected-vehicle-pilot-test-id-wv2imct-1-vehicle-2-70-mph","spatial_centroid":null,"spatial_shape":null,"theme":["Automobiles"],"title":"LTE-V2X Wyoming Connected Vehicle Pilot test ID WV2IMCT-1 Vehicle 2 70 mph","type":"dataset"},{"_score":8.183754,"_sort":[1788460521815,8.183754,40,"4dbc38a8-6da3-4a67-9030-566c33013cbb"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["021:15"],"contactPoint":{"@type":"vcard:Contact","fn":"Hyungjun Park","hasEmail":"mailto:hyungjun.park@dot.gov"},"description":"The main dataset is a 350 MB file of trajectory data (TGSIM-Foggy Bottom-Data.csv) that contains position, speed, and acceleration data for pedestrians, bicycles, scooters, non-automated passenger cars, automated vehicles, motorcycles, buses, and trucks in an urban environment. Supporting files include an aerial reference image (Reference_Image_Foggy Bottom.png) and a list of polygon boundaries (Foggy_Bottom_boundaries.txt) and associated images (i1.png, i2.png, \u2026, i49.png stored in the folder titled \u201cAnnotation on Regions.zip\u201d) to map physical roadway segments to numerical IDs (as referenced in the trajectory dataset). \n\nThis dataset was collected as part of the Third Generation Simulation Data (TGSIM): A Closer Look at the Impacts of Automated Driving Systems on Human Behavior project. During the project, six trajectory datasets capable of characterizing human-automated vehicle interactions under a diverse set of scenarios in highway and city environments were collected and processed. For more information, see the project report found here: https://rosap.ntl.bts.gov/view/dot/74647. This dataset, which is one of the six collected as part of the TGSIM project, contains data collected from twelve 4K stationary infrastructure cameras installed in the Foggy Bottom neighborhood of Washington, D.C. The cameras captured four intersections, adjacent crosswalks, road segments between the intersections, and partial road segments extending out from the intersections totaling more than one full block of coverage. These segments are represented by polygons to bound travel lanes, parking lanes, crosswalks, and intersections for detection and analysis purposes (see Reference_Image_Foggy Bottom.png for details). The cameras captured continuous footage during a weekday commute between 3:00PM-5:00PM ET on a sunny day. During this period, one test vehicle equipped with SAE Level 3 automation was deployed to perform various complex maneuvers at both stop signs and traffic signals, including both protected and permitted left turns, to capture human driving behaviors when interacting with automated vehicles. The automated vehicles are indicated in the dataset.\n\nAs part of this dataset, the following files were provided:\n<ul><li>TGSIM-Foggy Bottom-Data.csv contains the numerical data to be used for analysis that includes vehicle/bicycle/pedestrian trajectory data at every 0.1 second. Road user type, width, and length are provided with instantaneous location, speed, and acceleration data. All distance measurements (width, length, location) were converted from pixels to meters using the following conversion factor: 1 pixel = 0.0186613838586-meter conversion.</li>\n<li>Reference_Image_Foggy Bottom.png is the aerial reference image that defines the geographic region and the associated roadway segments.</li>\t\n<li>Foggy_Bottom_boundaries.txt contains the coordinates that define the roadway segments (n = 49). Each polygon is a list of four to six coordinate pairs measured in pixels (which can be converted to meters using the provided 1 pixel = 0.0186613838586-meter conversion), with (0,0) global reference coordinates at the top-left of the reference image.</li>\n<li>Annotation on Regions.zip, which includes i1.png, i2.png,..., i49.png, are images that visually map the road segment IDs (indicated by the number following the i in the file name) to the reference image.</li></ul>","distribution":[{"@type":"dcat:Distribution","describedBy":"https://data.transportation.gov/api/views/brzy-6zfh/columns.json","describedByType":"application/json","downloadURL":"https://data.transportation.gov/api/v3/views/brzy-6zfh/query.json?accessType=DOWNLOAD","mediaType":"application/json"},{"@type":"dcat:Distribution","describedBy":"https://data.transportation.gov/api/views/brzy-6zfh/columns.xml","describedByType":"application/xml","downloadURL":"https://data.transportation.gov/api/v3/views/brzy-6zfh/query.xml?accessType=DOWNLOAD","mediaType":"application/xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.transportation.gov/api/v3/views/brzy-6zfh/export.csv?accessType=DOWNLOAD","mediaType":"text/csv"}],"identifier":"https://data.transportation.gov/api/views/brzy-6zfh","issued":"2024-11-04","keyword":["aerial videography","automated vehicles","category: vehicle safety","human-automated vehicle interactions","infrastructure-based videography","intelligent transportation systems (its)","its joint program office (jpo)","multi-modal trajectories","subcategory: autonomous vehicle safety systems","tgsim","third generation simulation","vehicle trajectory data"],"landingPage":"https://data.transportation.gov/d/brzy-6zfh","license":"http://www.usa.gov/publicdomain/label/1.0/","modified":"2026-09-02","programCode":["021:042"],"publisher":{"@type":"org:Organization","name":"Federal Highway Administration"},"spatial":"I-90/I94 in Chicago, IL; I-294 near Hinsdale, IL; I-395 in Washington DC; George Washington University Campus, Washington DC (Foggy Bottom)","theme":["Automobiles"],"title":"Third Generation Simulation Data (TGSIM) Foggy Bottom Trajectories"},"description":"The main dataset is a 350 MB file of trajectory data (TGSIM-Foggy Bottom-Data.csv) that contains position, speed, and acceleration data for pedestrians, bicycles, scooters, non-automated passenger cars, automated vehicles, motorcycles, buses, and trucks in an urban environment. Supporting files include an aerial reference image (Reference_Image_Foggy Bottom.png) and a list of polygon boundaries (Foggy_Bottom_boundaries.txt) and associated images (i1.png, i2.png, \u2026, i49.png stored in the folder titled \u201cAnnotation on Regions.zip\u201d) to map physical roadway segments to numerical IDs (as referenced in the trajectory dataset). \n\nThis dataset was collected as part of the Third Generation Simulation Data (TGSIM): A Closer Look at the Impacts of Automated Driving Systems on Human Behavior project. During the project, six trajectory datasets capable of characterizing human-automated vehicle interactions under a diverse set of scenarios in highway and city environments were collected and processed. For more information, see the project report found here: https://rosap.ntl.bts.gov/view/dot/74647. This dataset, which is one of the six collected as part of the TGSIM project, contains data collected from twelve 4K stationary infrastructure cameras installed in the Foggy Bottom neighborhood of Washington, D.C. The cameras captured four intersections, adjacent crosswalks, road segments between the intersections, and partial road segments extending out from the intersections totaling more than one full block of coverage. These segments are represented by polygons to bound travel lanes, parking lanes, crosswalks, and intersections for detection and analysis purposes (see Reference_Image_Foggy Bottom.png for details). The cameras captured continuous footage during a weekday commute between 3:00PM-5:00PM ET on a sunny day. During this period, one test vehicle equipped with SAE Level 3 automation was deployed to perform various complex maneuvers at both stop signs and traffic signals, including both protected and permitted left turns, to capture human driving behaviors when interacting with automated vehicles. The automated vehicles are indicated in the dataset.\n\nAs part of this dataset, the following files were provided:\n<ul><li>TGSIM-Foggy Bottom-Data.csv contains the numerical data to be used for analysis that includes vehicle/bicycle/pedestrian trajectory data at every 0.1 second. Road user type, width, and length are provided with instantaneous location, speed, and acceleration data. All distance measurements (width, length, location) were converted from pixels to meters using the following conversion factor: 1 pixel = 0.0186613838586-meter conversion.</li>\n<li>Reference_Image_Foggy Bottom.png is the aerial reference image that defines the geographic region and the associated roadway segments.</li>\t\n<li>Foggy_Bottom_boundaries.txt contains the coordinates that define the roadway segments (n = 49). Each polygon is a list of four to six coordinate pairs measured in pixels (which can be converted to meters using the provided 1 pixel = 0.0186613838586-meter conversion), with (0,0) global reference coordinates at the top-left of the reference image.</li>\n<li>Annotation on Regions.zip, which includes i1.png, i2.png,..., i49.png, are images that visually map the road segment IDs (indicated by the number following the i in the file name) to the reference image.</li></ul>","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/4dfca4de-f1fc-426e-904d-59efecd0036b","harvest_record_raw":"https://catalog.data.gov/harvest_record/4dfca4de-f1fc-426e-904d-59efecd0036b/raw","has_download":true,"has_spatial":true,"identifier":"https://data.transportation.gov/api/views/brzy-6zfh","keyword":["aerial videography","automated vehicles","category: vehicle safety","human-automated vehicle interactions","infrastructure-based videography","intelligent transportation systems (its)","its joint program office (jpo)","multi-modal trajectories","subcategory: autonomous vehicle safety systems","tgsim","third generation simulation","vehicle trajectory data"],"last_harvested_date":"2026-09-03T18:35:21.815035","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"c549d5ce-2b93-4397-ab76-aa2b31d9983a","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/dot.png","name":"Department of Transportation","organization_type":"Federal Government","slug":"dot"},"parent_identifier":null,"popularity":40,"publisher":"Federal Highway Administration","slug":"third-generation-simulation-data-tgsim-foggy-bottom-trajectories","spatial_centroid":null,"spatial_shape":null,"theme":["Automobiles"],"title":"Third Generation Simulation Data (TGSIM) Foggy Bottom Trajectories","type":"dataset"},{"_score":8.761225,"_sort":[1788460520340,8.761225,13,"0b744d62-e399-40fe-8f62-8d4a81eef70f"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","accrualPeriodicity":"irregular","agencyDataSeriesURL":"http://www.ops.fhwa.dot.gov/freight/freight_analysis/faf/","agencyProgramURL":"http://www.ops.fhwa.dot.gov/freight/freight_analysis/faf/","analysisUnit":"Region","bureauCode":["021:15"],"categoryDesignation":"Research","collectionInstrument":"Forecast developed using commodity flow survey","contactPoint":{"@type":"vcard:Contact","fn":"Office of Freight Management and Operations","hasEmail":"mailto:FreightFeedback@dot.gov"},"dataQuality":true,"describedBy":"http://www.ops.fhwa.dot.gov/freight/freight_analysis/faf/faf3/userguide/index.htm#t5","description":"The Freight Analysis Framework (FAF) integrates data from a variety of sources to create a comprehensive picture of freight movement among states and major metropolitan areas by all modes of transportation. With data from the 2007 Commodity Flow Survey and additional sources, FAF version 3 (FAF3) provides estimates for tonnage, value, and domestic ton-miles by region of origin and destination, commodity type, and mode for 2007, the most recent year, and forecasts through 2040. Also included are state-to-state flows for these years plus 1997 and 2002, summary statistics, and flows by truck assigned to the highway network for 2007 and 2040.","distribution":[{"@type":"dcat:Distribution","downloadURL":"http://faf.ornl.gov/fafweb/","mediaType":"text/html","title":"FAF3 Origin-Destination zip data"}],"identifier":"286.4","isPartOf":"DOT-286","issued":"2013-03-20","keyword":["commodity","consumption","domestic","economic activity","energy","environment","export","exposure","flow","forecast","freight","import","infrastructure","risk","safety","ton-miles","tons","transportation","trend","trucks","value","wear"],"landingPage":"https://ops.fhwa.dot.gov/freight/freight_analysis/faf/","language":["en-US"],"license":"https://www.usa.gov/government-works","modified":"2026-09-02","phone":"202-366-6993","primaryITInvestmentUII":"021-844694854","programCode":["021:009"],"publisher":{"@type":"org:Organization","name":"Federal Highway Administration"},"spatial":"Region. Domestic regions are defined here: http://www.ops.fhwa.dot.gov/freight/freight_analysis/faf/faf3/userguide/index.htm#t3 and foreign regions are defined here: http://www.ops.fhwa.dot.gov/freight/freight_analysis/faf/faf3/userguide/index.htm#t4","temporal":"2007-01-01/2040-12-31","theme":["Transportation"],"title":"Freight Analysis Framework - FAF3 Origin-Destination zip data"},"description":"The Freight Analysis Framework (FAF) integrates data from a variety of sources to create a comprehensive picture of freight movement among states and major metropolitan areas by all modes of transportation. With data from the 2007 Commodity Flow Survey and additional sources, FAF version 3 (FAF3) provides estimates for tonnage, value, and domestic ton-miles by region of origin and destination, commodity type, and mode for 2007, the most recent year, and forecasts through 2040. Also included are state-to-state flows for these years plus 1997 and 2002, summary statistics, and flows by truck assigned to the highway network for 2007 and 2040.","distribution_titles":["FAF3 Origin-Destination zip data"],"harvest_record":"https://catalog.data.gov/harvest_record/bc3623dc-b2d8-4f17-9a73-1227da2efde5","harvest_record_raw":"https://catalog.data.gov/harvest_record/bc3623dc-b2d8-4f17-9a73-1227da2efde5/raw","has_download":true,"has_spatial":true,"identifier":"286.4","keyword":["commodity","consumption","domestic","economic activity","energy","environment","export","exposure","flow","forecast","freight","import","infrastructure","risk","safety","ton-miles","tons","transportation","trend","trucks","value","wear"],"last_harvested_date":"2026-09-03T18:35:20.340116","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"c549d5ce-2b93-4397-ab76-aa2b31d9983a","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/dot.png","name":"Department of Transportation","organization_type":"Federal Government","slug":"dot"},"parent_identifier":"DOT-286","popularity":13,"publisher":"Federal Highway Administration","slug":"freight-analysis-framework-faf3-origin-destination-zip-data","spatial_centroid":null,"spatial_shape":null,"theme":["Transportation"],"title":"Freight Analysis Framework - FAF3 Origin-Destination zip data","type":"dataset"},{"_score":6.911463,"_sort":[1788460506750,6.911463,12,"7479b7c6-a5cb-40c8-b5c6-ffbd39935c47"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["021:15"],"contactPoint":{"@type":"vcard:Contact","fn":"Hyungjun Park","hasEmail":"mailto:hyungjun.park@dot.gov"},"description":"The main dataset is a 304 MB file of trajectory data (I90_94_stationary_final.csv) that contains position, speed, and acceleration data for small and large automated (L2) vehicles and non-automated vehicles on a highway in an urban environment. Supporting files include aerial reference images for six distinct data collection \u201cRuns\u201d (I90_94_Stationary_Run_X_ref_image.png, where X equals 1, 2, 3, 4, 5, and 6). Associated centerline files are also provided for each \u201cRun\u201d (I-90-stationary-Run_X-geometry-with-ramps.csv). In each centerline file, x and y coordinates (in meters) marking each lane centerline are provided. The origin point of the reference image is located at the top left corner. Additionally, in each centerline file, an indicator variable is used for each lane to define the following types of road sections: 0=no ramp, 1=on-ramps, 2=off-ramps, and 3=weaving segments. The number attached to each column header is the numerical ID assigned for the specific lane (see \u201cTGSIM \u2013 Centerline Data Dictionary \u2013 I90_94Stationary.csv\u201d for more details). The dataset defines six northbound lanes using these centerline files. Twelve different numerical IDs are used to define the six northbound lanes (1, 2, 3, 4, 5, 6, 10, 11, 12, 13, 14, and 15) depending on the run. Images that map the lanes of interest to the numerical lane IDs referenced in the trajectory dataset are stored in the folder titled \u201cAnnotation on Regions.zip\u201d. Lane IDs are provided in the reference images in red text for each data collection run (I90_94_Stationary_Run_X_ref_image_annotated.jpg, where X equals 1, 2, 3, 4, 5, and 6). \n\nThis dataset was collected as part of the Third Generation Simulation Data (TGSIM): A Closer Look at the Impacts of Automated Driving Systems on Human Behavior project. During the project, six trajectory datasets capable of characterizing human-automated vehicle interactions under a diverse set of scenarios in highway and city environments were collected and processed. For more information, see the project report found here: https://rosap.ntl.bts.gov/view/dot/74647. This dataset, which is one of the six collected as part of the TGSIM project, contains data collected using the fixed location aerial videography approach with one high-resolution 8K camera mounted on a helicopter hovering over a short segment of I-94 focusing on the merge and diverge points in Chicago, IL. The altitude of the helicopter (approximately 213 meters) enabled the camera to capture 1.3 km of highway driving and a major weaving section in each direction (where I-90 and I-94 diverge in the northbound direction and merge in the southbound direction). The segment has two off-ramps and two on-ramps in the northbound direction. All roads have 88 kph (55 mph) speed limits. The camera captured footage during the evening rush hour (4:00 PM-6:00 PM CT) on a cloudy day. During this period, two SAE Level 2 ADAS-equipped vehicles drove through the segment, entering the northbound direction upstream of the target section, exiting the target section on the right through I-94, and attempting to perform a total of three lane-changing maneuvers (if safe to do so). These vehicles are indicated in the dataset.\n\nAs part of this dataset, the following files were provided:\n<ul><li>I90_94_stationary_final.csv contains the numerical data to be used for analysis that includes vehicle level trajectory data at every 0.1 second. Vehicle type, width, and length are provided with instantaneous location, speed, and acceleration data. All distance measurements (width, length, location) were converted from pixels to meters using the following conversion factor: 1 pixel = 0.3-meter conversion.</li>\n<li>I90_94_Stationary_Run_X_ref_image.png are the aerial reference images that define the geographic region for each run X.</li>\n<li>I-90-stationary-Run_X-geometry-with-ramps.csv contain the coordinates that define the lane centerlines for each Run X. The \"x\" and \"y\" columns represent the horizontal and ve","distribution":[{"@type":"dcat:Distribution","describedBy":"https://data.transportation.gov/api/views/9uas-hf8b/columns.json","describedByType":"application/json","downloadURL":"https://data.transportation.gov/api/v3/views/9uas-hf8b/query.json?accessType=DOWNLOAD","mediaType":"application/json"},{"@type":"dcat:Distribution","describedBy":"https://data.transportation.gov/api/views/9uas-hf8b/columns.xml","describedByType":"application/xml","downloadURL":"https://data.transportation.gov/api/v3/views/9uas-hf8b/query.xml?accessType=DOWNLOAD","mediaType":"application/xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.transportation.gov/api/v3/views/9uas-hf8b/export.csv?accessType=DOWNLOAD","mediaType":"text/csv"}],"identifier":"https://data.transportation.gov/api/views/9uas-hf8b","issued":"2024-11-04","keyword":["aerial videography","automated vehicles","category: vehicle safety","human-automated vehicle interactions","infrastructure-based videography","intelligent transportation systems (its)","its joint program office (jpo)","multi-modal trajectories","subcategory: autonomous vehicle safety systems","tgsim","third generation simulation","vehicle trajectory data"],"landingPage":"https://data.transportation.gov/d/9uas-hf8b","license":"http://www.usa.gov/publicdomain/label/1.0/","modified":"2026-09-02","programCode":["021:042"],"publisher":{"@type":"org:Organization","name":"Federal Highway Administration"},"spatial":"I-90/I94 in Chicago, IL; I-294 near Hinsdale, IL; I-395 in Washington DC; George Washington University Campus, Washington DC (Foggy Bottom)","theme":["Automobiles"],"title":"Third Generation Simulation Data (TGSIM) I-90/I-94 Stationary Trajectories"},"description":"The main dataset is a 304 MB file of trajectory data (I90_94_stationary_final.csv) that contains position, speed, and acceleration data for small and large automated (L2) vehicles and non-automated vehicles on a highway in an urban environment. Supporting files include aerial reference images for six distinct data collection \u201cRuns\u201d (I90_94_Stationary_Run_X_ref_image.png, where X equals 1, 2, 3, 4, 5, and 6). Associated centerline files are also provided for each \u201cRun\u201d (I-90-stationary-Run_X-geometry-with-ramps.csv). In each centerline file, x and y coordinates (in meters) marking each lane centerline are provided. The origin point of the reference image is located at the top left corner. Additionally, in each centerline file, an indicator variable is used for each lane to define the following types of road sections: 0=no ramp, 1=on-ramps, 2=off-ramps, and 3=weaving segments. The number attached to each column header is the numerical ID assigned for the specific lane (see \u201cTGSIM \u2013 Centerline Data Dictionary \u2013 I90_94Stationary.csv\u201d for more details). The dataset defines six northbound lanes using these centerline files. Twelve different numerical IDs are used to define the six northbound lanes (1, 2, 3, 4, 5, 6, 10, 11, 12, 13, 14, and 15) depending on the run. Images that map the lanes of interest to the numerical lane IDs referenced in the trajectory dataset are stored in the folder titled \u201cAnnotation on Regions.zip\u201d. Lane IDs are provided in the reference images in red text for each data collection run (I90_94_Stationary_Run_X_ref_image_annotated.jpg, where X equals 1, 2, 3, 4, 5, and 6). \n\nThis dataset was collected as part of the Third Generation Simulation Data (TGSIM): A Closer Look at the Impacts of Automated Driving Systems on Human Behavior project. During the project, six trajectory datasets capable of characterizing human-automated vehicle interactions under a diverse set of scenarios in highway and city environments were collected and processed. For more information, see the project report found here: https://rosap.ntl.bts.gov/view/dot/74647. This dataset, which is one of the six collected as part of the TGSIM project, contains data collected using the fixed location aerial videography approach with one high-resolution 8K camera mounted on a helicopter hovering over a short segment of I-94 focusing on the merge and diverge points in Chicago, IL. The altitude of the helicopter (approximately 213 meters) enabled the camera to capture 1.3 km of highway driving and a major weaving section in each direction (where I-90 and I-94 diverge in the northbound direction and merge in the southbound direction). The segment has two off-ramps and two on-ramps in the northbound direction. All roads have 88 kph (55 mph) speed limits. The camera captured footage during the evening rush hour (4:00 PM-6:00 PM CT) on a cloudy day. During this period, two SAE Level 2 ADAS-equipped vehicles drove through the segment, entering the northbound direction upstream of the target section, exiting the target section on the right through I-94, and attempting to perform a total of three lane-changing maneuvers (if safe to do so). These vehicles are indicated in the dataset.\n\nAs part of this dataset, the following files were provided:\n<ul><li>I90_94_stationary_final.csv contains the numerical data to be used for analysis that includes vehicle level trajectory data at every 0.1 second. Vehicle type, width, and length are provided with instantaneous location, speed, and acceleration data. All distance measurements (width, length, location) were converted from pixels to meters using the following conversion factor: 1 pixel = 0.3-meter conversion.</li>\n<li>I90_94_Stationary_Run_X_ref_image.png are the aerial reference images that define the geographic region for each run X.</li>\n<li>I-90-stationary-Run_X-geometry-with-ramps.csv contain the coordinates that define the lane centerlines for each Run X. The \"x\" and \"y\" columns represent the horizontal and ve","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/e66fb16d-b127-44ed-b839-fc66bf31dfd3","harvest_record_raw":"https://catalog.data.gov/harvest_record/e66fb16d-b127-44ed-b839-fc66bf31dfd3/raw","has_download":true,"has_spatial":true,"identifier":"https://data.transportation.gov/api/views/9uas-hf8b","keyword":["aerial videography","automated vehicles","category: vehicle safety","human-automated vehicle interactions","infrastructure-based videography","intelligent transportation systems (its)","its joint program office (jpo)","multi-modal trajectories","subcategory: autonomous vehicle safety systems","tgsim","third generation simulation","vehicle trajectory data"],"last_harvested_date":"2026-09-03T18:35:06.750064","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"c549d5ce-2b93-4397-ab76-aa2b31d9983a","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/dot.png","name":"Department of Transportation","organization_type":"Federal Government","slug":"dot"},"parent_identifier":null,"popularity":12,"publisher":"Federal Highway Administration","slug":"third-generation-simulation-data-tgsim-i-90-i-94-stationary-trajectories","spatial_centroid":null,"spatial_shape":null,"theme":["Automobiles"],"title":"Third Generation Simulation Data (TGSIM) I-90/I-94 Stationary Trajectories","type":"dataset"},{"_score":7.4724655,"_sort":[1788460505476,7.4724655,3,"82ea930c-a552-4345-bdcc-adb3a4d068c8"],"dcat":{"@type":"dcat:Dataset","accessLevel":"public","bureauCode":["021:15"],"contactPoint":{"@type":"vcard:Contact","fn":"Elina Zlotchenko","hasEmail":"mailto:Elina.Zlotchenko@dot.gov"},"description":"WFCW-2 Stopped Vehicle Message Prioritization Rep 2","distribution":[{"@type":"dcat:Distribution","describedBy":"https://data.transportation.gov/api/views/9k38-2n3v/columns.json","describedByType":"application/json","downloadURL":"https://data.transportation.gov/api/v3/views/9k38-2n3v/query.json?accessType=DOWNLOAD","mediaType":"application/json"},{"@type":"dcat:Distribution","describedBy":"https://data.transportation.gov/api/views/9k38-2n3v/columns.xml","describedByType":"application/xml","downloadURL":"https://data.transportation.gov/api/v3/views/9k38-2n3v/query.xml?accessType=DOWNLOAD","mediaType":"application/xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.transportation.gov/api/v3/views/9k38-2n3v/export.csv?accessType=DOWNLOAD","mediaType":"text/csv"},{"@type":"dcat:Distribution","downloadURL":"https://data.transportation.gov/api/v3/views/9k38-2n3v/export.kml?accessType=DOWNLOAD","mediaType":"application/vnd.google-earth.kml+xml"},{"@type":"dcat:Distribution","downloadURL":"https://data.transportation.gov/api/v3/views/9k38-2n3v/export.kmz?accessType=DOWNLOAD","mediaType":"application/vnd.google-earth.kmz"},{"@type":"dcat:Distribution","downloadURL":"https://data.transportation.gov/api/v3/views/9k38-2n3v/query.geojson?accessType=DOWNLOAD","mediaType":"application/geo+json"}],"identifier":"https://data.transportation.gov/api/views/9k38-2n3v","issued":"2024-09-06","keyword":["connected equipment","connected vehicle","connected vehicle data","connected vehicle environment","connected vehicle message","connected vehicles","cvp","intelligent transportation systems (its)","its joint program office (jpo)","on-board equipment","on-board unit","road side unit","roadside equipment","vehicle data","vehicle to infrastructure","vehicle to vehicle"],"landingPage":"https://data.transportation.gov/d/9k38-2n3v","license":"http://www.usa.gov/publicdomain/label/1.0/","modified":"2026-09-02","programCode":["021:042"],"publisher":{"@type":"org:Organization","name":"Federal Highway Administration"},"spatial":"Wyoming","theme":["Automobiles"],"title":"LTE-V2X Wyoming Connected Vehicle Pilot test ID WFCW-2 Rep 2"},"description":"WFCW-2 Stopped Vehicle Message Prioritization Rep 2","distribution_titles":[],"harvest_record":"https://catalog.data.gov/harvest_record/081c7cfc-e78f-4000-95d6-cfffd86299b9","harvest_record_raw":"https://catalog.data.gov/harvest_record/081c7cfc-e78f-4000-95d6-cfffd86299b9/raw","has_download":true,"has_spatial":true,"identifier":"https://data.transportation.gov/api/views/9k38-2n3v","keyword":["connected equipment","connected vehicle","connected vehicle data","connected vehicle environment","connected vehicle message","connected vehicles","cvp","intelligent transportation systems (its)","its joint program office (jpo)","on-board equipment","on-board unit","road side unit","roadside equipment","vehicle data","vehicle to infrastructure","vehicle to vehicle"],"last_harvested_date":"2026-09-03T18:35:05.476854","organization":{"aliases":["dept"],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"c549d5ce-2b93-4397-ab76-aa2b31d9983a","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/dot.png","name":"Department of Transportation","organization_type":"Federal Government","slug":"dot"},"parent_identifier":null,"popularity":3,"publisher":"Federal Highway Administration","slug":"lte-v2x-wyoming-connected-vehicle-pilot-test-id-wfcw-2-rep-2","spatial_centroid":null,"spatial_shape":null,"theme":["Automobiles"],"title":"LTE-V2X Wyoming Connected Vehicle Pilot test ID WFCW-2 Rep 2","type":"dataset"}],"sort":"last_harvested_date"}