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This data set contains soil water infiltration measurements using Beerkan infiltration rings in four Oregon agricultural soils amended with biochar. Gasified biochars made from wheat straw (AgEnergy, Spokane, WA) and conifer wood (BioLogical, Philomath, OR) were tilled into soils at experimental stations in Madras (loam), Pendleton (silt loam), Aurora (sandy loam), and Klamath Falls (loamy sand). The biochars were incorporated by tillage in fall 2016 to a depth of 12 cm at rates equating to 0, 9, 18, and 36 Mg/ha (about 0.5, 1, 2, and 4% by mass in the tillage zone), with three replicate plots per treatment. In April and May 2017 infiltration was measured by inserting small rings into the soil surface and determining the time required for repeated 10 0mL volumes of water to infiltrate. From each infiltration experiment we estimated steady-state infiltration rate, and where possible we also estimated field saturated soil hydraulic conductivity (Kfs). Diagnostic plots demonstrated that in about half of the measurements sets, Kfs could be estimated by modeling infiltration as a two-term function of sorptivity and Kfs. In the remaining plots, additional unknown factors that influenced infiltration prevented estimation of Kfs, possibly due to air entrapment, soil layering, or ring insertion effects in the remaining experiments. Increasing biochar amendment rates led to an increase in infiltration rate only for the CW biochar at the silt loam site. 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Diagnostic plots demonstrated that in about half of the measurements sets, Kfs could be estimated by modeling infiltration as a two-term function of sorptivity and Kfs. In the remaining plots, additional unknown factors that influenced infiltration prevented estimation of Kfs, possibly due to air entrapment, soil layering, or ring insertion effects in the remaining experiments. Increasing biochar amendment rates led to an increase in infiltration rate only for the CW biochar at the silt loam site. 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Data location: GeoPlatform (\"https://www.geoplatform.gov/\") and EPA Environmental Dataset Gateway (https://edg.epa.gov/). Abstract: We apply the hydrologic landscapes (HL) concept to assess the hydrologic vulnerability of the western United States (U.S.) to projected climate conditions. Our goal is to understand the potential impacts for stakeholder-defined interests across large geographic areas. The basic assumption of the HL approach is that catchments that share similar physical and climatic characteristics are expected to have similar hydrologic characteristics. We map climate vulnerability by integrating the HL approach into a retrospective analysis of historical data to assess variability in future climate projections and hydrology, which includes temperature, precipitation, potential evapotranspiration, snow accumulation, climatic moisture, surplus water, and seasonality of water surplus. Projections that are not within two-standard deviations of the historical decadal average contribute to the vulnerability index for each metric. The resulting vulnerability maps show that temperature and potential evapotranspiration are consistently projected to have high vulnerability indices for the western U.S. Precipitation vulnerability is not as spatially-uniform as temperature. The highest elevation areas with snow are projected to experience significant changes in snow accumulation. The seasonality vulnerability map shows that specific mountainous areas in the West are most prone to changes in seasonality, whereas many transitional terrains are moderately susceptible. This paper illustrates how the HL approach can help assess climatic and hydrologic vulnerability across large spatial scales. By combining the HL concept and climate vulnerability analyses, we provide a planning approach that could allow resource managers to consider how future climate conditions may impact important economic and conservation resources. Purpose: These data were created in support of the US EPA\u2019s ACE CIVA 2.3, Task Project (QAPP: E-WED-0030854). However, these climate data and hydrologic landscape summaries should have broad applicability for hydrological, geomorphic, or ecological modeling, management, and restoration. 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Data location: GeoPlatform (\"https://www.geoplatform.gov/\") and EPA Environmental Dataset Gateway (https://edg.epa.gov/). Abstract: We apply the hydrologic landscapes (HL) concept to assess the hydrologic vulnerability of the western United States (U.S.) to projected climate conditions. Our goal is to understand the potential impacts for stakeholder-defined interests across large geographic areas. The basic assumption of the HL approach is that catchments that share similar physical and climatic characteristics are expected to have similar hydrologic characteristics. We map climate vulnerability by integrating the HL approach into a retrospective analysis of historical data to assess variability in future climate projections and hydrology, which includes temperature, precipitation, potential evapotranspiration, snow accumulation, climatic moisture, surplus water, and seasonality of water surplus. 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The last download of the species locations occurred in November 2020.","distribution_titles":["EPA GeoPlatform Hosted Feature Service","EPA Geoplatform Item page"],"harvest_record":"https://catalog.data.gov/harvest_record/e365ae1f-03ef-437b-b2c1-3dd32656eba9","harvest_record_raw":"https://catalog.data.gov/harvest_record/e365ae1f-03ef-437b-b2c1-3dd32656eba9/raw","harvest_record_transformed":"https://catalog.data.gov/harvest_record/e365ae1f-03ef-437b-b2c1-3dd32656eba9/transformed","has_download":false,"has_spatial":true,"identifier":"https://edg.epa.gov/WAFer_harvest/ISO/ocspp-geo-records_Endangered_Species_Critical_Habitat_Areas.xml","keyword":["United States","Agriculture","Biology","Conservation","Ecology","Ecosystem","Environment","Exposure","Hazards","Land","Modeling","Pesticides","Regulatory","Risk","Toxics","Water","020:083","Downloadable Data"],"last_harvested_date":"2026-09-27T20:37:25.038474","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, Office of Pesticide Programs","slug":"critical-habitat-for-endangered-species","spatial_centroid":{"lat":29.738139,"lon":0.10364840000000583},"spatial_shape":{"coordinates":[[[[179.776438,-14.548618],[180.0,-14.548618],[180.0,74.024896],[179.776438,74.024896],[179.776438,-14.548618]]],[[[-180.0,74.024896],[-180.0,-14.548618],[-179.146415,-14.548618],[-179.146415,74.024896],[-180.0,74.024896]]]],"type":"MultiPolygon"},"theme":["geospatial"],"title":"Critical Habitat for Endangered Species","type":"dataset"},{"_score":10.053443,"_sort":[1790472756481,10.053443,0,"d2a41847-8a2e-4d32-b875-f8b738c3d850"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Jacob A Fleck","hasEmail":"mailto:jafleck@usgs.gov"},"description":"Little is known about mercury concentrations at bay margins, and how climate change, including changes in temperature and precipitation, will affect mercury exposure and methylmercury (MeHg) production. In addition, the San Francisco South Bay Salt Ponds Restoration Program (SBSPRP) needs more efficient and effective mercury monitoring approaches at larger spatial scales to understand changes in mercury at a regional level. The goal of this new project, a collaboration between the USGS Western Geographic Science Center, Water Mission Area, and the California Water Science Center (CAWSC), is to develop the capacity to map total mercury (THg) and MeHg in South San Francisco Bay (SFB) through the satellite remote sensing (Sentinel-2) of two known mercury indicators: total suspended solids (TSS) and colored dissolved organic matter (CDOM). In addition to quantifying the accuracy of this approach, this research aims in South SFB using the Sentinel-2 satellite in order to 1) improve understanding of region-wide mercury spatial and temporal trends associated with weather events and wetland restoration management activities, and 2) improve mercury monitoring efficiencies and capabilities moving forward. One main project objective is to assess the capacity to detect anomalies in remotely sensed TSS, CDOM, and mercury species associated with recent weather events or restoration activities through time series analysis.  \nThe optical measurements reported here were collected to aid in the characterization of water sources and mixtures and establish proxies (surrogates) for mercury and methylmercury concentrations and to provide ground-truthing for remotely sensed models of dissolved organic carbon (DOC) concentrations. Data are compiled into five tables: 1) full fluorescence spectra in vectorized format (LSB_Hg_RS_EEMs_vectors.csv), 2) full absorbance spectra for 1 centimeter (cm) path measurements (LSB_Hg_RS_1cm_ABS_scans.csv), 3) full absorbance spectra for 10 cm path measurements (SSFB_Hg_RS_10cm_ABS_scans.csv), 4) absorption coefficients derived from the 10cm path measurements (SSFB_Hg_RS_10cm_ag_scans.csv), and 5) summary file of commonly extracted optical indicators and calculated wavelength-array values derived from the optical data that correspond to arrays measured by field-based sensors for use in statistical analyses and model development (LSB_Hg_RS_OMRL_Sample_Summary.csv).","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P13JOXXA","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.6a1f4a72b66b018da518f7ee.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_6a1f4a72b66b018da518f7ee","keyword":["Absorbance","Aqualog","Dissolved Organic Matter","Fluorescence","Hydrology","USGS:6a1f4a72b66b018da518f7ee","Water Quality","environment","geoscientificInformation"],"modified":"2026-09-22T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-122.4200, 37.4000, -121.9000, 37.6400","theme":["geospatial"],"title":"Optical measurements for surface water samples collected within South San Francisco Bay in support of mercury modeling"},"description":"Little is known about mercury concentrations at bay margins, and how climate change, including changes in temperature and precipitation, will affect mercury exposure and methylmercury (MeHg) production. 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The objective of this research was to better understand some of the ecological implications of mangrove forest migration and salt marsh displacement. The potential ecological effects of mangrove migration are diverse ranging from important biotic impacts (e.g., coastal fisheries, land bird migration; colonial nesting wading birds) to ecosystem stability (e.g., response to sea level rise and drought; habitat loss; coastal protection) to biogeochemical processes (e.g., carbon storage; water quality). In this research, our focus was on the impact of mangrove forest migration on coastal wetland soil processes and the consequent implications for coastal wetland responses to sea level rise, ecosystem resilience, and carbon storage. Our study specifically addressed the following questions: (1) How do ecological processes and ecosystem properties differ between salt marshes and mangrove forests; (2) As mangrove forests develop, how do their ecosystem properties change and how do these properties compare to salt marshes; (3) How do plant-soil interactions across mangrove forest structural gradients differ among three distinct locations that span the northern Gulf of Mexico; and (4) What are the implications of mangrove forest encroachment and development into salt marsh in terms of soil development, carbon and nitrogen storage, and soil strength? To address these questions, we utilized the salt marshes and natural mangrove forest structural gradients present at three distinct locations in the northern Gulf of Mexico: Cedar Key (Florida), Port Fourchon (Louisiana), and Port Aransas (Texas). Each of these locations represents a distinct combination of climate-driven abiotic conditions. We quantified relationships between plant community composition and structure, soil and porewater physicochemical properties, hydroperiod, and climatic conditions. The suite of measurements that we collected provide initial insights into how different geographic areas of an ecotone, with different environmental conditions, may be impacted by mangrove forest expansion and development, and how these changes may alter the supply of specific ecosystem goods and services. 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The objective of this research was to better understand some of the ecological implications of mangrove forest migration and salt marsh displacement. The potential ecological effects of mangrove migration are diverse ranging from important biotic impacts (e.g., coastal fisheries, land bird migration; colonial nesting wading birds) to ecosystem stability (e.g., response to sea level rise and drought; habitat loss; coastal protection) to biogeochemical processes (e.g., carbon storage; water quality). In this research, our focus was on the impact of mangrove forest migration on coastal wetland soil processes and the consequent implications for coastal wetland responses to sea level rise, ecosystem resilience, and carbon storage. Our study specifically addressed the following questions: (1) How do ecological processes and ecosystem properties differ between salt marshes and mangrove forests; (2) As mangrove forests develop, how do their ecosystem properties change and how do these properties compare to salt marshes; (3) How do plant-soil interactions across mangrove forest structural gradients differ among three distinct locations that span the northern Gulf of Mexico; and (4) What are the implications of mangrove forest encroachment and development into salt marsh in terms of soil development, carbon and nitrogen storage, and soil strength? To address these questions, we utilized the salt marshes and natural mangrove forest structural gradients present at three distinct locations in the northern Gulf of Mexico: Cedar Key (Florida), Port Fourchon (Louisiana), and Port Aransas (Texas). Each of these locations represents a distinct combination of climate-driven abiotic conditions. We quantified relationships between plant community composition and structure, soil and porewater physicochemical properties, hydroperiod, and climatic conditions. The suite of measurements that we collected provide initial insights into how different geographic areas of an ecotone, with different environmental conditions, may be impacted by mangrove forest expansion and development, and how these changes may alter the supply of specific ecosystem goods and services. 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The field area is comprised of 311 surveyed points in, on the perimeter of, and surrounding six forest openings next to Coal Creek off Coal Bank Pass in the San Juan Mountains in southwestern Colorado, USA.  These measurements were taken to look at the relationship between snow accumulation and snow melt patterns between forest gaps of various sizes, and forest edges of various sizes (edge of forest gaps).  Canopy metrics, including canopy height, total gap area, mean distance to canopy, canopy closure, leaf area index, non-directional edginess, canopy edginess with a southern aspect, and canopy edginess with a northern aspect were defined using aerial lidar data for the San Juan Mountains and can be found in an affiliated data release titled, \u2018High Resolution Canopy Structure and Density Metrics for Southwest Colorado Derived from 2019 Aerial Lidar.\u2019  These metrics are also included herein for the 311 surveyed points.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P1EAGT6Y","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.66b164fed34e5d7d928b1190.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_66b164fed34e5d7d928b1190","keyword":["San Juan Mountains","Southwest Colorado","USGS:66b164fed34e5d7d928b1190","canopy density","canopy structure","environment","precipitation (atmospheric)","snow depth","snow water equivalent"],"modified":"2024-09-10T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-107.765923, 37.697812, -107.756824, 37.704060","theme":["geospatial"],"title":"Snow Measurements in Specific Canopy Structure Regimes for April 9, 2024, North of Coal Creek, San Juan Mountains, Colorado, USA"},"description":"These data include snow depth and snow water equivalent (SWE) for a field campaign on April 9, 2024.  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We predicted that trees in warmer, lower latitude cities would be in poorer health at lower levels of urbanization than trees at cooler, higher latitudes due to the interaction of urbanization, latitudinal temperature, and herbivory. To evaluate our predictions, we surveyed the abundance of scale insect herbivores on a single, common tree species (Acer rubrum) in eight US cities spanning 10\u00b0 of latitude. We estimated urbanization at two extents, a local one that accounted for the direct effects on an individual tree, and a larger one that captured the surrounding urban landscape.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P1YDVJN2","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.62b9e2d0d34e8f4977cc9f14.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_62b9e2d0d34e8f4977cc9f14","keyword":["USGS:62b9e2d0d34e8f4977cc9f14","acer rubrum","biota","climate","environment","external research support","latitude","pests","urban heat island"],"modified":"2026-09-23T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"theme":["geospatial"],"title":"Scale insect abundance, impervious surface proportions, and temperature data for Acer rubrum study trees"},"description":"In this study, we investigated how the interaction of urbanization, latitudinal warming, and scale insect abundance affected urban tree health. We predicted that trees in warmer, lower latitude cities would be in poorer health at lower levels of urbanization than trees at cooler, higher latitudes due to the interaction of urbanization, latitudinal temperature, and herbivory. To evaluate our predictions, we surveyed the abundance of scale insect herbivores on a single, common tree species (Acer rubrum) in eight US cities spanning 10\u00b0 of latitude. We estimated urbanization at two extents, a local one that accounted for the direct effects on an individual tree, and a larger one that captured the surrounding urban landscape.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/6248918f-efa7-4af0-bc9e-12ce2bfedad5","harvest_record_raw":"https://catalog.data.gov/harvest_record/6248918f-efa7-4af0-bc9e-12ce2bfedad5/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_62b9e2d0d34e8f4977cc9f14","keyword":["USGS:62b9e2d0d34e8f4977cc9f14","acer rubrum","biota","climate","environment","external research support","latitude","pests","urban heat island"],"last_harvested_date":"2026-09-27T01:29:01.809754","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":"scale-insect-abundance-impervious-surface-proportions-and-temperature-data-for-acer-rubrum","spatial_centroid":null,"spatial_shape":null,"theme":["geospatial"],"title":"Scale insect abundance, impervious surface proportions, and temperature data for Acer rubrum study trees","type":"dataset"},{"_score":8.151949,"_sort":[1790472510664,8.151949,4,"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/b50fcbc1-3370-4928-8c1c-f70df12e3847","harvest_record_raw":"https://catalog.data.gov/harvest_record/b50fcbc1-3370-4928-8c1c-f70df12e3847/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":"2026-09-27T01:28:30.664230","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":10.494556,"_sort":[1790472186967,10.494556,5,"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/23a79d3d-35f8-46e6-83b9-28bcdb602251","harvest_record_raw":"https://catalog.data.gov/harvest_record/23a79d3d-35f8-46e6-83b9-28bcdb602251/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":"2026-09-27T01:23:06.967738","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":8.951186,"_sort":[1790472142788,8.951186,1,"a7cdcf8c-59d2-4ff5-af81-9d956a7fbd3a"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Katherine Warnell","hasEmail":"mailto:katie.warnell@duke.edu"},"description":"Wild insect pollination has significant positive effects on pollinator-dependent crop production.  While managed honeybees are often used to provide pollination to pollinator-dependent crops, visits by wild insect pollinators have been shown to be more effective in increasing fruit set than managed pollinators, and wild insect pollination increases fruit set even when managed pollinator visitation is high (Garibaldi et al. 2013). The total value of the pollination services provided by wild, native insects has been estimated at $3.07 billion annually (2003 dollars) in the United States (Losey &amp; Vaughan 2006).\nTo assess the spatial distribution of potential wild insect pollination, we mapped the supply of potential wild pollinator habitat (forest, grassland, wetland, and shrubland land cover types) and the demand for pollination (directly pollinator-dependent crops).  A foraging travel distance for temperate native bees (1308 meters) was used to estimate relative pollinator activity on cropland based on distance from habitat.  We also calculated the proportion of pollinator habitat within pollinator travel distance of crops.  Methods for this analysis were adapted from the Gulf Coastal Plains and Ozarks Landscape Conservation Cooperative mapping project (Olander et al. 2017).\nThis information was summarized by county and subwatershed (HUC 12) to identify regional priority areas for conservation and restoration of pollinator habitat. Datasets provided include county and subwatershed shapefiles identifying priority areas and including attributes used to select priorities, and raster datasets used to calculate those attributes.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.21429/69zz-7f78","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.5d288fcee4b0941bde65132a.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_5d288fcee4b0941bde65132a","keyword":["Alabama","Arkansas","Florida","Georgia","Louisiana","Mississippi","Missouri","North Carolina","South Carolina","Tennessee","USGS:5d288fcee4b0941bde65132a","environment","farming","geospatial datasets","habitats","natural resource management","pollination","pollinators","remediation"],"modified":"2026-09-23T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-95.8139, 23.8934, -74.5003, 40.6853","theme":["geospatial"],"title":"Conservation and Restoration Priorities for Wild Pollinator Habitat"},"description":"Wild insect pollination has significant positive effects on pollinator-dependent crop production.  While managed honeybees are often used to provide pollination to pollinator-dependent crops, visits by wild insect pollinators have been shown to be more effective in increasing fruit set than managed pollinators, and wild insect pollination increases fruit set even when managed pollinator visitation is high (Garibaldi et al. 2013). The total value of the pollination services provided by wild, native insects has been estimated at $3.07 billion annually (2003 dollars) in the United States (Losey &amp; Vaughan 2006).\nTo assess the spatial distribution of potential wild insect pollination, we mapped the supply of potential wild pollinator habitat (forest, grassland, wetland, and shrubland land cover types) and the demand for pollination (directly pollinator-dependent crops).  A foraging travel distance for temperate native bees (1308 meters) was used to estimate relative pollinator activity on cropland based on distance from habitat.  We also calculated the proportion of pollinator habitat within pollinator travel distance of crops.  Methods for this analysis were adapted from the Gulf Coastal Plains and Ozarks Landscape Conservation Cooperative mapping project (Olander et al. 2017).\nThis information was summarized by county and subwatershed (HUC 12) to identify regional priority areas for conservation and restoration of pollinator habitat. 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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/f2e7e4a2-2265-4a84-a0f6-19a1dba2f857","harvest_record_raw":"https://catalog.data.gov/harvest_record/f2e7e4a2-2265-4a84-a0f6-19a1dba2f857/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":"2026-09-27T01:22:05.115109","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":10.285824,"_sort":[1790472073006,10.285824,3,"1d2dba95-81b9-4104-9d66-3e588ee978ec"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Ryan F. 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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.  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For 41 estuaries in the northern Gulf of Mexico (i.e., the USA gulf coast), we quantified and compared the area available for the landward migration of tidal saline wetlands and the area where urban development is expected to prevent migration (coastal squeeze), under three alternative future sea-level rise scenarios (0.5-, 1.0-, and 1.5-m by 2100).","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/F7S75F7K","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.5989fd82e4b09fa1cb0cc903.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_5989fd82e4b09fa1cb0cc903","keyword":["Alabama","Florida","Gulf of Mexico","Louisiana","Mississippi","North America","Texas","USGS:5989fd82e4b09fa1cb0cc903","United States","biota","climate change","effects of climate change","environment","estuaries","estuary","geospatial datasets","natural resource management","planning Cadastre","sea level change","sea-level change","wetlands"],"modified":"2026-09-23T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-97.9958, 24.1683, -80.3992, 32.0006","theme":["geospatial"],"title":"Landward migration of tidal saline wetlands with sea-level rise and urbanization: a comparison of northern Gulf of Mexico estuaries"},"description":"Coastal wetland ecosystems are expected to migrate landward in response to accelerated sea-level rise. 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For 41 estuaries in the northern Gulf of Mexico (i.e., the USA gulf coast), we quantified and compared the area available for the landward migration of tidal saline wetlands and the area where urban development is expected to prevent migration (coastal squeeze), under three alternative future sea-level rise scenarios (0.5-, 1.0-, and 1.5-m by 2100).","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/f6e7a650-da7b-43ee-96a5-885d91133433","harvest_record_raw":"https://catalog.data.gov/harvest_record/f6e7a650-da7b-43ee-96a5-885d91133433/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_5989fd82e4b09fa1cb0cc903","keyword":["Alabama","Florida","Gulf of Mexico","Louisiana","Mississippi","North America","Texas","USGS:5989fd82e4b09fa1cb0cc903","United States","biota","climate change","effects of climate change","environment","estuaries","estuary","geospatial datasets","natural resource management","planning Cadastre","sea level change","sea-level change","wetlands"],"last_harvested_date":"2026-09-27T01:20:42.900703","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":"landward-migration-of-tidal-saline-wetlands-with-sea-level-rise-and-urbanization-a-compari","spatial_centroid":{"lat":27.30122,"lon":-90.95716},"spatial_shape":{"coordinates":[[[-97.9958,24.1683],[-97.9958,32.0006],[-80.3992,32.0006],[-80.3992,24.1683],[-97.9958,24.1683]]],"type":"Polygon"},"theme":["geospatial"],"title":"Landward migration of tidal saline wetlands with sea-level rise and urbanization: a comparison of northern Gulf of Mexico estuaries","type":"dataset"},{"_score":9.362732,"_sort":[1790472003689,9.362732,2,"d1a22498-ea4e-4e99-9e84-48b94536504d"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Thomas J. 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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. 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We analyzed forest inventory data and multi-temporal Landsat data from different seasons to create this map. Each value in the map represents a plot ID for an FVS inventory plot that was imputed to a location based on class membership in a class map created with Landsat data. When used with the LANDIS-II model and associated input files, this map will populate each cell with species cohorts of observed ages from the imputed plot inventory information.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P1DGEMFW","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.59b1528ce4b020cdf7d90282.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_59b1528ce4b020cdf7d90282","keyword":["Green Mountains National Forest","USGS:59b1528ce4b020cdf7d90282","Vermont","biota","ecological processes","environment","geospatial datasets","natural resource management"],"modified":"2026-09-24T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-73.3324, 42.6975, -72.6485, 44.2107","theme":["geospatial"],"title":"Initial Forest Community Map of Green Mountains National Forest for LANDIS-II Model, Derived from Landsat and FVS data"},"description":"This raster map represents imputed forest community classes from forest inventory data summarized from the FVS national forest inventory data. 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We analyzed forest inventory data and multi-temporal Landsat data from different seasons to create this map. Each value in the map represents a plot ID for an FVS inventory plot that was imputed to a location based on class membership in a class map created with Landsat data. 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The objective of this research was to better understand some of the ecological implications of mangrove forest migration and salt marsh displacement. The potential ecological effects of mangrove migration are diverse ranging from important biotic impacts (e.g., coastal fisheries, land bird migration; colonial nesting wading birds) to ecosystem stability (e.g., response to sea level rise and drought; habitat loss; coastal protection) to biogeochemical processes (e.g., carbon storage; water quality). In this research, our focus was on the impact of mangrove forest migration on coastal wetland soil processes and the consequent implications for coastal wetland responses to sea level rise, ecosystem resilience, and carbon storage. Our study specifically addressed the following questions: (1) How do ecological processes and ecosystem properties differ between salt marshes and mangrove forests; (2) As mangrove forests develop, how do their ecosystem properties change and how do these properties compare to salt marshes; (3) How do plant-soil interactions across mangrove forest structural gradients differ among three distinct locations that span the northern Gulf of Mexico; and (4) What are the implications of mangrove forest encroachment and development into salt marsh in terms of soil development, carbon and nitrogen storage, and soil strength? To address these questions, we utilized the salt marshes and natural mangrove forest structural gradients present at three distinct locations in the northern Gulf of Mexico: Cedar Key (Florida), Port Fourchon (Louisiana), and Port Aransas (Texas). Each of these locations represents a distinct combination of climate-driven abiotic conditions. We quantified relationships between plant community composition and structure, soil and porewater physicochemical properties, hydroperiod, and climatic conditions. The suite of measurements that we collected provide initial insights into how different geographic areas of an ecotone, with different environmental conditions, may be impacted by mangrove forest expansion and development, and how these changes may alter the supply of specific ecosystem goods and services. This file includes the individual-level tall tree stratum vegetation data.\nThis work was conducted via a collaborative effort between scientists at the U.S. Geological Survey National Wetland Research Center and the Department of Biology of the University of Louisiana at Lafayette.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P1GDTXUR","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.545bfd63e4b009f8aec9b6ce.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_545bfd63e4b009f8aec9b6ce","keyword":["Cedar Key","Gulf of Mexico","Port Aransas","Port Fourchon","State of Florida","State of Louisiana","State of Texas","USGS:545bfd63e4b009f8aec9b6ce","United States of America","environment","vegetation"],"modified":"2026-09-22T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"theme":["geospatial"],"title":"Dataset 3: New vegetation data collection: individual-level tall tree stratum"},"description":"Winter climate change has the potential to have a large impact on coastal wetlands in the southeastern U.S. Warmer winter temperatures and reductions in the intensity of freeze events would likely lead to mangrove forest range expansion and salt marsh displacement in parts of the U.S. Gulf of Mexico and Atlantic coast. 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Our study specifically addressed the following questions: (1) How do ecological processes and ecosystem properties differ between salt marshes and mangrove forests; (2) As mangrove forests develop, how do their ecosystem properties change and how do these properties compare to salt marshes; (3) How do plant-soil interactions across mangrove forest structural gradients differ among three distinct locations that span the northern Gulf of Mexico; and (4) What are the implications of mangrove forest encroachment and development into salt marsh in terms of soil development, carbon and nitrogen storage, and soil strength? To address these questions, we utilized the salt marshes and natural mangrove forest structural gradients present at three distinct locations in the northern Gulf of Mexico: Cedar Key (Florida), Port Fourchon (Louisiana), and Port Aransas (Texas). Each of these locations represents a distinct combination of climate-driven abiotic conditions. We quantified relationships between plant community composition and structure, soil and porewater physicochemical properties, hydroperiod, and climatic conditions. The suite of measurements that we collected provide initial insights into how different geographic areas of an ecotone, with different environmental conditions, may be impacted by mangrove forest expansion and development, and how these changes may alter the supply of specific ecosystem goods and services. This file includes the individual-level tall tree stratum vegetation data.\nThis work was conducted via a collaborative effort between scientists at the U.S. Geological Survey National Wetland Research Center and the Department of Biology of the University of Louisiana at Lafayette.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/3699dd4e-da08-47ae-98b9-dbb6086b945d","harvest_record_raw":"https://catalog.data.gov/harvest_record/3699dd4e-da08-47ae-98b9-dbb6086b945d/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_545bfd63e4b009f8aec9b6ce","keyword":["Cedar Key","Gulf of Mexico","Port Aransas","Port Fourchon","State of Florida","State of Louisiana","State of Texas","USGS:545bfd63e4b009f8aec9b6ce","United States of America","environment","vegetation"],"last_harvested_date":"2026-09-27T01:11:52.226818","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":"dataset-3-new-vegetation-data-collection-individual-level-tall-tree-stratum","spatial_centroid":null,"spatial_shape":null,"theme":["geospatial"],"title":"Dataset 3: New vegetation data collection: individual-level tall tree stratum","type":"dataset"},{"_score":8.779042,"_sort":[1790471398268,8.779042,1,"0147c0d3-3c9d-41ef-a9fc-e698db43f52f"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Nicholas M Enwright","hasEmail":"mailto:enwrightn@usgs.gov"},"description":"This data release includes digital elevation models (DEMs) that were created using Monte Carlo simulations with the aim to reduce elevation overestimation in coastal wetlands at Plum Island, MA. We evaluated the performance of coastal wetland elevation refinement by using bare earth DEMs and DEMs created from the last return from the light detection and ranging (lidar) point cloud, hereafter referred to as the minimum bin DEM. We additionally created DEMs for a range of resolutions \u2013 3 m, 5 m, and 10 m. The elevation source data were from 2021. Using high-accuracy elevation data collected from 2014 to 2023 by the Plum Island Ecosystems Long-Term Ecological Research program and others, we assessed initial error of the DEMs. For each DEM, we used Monte Carlo simulation with 1,000 iterations to create new DEM realizations. Next, we summarized the 1,000 DEM realizations by calculating the 5th \u2013 95th percentiles (that is, median and every 5th percentile) of elevation by pixel across all iterations. This data release includes all percentiles from each DEM type and resolution. We used the previously mentioned in-situ elevation observations to assess the performance of the DEM error reduction. These DEMs are recommended for use in wetland modeling over the full range of percentiles.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P1ED6XKF","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.685aa9b1d4be024a9b2868d4.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_685aa9b1d4be024a9b2868d4","keyword":["Massachusetts","Plum Island Estuary","USGS:685aa9b1d4be024a9b2868d4","digital elevation models","ecology","elevation","environment","geography","land use change","mathematical simulation","remote sensing","sea-level change","spatial analysis","wetland ecosystems"],"modified":"2026-09-22T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-70.9453, 42.6339, -70.7315, 42.8400","theme":["geospatial"],"title":"Digital elevation models with elevation uncertainty treatment, Plum Island Estuary, Massachusetts, 2021 (ver. 2.0, May 2026)"},"description":"This data release includes digital elevation models (DEMs) that were created using Monte Carlo simulations with the aim to reduce elevation overestimation in coastal wetlands at Plum Island, MA. We evaluated the performance of coastal wetland elevation refinement by using bare earth DEMs and DEMs created from the last return from the light detection and ranging (lidar) point cloud, hereafter referred to as the minimum bin DEM. We additionally created DEMs for a range of resolutions \u2013 3 m, 5 m, and 10 m. The elevation source data were from 2021. Using high-accuracy elevation data collected from 2014 to 2023 by the Plum Island Ecosystems Long-Term Ecological Research program and others, we assessed initial error of the DEMs. For each DEM, we used Monte Carlo simulation with 1,000 iterations to create new DEM realizations. Next, we summarized the 1,000 DEM realizations by calculating the 5th \u2013 95th percentiles (that is, median and every 5th percentile) of elevation by pixel across all iterations. This data release includes all percentiles from each DEM type and resolution. We used the previously mentioned in-situ elevation observations to assess the performance of the DEM error reduction. These DEMs are recommended for use in wetland modeling over the full range of percentiles.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/f2647df0-4de9-4b8d-b418-905980586ce6","harvest_record_raw":"https://catalog.data.gov/harvest_record/f2647df0-4de9-4b8d-b418-905980586ce6/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_685aa9b1d4be024a9b2868d4","keyword":["Massachusetts","Plum Island Estuary","USGS:685aa9b1d4be024a9b2868d4","digital elevation models","ecology","elevation","environment","geography","land use change","mathematical simulation","remote sensing","sea-level change","spatial analysis","wetland ecosystems"],"last_harvested_date":"2026-09-27T01:09:58.268675","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":"digital-elevation-models-with-elevation-uncertainty-treatment-plum-island-estuary-mas-2021","spatial_centroid":{"lat":42.71634,"lon":-70.85978},"spatial_shape":{"coordinates":[[[-70.9453,42.6339],[-70.9453,42.84],[-70.7315,42.84],[-70.7315,42.6339],[-70.9453,42.6339]]],"type":"Polygon"},"theme":["geospatial"],"title":"Digital elevation models with elevation uncertainty treatment, Plum Island Estuary, Massachusetts, 2021 (ver. 2.0, May 2026)","type":"dataset"},{"_score":9.510656,"_sort":[1790471345783,9.510656,0,"c6f56e9d-cdaf-42c8-bcea-255b115917ce"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Jared Oyler","hasEmail":"mailto:jaredwo@gmail.com"},"description":"Dataset includes daily estimated climate data for a study site near Seeley Lake MT, USA. We used a locally calibrated temperature index snowfall-snowmelt model to estimate both past and future daily snow water equivalent (SWE) at our study site.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P19ZFWYG","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.54355bc9e4b0a4f4b46a252e.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_54355bc9e4b0a4f4b46a252e","keyword":["Montana","Seeley Lake","USGS:54355bc9e4b0a4f4b46a252e","atmospheric and climatic processes","climate change","environment","external research support","precipitation (atmospheric)","snow","swe","temperature"],"modified":"2026-09-24T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"theme":["geospatial"],"title":"Daily Temperature, Precipitation, and Snow Data, Montana Study Site 1948-2012"},"description":"Dataset includes daily estimated climate data for a study site near Seeley Lake MT, USA. We used a locally calibrated temperature index snowfall-snowmelt model to estimate both past and future daily snow water equivalent (SWE) at our study site.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/fa6548df-7512-488a-9825-239cad18f668","harvest_record_raw":"https://catalog.data.gov/harvest_record/fa6548df-7512-488a-9825-239cad18f668/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_54355bc9e4b0a4f4b46a252e","keyword":["Montana","Seeley Lake","USGS:54355bc9e4b0a4f4b46a252e","atmospheric and climatic processes","climate change","environment","external research support","precipitation (atmospheric)","snow","swe","temperature"],"last_harvested_date":"2026-09-27T01:09:05.783792","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-temperature-precipitation-and-snow-data-montana-study-site-1948-2012","spatial_centroid":null,"spatial_shape":null,"theme":["geospatial"],"title":"Daily Temperature, Precipitation, and Snow Data, Montana Study Site 1948-2012","type":"dataset"},{"_score":8.906205,"_sort":[1790471328064,8.906205,3,"dd71b40f-5bbe-4d59-ad74-b1800a70714f"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Jason M. Fine","hasEmail":"mailto:jmfine@usgs.gov"},"description":"An existing three-dimensional model (MODFLOW-2000) by Fine, Petkewich, and Campbell (2017) \n(https://doi.org/10.3133/sir20175128) was used to evaluate 7 water-management scenarios and \npredict the effects on the groundwater flow and groundwater-level conditions in the Mount Pleasant, \nSouth Carolina area. This model was originally developed in 2007, by Petkewich and Campbell \n(https://pubs.er.usgs.gov/publication/sir20075126), then updated and recalibrated to conditions \nfrom 1900 to 2015.  Results of six previous scenario simulations (scenarios 1-6) for the Mount \nPleasant Water Works are published in a U.S. Geological Survey (USGS) Scientific Investigations \nReport (https://doi.org/10.3133/sir20175128).  The archived model input and output files are available \nin a USGS data release (https://doi.org/10.5066/F7S181FC). \n\t\t\nSeven additional MODFLOW-2000 scenarios (numbered 7-13), using this updated and recalibrated \nmodel, were developed to evaluate different withdrawal strategies which are included in this data \nrelease: (7) Mount Pleasant Waterworks bringing online a new well (located at the old well 5 location) \nat 3.51 million gallons per day (Mgal/d) in 2025; (8) Maximizing withdrawals from Mount Pleasant \nWaterworks wells 2 and 5 (3.51 Mgal/d each) in 2020 and 2025, respectively; (9) Same as Scenario \n7, but removing well 3 from production in 2025; (10) Same as Scenario 9, but removing well 4 from \nproduction in 2025 (11) Same as Scenario 7, but converting well 3 to an injection well in 2025 (12) \nSame as Scenario 11, but converting well 4 to an injection well in 2030; and (13) Same as scenario \n8, but with two injection wells added (one in 2025 and one in 2035) to Mount Pleasant Waterworks \nwell field. Nine alternate simulations for scenarios 11-13 (three MODFLOW and six MODPATH) \nwere done to evaluate the effects of different porosity on the groundwater flow system, water levels, \nand the time-of-travel of particles from injection wells to the main water source.  This USGS data \nrelease contains all the input and output files for the simulations described above and in the \nreadme.txt file of this data release (https://doi.org/10.5066/P9GZEE4E).","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P9GZEE4E","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.6ba49343-2436-45ea-b0d8-ec6f7d84577b.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_6ba49343-2436-45ea-b0d8-ec6f7d84577b","keyword":["Charleston County","Groundwater","Groundwater Model","InlandWaters","MODFLOW-2000","MODPATH","Middendorf aquifer","Mount Pleasant","South Carolina","USGS:6ba49343-2436-45ea-b0d8-ec6f7d84577b","environment","geoscientificInformation","inlandWaters","usgsgroundwatermodel"],"modified":"2020-11-17T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-83.786434, 29.923548, -76.289479, 35.881171","theme":["geospatial"],"title":"MODFLOW-2000 and MODPATH model data sets used in scenarios of groundwater flow and pumping (1900-2500) near Mount Pleasant, South Carolina"},"description":"An existing three-dimensional model (MODFLOW-2000) by Fine, Petkewich, and Campbell (2017) \n(https://doi.org/10.3133/sir20175128) was used to evaluate 7 water-management scenarios and \npredict the effects on the groundwater flow and groundwater-level conditions in the Mount Pleasant, \nSouth Carolina area. This model was originally developed in 2007, by Petkewich and Campbell \n(https://pubs.er.usgs.gov/publication/sir20075126), then updated and recalibrated to conditions \nfrom 1900 to 2015.  Results of six previous scenario simulations (scenarios 1-6) for the Mount \nPleasant Water Works are published in a U.S. Geological Survey (USGS) Scientific Investigations \nReport (https://doi.org/10.3133/sir20175128).  The archived model input and output files are available \nin a USGS data release (https://doi.org/10.5066/F7S181FC). \n\t\t\nSeven additional MODFLOW-2000 scenarios (numbered 7-13), using this updated and recalibrated \nmodel, were developed to evaluate different withdrawal strategies which are included in this data \nrelease: (7) Mount Pleasant Waterworks bringing online a new well (located at the old well 5 location) \nat 3.51 million gallons per day (Mgal/d) in 2025; (8) Maximizing withdrawals from Mount Pleasant \nWaterworks wells 2 and 5 (3.51 Mgal/d each) in 2020 and 2025, respectively; (9) Same as Scenario \n7, but removing well 3 from production in 2025; (10) Same as Scenario 9, but removing well 4 from \nproduction in 2025 (11) Same as Scenario 7, but converting well 3 to an injection well in 2025 (12) \nSame as Scenario 11, but converting well 4 to an injection well in 2030; and (13) Same as scenario \n8, but with two injection wells added (one in 2025 and one in 2035) to Mount Pleasant Waterworks \nwell field. Nine alternate simulations for scenarios 11-13 (three MODFLOW and six MODPATH) \nwere done to evaluate the effects of different porosity on the groundwater flow system, water levels, \nand the time-of-travel of particles from injection wells to the main water source.  This USGS data \nrelease contains all the input and output files for the simulations described above and in the \nreadme.txt file of this data release (https://doi.org/10.5066/P9GZEE4E).","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/ed893c6a-f508-4652-923f-c18a43246389","harvest_record_raw":"https://catalog.data.gov/harvest_record/ed893c6a-f508-4652-923f-c18a43246389/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_6ba49343-2436-45ea-b0d8-ec6f7d84577b","keyword":["Charleston County","Groundwater","Groundwater Model","InlandWaters","MODFLOW-2000","MODPATH","Middendorf aquifer","Mount Pleasant","South Carolina","USGS:6ba49343-2436-45ea-b0d8-ec6f7d84577b","environment","geoscientificInformation","inlandWaters","usgsgroundwatermodel"],"last_harvested_date":"2026-09-27T01:08:48.064546","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":"modflow-2000-and-modpath-model-data-sets-used-in-scenarios-of-groundwater-flow-and-pumping","spatial_centroid":{"lat":32.3065972,"lon":-80.78765200000001},"spatial_shape":{"coordinates":[[[-83.786434,29.923548],[-83.786434,35.881171],[-76.289479,35.881171],[-76.289479,29.923548],[-83.786434,29.923548]]],"type":"Polygon"},"theme":["geospatial"],"title":"MODFLOW-2000 and MODPATH model data sets used in scenarios of groundwater flow and pumping (1900-2500) near Mount Pleasant, South Carolina","type":"dataset"},{"_score":10.314411,"_sort":[1790471263217,10.314411,0,"113572f2-1b62-4bb7-b4fd-25fbfc869207"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Ralph W Tingley","hasEmail":"mailto:rtingley@usgs.gov"},"description":"Adult walleye presence/absence in stream reaches of Wisconsin (1989-2017). 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This dataset represents geology\nof the High Plains study region.  The original dataset was presented\non a CD-ROM intended for use with ARC/INFO.  The files presented here\nconsist of HPGEO--ARC/INFO export format files, hpgeology_shp--shape-\nfiles of coverages and hpgeosdts--SDTS formatted covers.  The folder\nHPGEO contains amls, and color conventions for the coverages. They are\nnot necessary to display the coverages and are not included in the SDTS\nfolder or the shapefile folder.  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Our study specifically addressed the following questions: (1) How do ecological processes and ecosystem properties differ between salt marshes and mangrove forests; (2) As mangrove forests develop, how do their ecosystem properties change and how do these properties compare to salt marshes; (3) How do plant-soil interactions across mangrove forest structural gradients differ among three distinct locations that span the northern Gulf of Mexico; and (4) What are the implications of mangrove forest encroachment and development into salt marsh in terms of soil development, carbon and nitrogen storage, and soil strength? To address these questions, we utilized the salt marshes and natural mangrove forest structural gradients present at three distinct locations in the northern Gulf of Mexico: Cedar Key (Florida), Port Fourchon (Louisiana), and Port Aransas (Texas). Each of these locations represents a distinct combination of climate-driven abiotic conditions. We quantified relationships between plant community composition and structure, soil and porewater physicochemical properties, hydroperiod, and climatic conditions. The suite of measurements that we collected provide initial insights into how different geographic areas of an ecotone, with different environmental conditions, may be impacted by mangrove forest expansion and development, and how these changes may alter the supply of specific ecosystem goods and services. \nThis file includes the scanned laboratory notes associated with this project.\nThis work was conducted via a collaborative effort between scientists at the U.S. Geological Survey National Wetland Research Center and the Department of Biology of the University of Louisiana at Lafayette.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P138EI2Z","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.545bf9b3e4b009f8aec9b5a5.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_545bf9b3e4b009f8aec9b5a5","keyword":["Florida","Gulf of Mexico","Louisiana","Texas","USGS:545bf9b3e4b009f8aec9b5a5","climate change","ecology","ecosystem monitoring","environment","forest","mangrove","migration","moisture","soil","wetlands"],"modified":"2026-09-22T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-97.1401, 27.8300, -83.0298, 29.2000","theme":["geospatial"],"title":"Laboratory Notes: Scanned Laboratory Notebook Pages for the following project - Ecological implications of mangrove forest migration in the southeastern US (2012-2-13)"},"description":"Winter climate change has the potential to have a large impact on coastal wetlands in the southeastern U.S. Warmer winter temperatures and reductions in the intensity of freeze events would likely lead to mangrove forest range expansion and salt marsh displacement in parts of the U.S. Gulf of Mexico and Atlantic coast. The objective of this research was to better understand some of the ecological implications of mangrove forest migration and salt marsh displacement. The potential ecological effects of mangrove migration are diverse ranging from important biotic impacts (e.g., coastal fisheries, land bird migration; colonial nesting wading birds) to ecosystem stability (e.g., response to sea level rise and drought; habitat loss; coastal protection) to biogeochemical processes (e.g., carbon storage; water quality). In this research, our focus was on the impact of mangrove forest migration on coastal wetland soil processes and the consequent implications for coastal wetland responses to sea level rise, ecosystem resilience, and carbon storage. Our study specifically addressed the following questions: (1) How do ecological processes and ecosystem properties differ between salt marshes and mangrove forests; (2) As mangrove forests develop, how do their ecosystem properties change and how do these properties compare to salt marshes; (3) How do plant-soil interactions across mangrove forest structural gradients differ among three distinct locations that span the northern Gulf of Mexico; and (4) What are the implications of mangrove forest encroachment and development into salt marsh in terms of soil development, carbon and nitrogen storage, and soil strength? To address these questions, we utilized the salt marshes and natural mangrove forest structural gradients present at three distinct locations in the northern Gulf of Mexico: Cedar Key (Florida), Port Fourchon (Louisiana), and Port Aransas (Texas). Each of these locations represents a distinct combination of climate-driven abiotic conditions. We quantified relationships between plant community composition and structure, soil and porewater physicochemical properties, hydroperiod, and climatic conditions. The suite of measurements that we collected provide initial insights into how different geographic areas of an ecotone, with different environmental conditions, may be impacted by mangrove forest expansion and development, and how these changes may alter the supply of specific ecosystem goods and services. \nThis file includes the scanned laboratory notes associated with this project.\nThis work was conducted via a collaborative effort between scientists at the U.S. Geological Survey National Wetland Research Center and the Department of Biology of the University of Louisiana at Lafayette.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/eb9f2a86-118a-49eb-9018-418c24b7ee2f","harvest_record_raw":"https://catalog.data.gov/harvest_record/eb9f2a86-118a-49eb-9018-418c24b7ee2f/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_545bf9b3e4b009f8aec9b5a5","keyword":["Florida","Gulf of Mexico","Louisiana","Texas","USGS:545bf9b3e4b009f8aec9b5a5","climate change","ecology","ecosystem monitoring","environment","forest","mangrove","migration","moisture","soil","wetlands"],"last_harvested_date":"2026-09-27T00:55:02.982569","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":"laboratory-notes-scanned-laboratory-notebook-pages-for-the-following-project-ecological-13","spatial_centroid":{"lat":28.377999999999997,"lon":-91.49598},"spatial_shape":{"coordinates":[[[-97.1401,27.83],[-97.1401,29.2],[-83.0298,29.2],[-83.0298,27.83],[-97.1401,27.83]]],"type":"Polygon"},"theme":["geospatial"],"title":"Laboratory Notes: Scanned Laboratory Notebook Pages for the following project - Ecological implications of mangrove forest migration in the southeastern US (2012-2-13)","type":"dataset"},{"_score":8.413892,"_sort":[1790470427274,8.413892,0,"0f524498-bdd3-444f-9550-1532c3900d6f"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Nicholas M Enwright","hasEmail":"mailto:enwrightn@usgs.gov"},"description":"The Barrier Island Comprehensive Monitoring (BICM) program was developed by Louisiana\u2019s Coastal Protection and Restoration Authority (CPRA) and is implemented as a component of the System Wide Assessment and Monitoring Program (SWAMP). The program uses both historical data and contemporary data collections to assess and monitor changes in the aerial and subaqueous extent of islands, habitat types, sediment texture and geotechnical properties, environmental processes, and vegetation composition. Examples of BICM datasets include still and video aerial photography for documenting shoreline changes, shoreline positions, habitat mapping, land change analyses, light detection and ranging (lidar) surveys for topographic elevations, single-beam and swath bathymetry, and sediment grab samples. For more information about the BICM program, see Kindinger and others (2013). \nThe U.S. Geological Survey, Wetland and Aquatic Research Center provides support to the BICM program through the development of habitat map products using aerial imagery and lidar elevation data and assessing change in habitats over time. These data provide a snapshot of barrier island habitats and can be combined with other past and/or future maps to monitor these valuable natural resources over time. Previous efforts of this habitat mapping program included developing habitat maps for 2008 and 2015\u20132016 for the following BICM regions (Enwright and others, 2020): 1) West Chenier; 2) East Chenier; 3) Acadiana Bays (only Marsh Island); 4) Early Lafourche Delta; 5) Late Lafourche Delta; 6) Modern Delta (only Chaland Headland and Shell Island); and 7) Chandeleur Islands. Additionally, a habitat change analysis was conducted comparing reaches mapped in 2008 and 2015\u20132016. The current effort of this habitat mapping program includes developing habitat maps for 2021 for the previously mentioned regions. A habitat change analysis will be conducted comparing reaches mapped 2015\u20132016 and 2021. The BICM program has developed two habitat classification schemes which include a detailed 15-class habitat scheme and a general eight-class habitat scheme. The detailed scheme was developed specifically for this habitat mapping effort and builds off the general scheme used in previous BICM habitat mapping efforts (Fearnley and others, 2009). The additional classes developed in the detailed scheme are primarily used to further delineate various dune habitats, separate marsh and mangrove, and distinguish between beach and unvegetated barrier flat habitats. To ensure comparability between this effort and previous BICM map products, we have crosswalked the detailed classes to general habitat classes previously used by Fearnley and others (2009). \nIn other words, the general habitat classes included in these products were not directly interpreted using aerial imagery and lidar elevation data. Thus, we recommend only using these general habitat classes for analyses that include previous BICM habitat maps (1996\u20132005). For more information about the BICM program, see Kindinger and others (2013). For more details on BICM habitat classes, see the Entity and Attribute Information section of the metadata. Please consult the accompanying readME.txt file for information and recommendations on the contents of this dataset (i.e., dataset and recommended symbology). For more information about the BICM program, see Kindinger and others (2013). \nReferences:\nKindinger, J.L., Buster, N.A., Flocks, J.G., Bernier, J.C., and Kulp, M.A., 2013, Louisiana Barrier Island Comprehensive Monitoring (BICM) program summary report\u2014Data and analyses 2006 through 2010: U.S. Geological Survey Open-File Report 2013\u20131083, 86 p., at https://pubs.usgs.gov/of/2013/1083/.\nEnwright, N.M., SooHoo, W.M., Dugas, J.L., Conzelmann, C.P., Laurenzano, C., Lee, D.M., Mouton, K., and Stelly, S.J., 2020, Louisiana Barrier Island Comprehensive Monitoring Program\u2014Mapping habitats in beach, dune, and intertidal environments along the Louisiana Gulf of Mexico shoreline, 2008 and 2015\u201316: U.S. Geological Survey Open-File Report 2020\u20131030, 57 p., https://doi.org/10.3133/ofr20201030.\nFearnley, S., Brien, L., Martinez, L., Miner, M., Kulp, M., and Penland, S., 2009, Chenier Plain, South-Central Louisiana, and Chandeleur Islands, Habitat mapping and change analysis 1996 to 2005, Part 1\u2014Methods for habitat mapping and change analysis 1996 to 2005\u2014Louisiana Barrier Island Comprehensive Monitoring Program (BICM) 5: New Orleans, University of New Orleans, Pontchartrain Institute for Environmental Sciences, 11 p.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P1ZQP7SN","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.68505a2cd4be025b9e8c6b6a.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_68505a2cd4be025b9e8c6b6a","keyword":["Gulf of America","Louisiana","Louisiana Coastal","Modern Delta Region","Plaquemines Parish","USGS:68505a2cd4be025b9e8c6b6a","barrier islands","barrier vegetation","beach","coastal wetlands","dune","environment","farming","habitat map","mangrove","marsh","planningCadastre","remote sensing","scrub/shrub"],"modified":"2026-09-17T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-89.8837, 29.1798, -89.4280, 29.3839","theme":["geospatial"],"title":"Louisiana Barrier Island Comprehensive Monitoring Program \u2013 2021 habitat map, Modern Delta Region (ver. 2.0, September 2026)"},"description":"The Barrier Island Comprehensive Monitoring (BICM) program was developed by Louisiana\u2019s Coastal Protection and Restoration Authority (CPRA) and is implemented as a component of the System Wide Assessment and Monitoring Program (SWAMP). The program uses both historical data and contemporary data collections to assess and monitor changes in the aerial and subaqueous extent of islands, habitat types, sediment texture and geotechnical properties, environmental processes, and vegetation composition. Examples of BICM datasets include still and video aerial photography for documenting shoreline changes, shoreline positions, habitat mapping, land change analyses, light detection and ranging (lidar) surveys for topographic elevations, single-beam and swath bathymetry, and sediment grab samples. For more information about the BICM program, see Kindinger and others (2013). \nThe U.S. Geological Survey, Wetland and Aquatic Research Center provides support to the BICM program through the development of habitat map products using aerial imagery and lidar elevation data and assessing change in habitats over time. These data provide a snapshot of barrier island habitats and can be combined with other past and/or future maps to monitor these valuable natural resources over time. Previous efforts of this habitat mapping program included developing habitat maps for 2008 and 2015\u20132016 for the following BICM regions (Enwright and others, 2020): 1) West Chenier; 2) East Chenier; 3) Acadiana Bays (only Marsh Island); 4) Early Lafourche Delta; 5) Late Lafourche Delta; 6) Modern Delta (only Chaland Headland and Shell Island); and 7) Chandeleur Islands. Additionally, a habitat change analysis was conducted comparing reaches mapped in 2008 and 2015\u20132016. The current effort of this habitat mapping program includes developing habitat maps for 2021 for the previously mentioned regions. A habitat change analysis will be conducted comparing reaches mapped 2015\u20132016 and 2021. The BICM program has developed two habitat classification schemes which include a detailed 15-class habitat scheme and a general eight-class habitat scheme. The detailed scheme was developed specifically for this habitat mapping effort and builds off the general scheme used in previous BICM habitat mapping efforts (Fearnley and others, 2009). The additional classes developed in the detailed scheme are primarily used to further delineate various dune habitats, separate marsh and mangrove, and distinguish between beach and unvegetated barrier flat habitats. To ensure comparability between this effort and previous BICM map products, we have crosswalked the detailed classes to general habitat classes previously used by Fearnley and others (2009). \nIn other words, the general habitat classes included in these products were not directly interpreted using aerial imagery and lidar elevation data. Thus, we recommend only using these general habitat classes for analyses that include previous BICM habitat maps (1996\u20132005). For more information about the BICM program, see Kindinger and others (2013). For more details on BICM habitat classes, see the Entity and Attribute Information section of the metadata. Please consult the accompanying readME.txt file for information and recommendations on the contents of this dataset (i.e., dataset and recommended symbology). For more information about the BICM program, see Kindinger and others (2013). \nReferences:\nKindinger, J.L., Buster, N.A., Flocks, J.G., Bernier, J.C., and Kulp, M.A., 2013, Louisiana Barrier Island Comprehensive Monitoring (BICM) program summary report\u2014Data and analyses 2006 through 2010: U.S. Geological Survey Open-File Report 2013\u20131083, 86 p., at https://pubs.usgs.gov/of/2013/1083/.\nEnwright, N.M., SooHoo, W.M., Dugas, J.L., Conzelmann, C.P., Laurenzano, C., Lee, D.M., Mouton, K., and Stelly, S.J., 2020, Louisiana Barrier Island Comprehensive Monitoring Program\u2014Mapping habitats in beach, dune, and intertidal environments along the Louisiana Gulf of Mexico shoreline, 2008 and 2015\u201316: U.S. Geological Survey Open-File Report 2020\u20131030, 57 p., https://doi.org/10.3133/ofr20201030.\nFearnley, S., Brien, L., Martinez, L., Miner, M., Kulp, M., and Penland, S., 2009, Chenier Plain, South-Central Louisiana, and Chandeleur Islands, Habitat mapping and change analysis 1996 to 2005, Part 1\u2014Methods for habitat mapping and change analysis 1996 to 2005\u2014Louisiana Barrier Island Comprehensive Monitoring Program (BICM) 5: New Orleans, University of New Orleans, Pontchartrain Institute for Environmental Sciences, 11 p.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/91f4fa35-a0c9-4c30-8895-1246a701f24a","harvest_record_raw":"https://catalog.data.gov/harvest_record/91f4fa35-a0c9-4c30-8895-1246a701f24a/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_68505a2cd4be025b9e8c6b6a","keyword":["Gulf of America","Louisiana","Louisiana Coastal","Modern Delta Region","Plaquemines Parish","USGS:68505a2cd4be025b9e8c6b6a","barrier islands","barrier vegetation","beach","coastal wetlands","dune","environment","farming","habitat map","mangrove","marsh","planningCadastre","remote sensing","scrub/shrub"],"last_harvested_date":"2026-09-27T00:53:47.274481","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":"louisiana-barrier-island-comprehensive-monitoring-program-2021-habitat-map-modern-delta-re","spatial_centroid":{"lat":29.26144,"lon":-89.70142000000001},"spatial_shape":{"coordinates":[[[-89.8837,29.1798],[-89.8837,29.3839],[-89.428,29.3839],[-89.428,29.1798],[-89.8837,29.1798]]],"type":"Polygon"},"theme":["geospatial"],"title":"Louisiana Barrier Island Comprehensive Monitoring Program \u2013 2021 habitat map, Modern Delta Region (ver. 2.0, September 2026)","type":"dataset"},{"_score":9.081593,"_sort":[1790470404474,9.081593,0,"be0ef096-7975-4ffc-8d91-459c3339e3ce"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Lindsay E. F. Hunt","hasEmail":"mailto:lhunt@usgs.gov"},"description":"This dataset is the sixth installment of a yearly connectivity update for forested habitat within the Great Lakes Restoration Initiative's (GLRI) Terrestrial Habitats &amp; Connectivity (TH&amp;C) work group's Pilot Area. The Pilot Area is a region of the northern Great Lakes Basin between Ashland, WI and the Keweenaw Peninsula and is bounded by Lake Superior in the north and the basin boundary in the south, including a 70 km buffer. Each year the TH&amp;C selects project proposals for funding within the pilot area. These proposals involve either restoration, research, or land acquisition aimed at improving or increasing forest connectivity in this area. The intended purpose of each year\u2019s update is to understand the effects of funded projects on the groundwork and help inform the location and purpose of future project proposals. The post-fiscal year 2025 forest connectivity maps serve as an additional time step for comparison from each previous fiscal year into the future.  \nTo create the post FY25 installment of GLRI's Terrestrial Habitats &amp; Connectivity work group's pilot area yearly connectivity maps, we identified the geospatial locations where restoration work benefitting forested habitats was completed throughout FY25. These locations were then assigned the lowest resistance value. Then using the forest habitat resistance layer from Great Lakes Restoration Initiative's Terrestrial Habitats and Connectivity Work group's Pilot Area's post-fiscal year 2025 we overwrote the post FY24 resistance values with the resistance values assigned to the FY25 locations where work was done. This analysis produced two connectivity maps: a cumulative current map and a normalized current map. The cumulative current map shows where potential movement pathways between forests are located within the pilot area, while the normalized current map shows where obstructed movement, diffuse movement, and channelized movement occurs within the pilot area. These maps provide important information on how restoration efforts from FY21, FY22, FY23, FY24, and FY25 in the pilot area are affecting forest habitat connectivity.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P14MMKBI","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.6a42901e1ba49b09ad17da03.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_6a42901e1ba49b09ad17da03","keyword":["Connectivity","Forest Habitat","Great Lakes","Northern Wisconsin/Michigan","USGS:6a42901e1ba49b09ad17da03","biota","dispersal (organisms)","environment","habitat fragmentation","imageryBaseMapsEarthCover","land use change","remote sensing","structure"],"modified":"2026-09-24T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-92.7750, 45.2500, -86.3710, 48.2097","theme":["geospatial"],"title":"Great Lakes Restoration Initiative's Terrestrial Habitats &amp; Connectivity Work Group's Pilot Area's Post-Fiscal Year 2025 Forest Habitat Connectivity"},"description":"This dataset is the sixth installment of a yearly connectivity update for forested habitat within the Great Lakes Restoration Initiative's (GLRI) Terrestrial Habitats &amp; Connectivity (TH&amp;C) work group's Pilot Area. The Pilot Area is a region of the northern Great Lakes Basin between Ashland, WI and the Keweenaw Peninsula and is bounded by Lake Superior in the north and the basin boundary in the south, including a 70 km buffer. Each year the TH&amp;C selects project proposals for funding within the pilot area. These proposals involve either restoration, research, or land acquisition aimed at improving or increasing forest connectivity in this area. The intended purpose of each year\u2019s update is to understand the effects of funded projects on the groundwork and help inform the location and purpose of future project proposals. The post-fiscal year 2025 forest connectivity maps serve as an additional time step for comparison from each previous fiscal year into the future.  \nTo create the post FY25 installment of GLRI's Terrestrial Habitats &amp; Connectivity work group's pilot area yearly connectivity maps, we identified the geospatial locations where restoration work benefitting forested habitats was completed throughout FY25. These locations were then assigned the lowest resistance value. Then using the forest habitat resistance layer from Great Lakes Restoration Initiative's Terrestrial Habitats and Connectivity Work group's Pilot Area's post-fiscal year 2025 we overwrote the post FY24 resistance values with the resistance values assigned to the FY25 locations where work was done. This analysis produced two connectivity maps: a cumulative current map and a normalized current map. The cumulative current map shows where potential movement pathways between forests are located within the pilot area, while the normalized current map shows where obstructed movement, diffuse movement, and channelized movement occurs within the pilot area. These maps provide important information on how restoration efforts from FY21, FY22, FY23, FY24, and FY25 in the pilot area are affecting forest habitat connectivity.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/5422c2a9-4fa8-430c-a53d-81bdd06b1016","harvest_record_raw":"https://catalog.data.gov/harvest_record/5422c2a9-4fa8-430c-a53d-81bdd06b1016/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_6a42901e1ba49b09ad17da03","keyword":["Connectivity","Forest Habitat","Great Lakes","Northern Wisconsin/Michigan","USGS:6a42901e1ba49b09ad17da03","biota","dispersal (organisms)","environment","habitat fragmentation","imageryBaseMapsEarthCover","land use change","remote sensing","structure"],"last_harvested_date":"2026-09-27T00:53:24.474463","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":"great-lakes-restoration-initiatives-terrestrial-habitats-amp-connectivity-work-groups-pilo-e7121","spatial_centroid":{"lat":46.43388,"lon":-90.21340000000001},"spatial_shape":{"coordinates":[[[-92.775,45.25],[-92.775,48.2097],[-86.371,48.2097],[-86.371,45.25],[-92.775,45.25]]],"type":"Polygon"},"theme":["geospatial"],"title":"Great Lakes Restoration Initiative's Terrestrial Habitats &amp; Connectivity Work Group's Pilot Area's Post-Fiscal Year 2025 Forest Habitat Connectivity","type":"dataset"},{"_score":9.618819,"_sort":[1790470384979,9.618819,0,"c4170fa3-939e-496d-a857-9731e41d87d4"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Andy Bock","hasEmail":"mailto:abock@usgs.gov"},"description":"The National Hydrologic Geospatial Fabric Reference and Derived Hydrofabrics is a geospatial dataset of connected rivers, streams, lakes, catchments, hydrologic locations, and relevant attributes to support multi-scale and integrative hydrologic modeling and analysis.\nThis child dataset contains features and attributes representing the National Hydrologic Geospatial Fabric Refactored Hydrofabric. The Refactored Hydrofabric is a processed version of the Reference Hydrofabric with a more uniform distribution of catchment size. The complexity of different models requires flexibility to create different spatial levels of resolution and detail. Catchments with flowpath-lengths shorter than the user-specified minimum length threshold that increase data volume and compute cost but don't add hydrologic fidelity have been consolidated into larger ones. Catchments whose flowpath lengths are longer than the user-specified maximum flowpath-length threshold are split apart to provide uniform fidelity and better represent network outlets such as streamgages. When refactoring, key hydrologic locations like stream gages are preserved precisely, unless they are specified specifically as split events.\nThis item contains an Open Geospatial Consortium geopackage (gpkg) containing refactored flowlines, catchments, and other layers for all of Conterminous United States CONUS (refactor_CONUS.gpkg). See the processing steps for specific refactoring details.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P9NFPB5S","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.61fbfdced34e622189cb1b0a.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_61fbfdced34e622189cb1b0a","keyword":["Geographic Information Systems","Hydrologic Response Units","Hydrologic modeling","Points of Interest","Routing Network","USGS:61fbfdced34e622189cb1b0a","environment","geoscientificInformation","inlandWaters"],"modified":"2026-09-24T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-124.7337, 24.6304, -66.9496, 52.8800","theme":["geospatial"],"title":"National Hydrologic Geospatial Fabric Refactored Hydrofabric"},"description":"The National Hydrologic Geospatial Fabric Reference and Derived Hydrofabrics is a geospatial dataset of connected rivers, streams, lakes, catchments, hydrologic locations, and relevant attributes to support multi-scale and integrative hydrologic modeling and analysis.\nThis child dataset contains features and attributes representing the National Hydrologic Geospatial Fabric Refactored Hydrofabric. The Refactored Hydrofabric is a processed version of the Reference Hydrofabric with a more uniform distribution of catchment size. The complexity of different models requires flexibility to create different spatial levels of resolution and detail. Catchments with flowpath-lengths shorter than the user-specified minimum length threshold that increase data volume and compute cost but don't add hydrologic fidelity have been consolidated into larger ones. Catchments whose flowpath lengths are longer than the user-specified maximum flowpath-length threshold are split apart to provide uniform fidelity and better represent network outlets such as streamgages. When refactoring, key hydrologic locations like stream gages are preserved precisely, unless they are specified specifically as split events.\nThis item contains an Open Geospatial Consortium geopackage (gpkg) containing refactored flowlines, catchments, and other layers for all of Conterminous United States CONUS (refactor_CONUS.gpkg). See the processing steps for specific refactoring details.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/5ce2a524-b4e4-4a7c-a960-065aa548f0fc","harvest_record_raw":"https://catalog.data.gov/harvest_record/5ce2a524-b4e4-4a7c-a960-065aa548f0fc/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_61fbfdced34e622189cb1b0a","keyword":["Geographic Information Systems","Hydrologic Response Units","Hydrologic modeling","Points of Interest","Routing Network","USGS:61fbfdced34e622189cb1b0a","environment","geoscientificInformation","inlandWaters"],"last_harvested_date":"2026-09-27T00:53:04.979454","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":"national-hydrologic-geospatial-fabric-refactored-hydrofabric","spatial_centroid":{"lat":35.930240000000005,"lon":-101.62006},"spatial_shape":{"coordinates":[[[-124.7337,24.6304],[-124.7337,52.88],[-66.9496,52.88],[-66.9496,24.6304],[-124.7337,24.6304]]],"type":"Polygon"},"theme":["geospatial"],"title":"National Hydrologic Geospatial Fabric Refactored Hydrofabric","type":"dataset"},{"_score":10.327461,"_sort":[1790470292050,10.327461,0,"81e5e55c-faeb-46d2-859e-0475af612e5b"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Cody Hudson","hasEmail":"mailto:chudson@intera.com"},"description":"Daily streamflow and reservoir water elevation data for modeled locations in the Red River Basin. Values reported are for 18 different GCM (Global Climate Model) / RCP (Representative Concentration Pathway) / GDM Downscaling scenarios. Climate data from each scenario was input into a Variable Infiltration Capacity (VIC) model, that output flow values. These values were then input into RiverWare, to determine the impacts on regulated flows, lake levels and water availability. RiverWare was used for this project, because of its ability to simulate water use, reservoir operations, and local/interstate regulations.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.21429/C91599","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.57d84d1ae4b090824ff9ac7b.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_57d84d1ae4b090824ff9ac7b","keyword":["Climate Change","Oklahoma","Red River","RiverWare","USGS:57d84d1ae4b090824ff9ac7b","Water Availability","environment"],"modified":"2026-09-23T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-99.9612, 33.7317, -94.6297, 35.6655","theme":["geospatial"],"title":"RiverWare Daily Simulated values of Streamflow from 2006-2099: Oklahoma"},"description":"Daily streamflow and reservoir water elevation data for modeled locations in the Red River Basin. 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RiverWare was used for this project, because of its ability to simulate water use, reservoir operations, and local/interstate regulations.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/59b7ae13-b980-452b-ba0e-ba20a3f31439","harvest_record_raw":"https://catalog.data.gov/harvest_record/59b7ae13-b980-452b-ba0e-ba20a3f31439/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_57d84d1ae4b090824ff9ac7b","keyword":["Climate Change","Oklahoma","Red River","RiverWare","USGS:57d84d1ae4b090824ff9ac7b","Water Availability","environment"],"last_harvested_date":"2026-09-27T00:51:32.050796","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":"riverware-daily-simulated-values-of-streamflow-from-2006-2099-oklahoma","spatial_centroid":{"lat":34.505219999999994,"lon":-97.82860000000001},"spatial_shape":{"coordinates":[[[-99.9612,33.7317],[-99.9612,35.6655],[-94.6297,35.6655],[-94.6297,33.7317],[-99.9612,33.7317]]],"type":"Polygon"},"theme":["geospatial"],"title":"RiverWare Daily Simulated values of Streamflow from 2006-2099: Oklahoma","type":"dataset"},{"_score":4.793105,"_sort":[1790470273412,4.793105,0,"2b991e1f-2b8f-45e0-99c2-aec7a26b77e7"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Tabitha A Graves","hasEmail":"mailto:tgraves@usgs.gov"},"description":"This data release contains the citation details, abstracts, and expert annotations of 235 publications on the topic of the potential effects of oil and gas development on pollinating insects in the western United States.\nPublications were collected through a structured literature search and a semi-automated content analysis. We developed a search string designed to pull relevant papers from Scopus and Web of Science. We used a set of benchmark publications identified by experts that were known to be relevant to the topic to refine the search string. The search returned 1,435 unique publications. Text mining of the title, abstract, and keywords quantified the relevancy of each paper to the topic and was used to discard the least relevant papers. We divided the remaining 731 publications into ten disturbance-based categories. The publications went through a three-step review process to remove irrelevant papers and to annotate relevant papers with key information related to the disturbance category. Lastly, text mining of the full manuscripts using the KWICer R code (Bailey and others 2026) was used to count the number of mentions of key words and phrases related to disturbance type, pollinator taxa, effect on pollinators, geographic location, ecosystem type, and study methodology.\nThe annotated bibliography contains 235 unique publications across the 10 disturbances categories: Air and chemical pollution (87 publications), air turbulence (4), dust (6), habitat loss and fragmentation (23), invasive plants (52), light pollution (37), noise pollution (6), oil and gas (7), roads (38), and soil compaction and trampling (10). The publications date from 1992 to 2026 and are mostly scientific articles (220) with some review papers (13), one editorial material, and one brief report. Full-manuscript text mining results are summarized in a set of figures that show the publication year, ecosystem type, and geographic area, as well as matrices that show the frequency and co-occurrence of pollinator taxa, disturbance type, and effect on pollinators in the body of literature. Together with the annotated bibliography, these elements provide key information that can help streamline regulatory processes related to oil and gas development on public lands.\nBailey, L.N., Varner, D.M., Whipple, S.E., 2026, KWICer: Producing an annotated bibliography from a set of PDFs by quantifying keywords, (Version 1.0.0): U.S. Geological Survey software release, https://doi.org/10.5066/P1476GUY.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P14A5GRG","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.6a8619cc1ba49b21c50f4f5e.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_6a8619cc1ba49b21c50f4f5e","keyword":["Argentina","Austria","Belarus","Belgium","Bolivia","Brazil","Canada","Chad","Chile","China","Costa Rica","Czech Republic","Denmark","Estonia","Finland","France","Georgia","Germany","Ghana","Greece","Guinea","Hungary","India","Indonesia","Iran","Ireland","Israel","Italy","Japan","Jordan","Kenya","Latvia","Lesotho","Libya","Lithuania","Luxembourg","Madagascar","Maldives","Mexico","Monaco","Mongolia","Nepal","Netherlands","Niger","Norway","Pakistan","Panama","Poland","Portugal","Romania","Russia","Seychelles","Singapore","Slovakia","Slovenia","South Africa","Spain","Sri Lanka","Sweden","Switzerland","Taiwan","Thailand","Turkey","USGS:6a8619cc1ba49b21c50f4f5e","Ukraine","United Kingdom","United States","Venezuela","Zimbabwe","air pollution","air turbulence","biota","dust pollution","energy resources","environment","habitat alteration and disturbance","habitat fragmentation","invasive species","light pollution","natural gas resources","natural resource extraction","natural resource management","noise pollution","oil resources","pollination","pollinators","roads","soil compaction","soil resources"],"modified":"2026-09-22T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-180.0000, -90.0000, 180.0000, 90.0000","theme":["geospatial"],"title":"Potential effects of oil and gas development on pollinating insects in the western United States: An annotated bibliography produced through a structured literature search and semi-automated content analysis"},"description":"This data release contains the citation details, abstracts, and expert annotations of 235 publications on the topic of the potential effects of oil and gas development on pollinating insects in the western United States.\nPublications were collected through a structured literature search and a semi-automated content analysis. We developed a search string designed to pull relevant papers from Scopus and Web of Science. We used a set of benchmark publications identified by experts that were known to be relevant to the topic to refine the search string. The search returned 1,435 unique publications. Text mining of the title, abstract, and keywords quantified the relevancy of each paper to the topic and was used to discard the least relevant papers. We divided the remaining 731 publications into ten disturbance-based categories. The publications went through a three-step review process to remove irrelevant papers and to annotate relevant papers with key information related to the disturbance category. Lastly, text mining of the full manuscripts using the KWICer R code (Bailey and others 2026) was used to count the number of mentions of key words and phrases related to disturbance type, pollinator taxa, effect on pollinators, geographic location, ecosystem type, and study methodology.\nThe annotated bibliography contains 235 unique publications across the 10 disturbances categories: Air and chemical pollution (87 publications), air turbulence (4), dust (6), habitat loss and fragmentation (23), invasive plants (52), light pollution (37), noise pollution (6), oil and gas (7), roads (38), and soil compaction and trampling (10). The publications date from 1992 to 2026 and are mostly scientific articles (220) with some review papers (13), one editorial material, and one brief report. Full-manuscript text mining results are summarized in a set of figures that show the publication year, ecosystem type, and geographic area, as well as matrices that show the frequency and co-occurrence of pollinator taxa, disturbance type, and effect on pollinators in the body of literature. 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The data release also includes some data to enable better understanding of the models used in the associated manuscript such as model standard deviations and model parameter permutation importance values.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P13HZTMZ","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.677728fed34ee88ba0b15b25.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_677728fed34ee88ba0b15b25","keyword":["Aquatic","Connecticut","Lentic","Lotic","Maine","Massachusetts","MaxEnt","New Hampshire","Northeast","Rhode Island","USGS:677728fed34ee88ba0b15b25","United States","Vermont","biota","elevation","environment","farming","freshwater","geospatial datasets","inlandWaters","modeling","mussels","river","stream","unionidae"],"modified":"2026-09-23T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-73.6857, 41.0274, -67.0094, 47.3254","theme":["geospatial"],"title":"Mussel occurrence and catchment priority for mussel conservation in the Northeastern U.S."},"description":"This data release includes the data associated with the manuscript \"Freshwater mussel distribution and catchment prioritization for mussel conservation in the Northeastern United States.\"  It describes native freshwater mussel distribution data for Maine, New Hampshire, Vermont, Massachusetts, Rhode Island, and Connecticut as well as catchment priority scores for different conservation activities.  The data release also includes some data to enable better understanding of the models used in the associated manuscript such as model standard deviations and model parameter permutation importance values.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/cb829d41-b60b-468d-a1db-9556611659ba","harvest_record_raw":"https://catalog.data.gov/harvest_record/cb829d41-b60b-468d-a1db-9556611659ba/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_677728fed34ee88ba0b15b25","keyword":["Aquatic","Connecticut","Lentic","Lotic","Maine","Massachusetts","MaxEnt","New Hampshire","Northeast","Rhode Island","USGS:677728fed34ee88ba0b15b25","United States","Vermont","biota","elevation","environment","farming","freshwater","geospatial datasets","inlandWaters","modeling","mussels","river","stream","unionidae"],"last_harvested_date":"2026-09-27T00:50:43.210190","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":"mussel-occurrence-and-catchment-priority-for-mussel-conservation-in-the-northeastern-u-s","spatial_centroid":{"lat":43.5466,"lon":-71.01518},"spatial_shape":{"coordinates":[[[-73.6857,41.0274],[-73.6857,47.3254],[-67.0094,47.3254],[-67.0094,41.0274],[-73.6857,41.0274]]],"type":"Polygon"},"theme":["geospatial"],"title":"Mussel occurrence and catchment priority for mussel conservation in the Northeastern U.S.","type":"dataset"},{"_score":8.766132,"_sort":[1790470223694,8.766132,0,"0e4b1b8b-5e9b-428f-81cf-9a11eb16240f"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Michael Osland","hasEmail":"mailto:mosland@usgs.gov"},"description":"Winter climate change has the potential to have a large impact on coastal wetlands in the southeastern U.S. Warmer winter temperatures and reductions in the intensity of freeze events would likely lead to mangrove forest range expansion and salt marsh displacement in parts of the U.S. Gulf of Mexico and Atlantic coast. The objective of this research was to better understand some of the ecological implications of mangrove forest migration and salt marsh displacement. The potential ecological effects of mangrove migration are diverse ranging from important biotic impacts (e.g., coastal fisheries, land bird migration; colonial nesting wading birds) to ecosystem stability (e.g., response to sea level rise and drought; habitat loss; coastal protection) to biogeochemical processes (e.g., carbon storage; water quality). In this research, our focus was on the impact of mangrove forest migration on coastal wetland soil processes and the consequent implications for coastal wetland responses to sea level rise, ecosystem resilience, and carbon storage. Our study specifically addressed the following questions: (1) How do ecological processes and ecosystem properties differ between salt marshes and mangrove forests; (2) As mangrove forests develop, how do their ecosystem properties change and how do these properties compare to salt marshes; (3) How do plant-soil interactions across mangrove forest structural gradients differ among three distinct locations that span the northern Gulf of Mexico; and (4) What are the implications of mangrove forest encroachment and development into salt marsh in terms of soil development, carbon and nitrogen storage, and soil strength? To address these questions, we utilized the salt marshes and natural mangrove forest structural gradients present at three distinct locations in the northern Gulf of Mexico: Cedar Key (Florida), Port Fourchon (Louisiana), and Port Aransas (Texas). Each of these locations represents a distinct combination of climate-driven abiotic conditions. We quantified relationships between plant community composition and structure, soil and porewater physicochemical properties, hydroperiod, and climatic conditions. The suite of measurements that we collected provide initial insights into how different geographic areas of an ecotone, with different environmental conditions, may be impacted by mangrove forest expansion and development, and how these changes may alter the supply of specific ecosystem goods and services. \nThis file includes the sub-plot-level small plot vegetation cover data.\nThis work was conducted via a collaborative effort between scientists at the U.S. Geological Survey National Wetland Research Center and the Department of Biology of the University of Louisiana at Lafayette.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P1GDTXUR","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.545cfa50e4b0ba8303f711e2.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_545cfa50e4b0ba8303f711e2","keyword":["Avicennia germinans","Cedar Key","Gulf of Mexico","Port Aransas","Port Fourchon","Spartina alterniflora","State of Florida","State of Louisiana","State of Texas","USGS:545cfa50e4b0ba8303f711e2","United States of America","environment","habitat","vegetation"],"modified":"2026-09-22T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"theme":["geospatial"],"title":"Dataset 6: New vegetation data collection: sub-plot-level small plot cover"},"description":"Winter climate change has the potential to have a large impact on coastal wetlands in the southeastern U.S. Warmer winter temperatures and reductions in the intensity of freeze events would likely lead to mangrove forest range expansion and salt marsh displacement in parts of the U.S. Gulf of Mexico and Atlantic coast. The objective of this research was to better understand some of the ecological implications of mangrove forest migration and salt marsh displacement. The potential ecological effects of mangrove migration are diverse ranging from important biotic impacts (e.g., coastal fisheries, land bird migration; colonial nesting wading birds) to ecosystem stability (e.g., response to sea level rise and drought; habitat loss; coastal protection) to biogeochemical processes (e.g., carbon storage; water quality). In this research, our focus was on the impact of mangrove forest migration on coastal wetland soil processes and the consequent implications for coastal wetland responses to sea level rise, ecosystem resilience, and carbon storage. Our study specifically addressed the following questions: (1) How do ecological processes and ecosystem properties differ between salt marshes and mangrove forests; (2) As mangrove forests develop, how do their ecosystem properties change and how do these properties compare to salt marshes; (3) How do plant-soil interactions across mangrove forest structural gradients differ among three distinct locations that span the northern Gulf of Mexico; and (4) What are the implications of mangrove forest encroachment and development into salt marsh in terms of soil development, carbon and nitrogen storage, and soil strength? To address these questions, we utilized the salt marshes and natural mangrove forest structural gradients present at three distinct locations in the northern Gulf of Mexico: Cedar Key (Florida), Port Fourchon (Louisiana), and Port Aransas (Texas). Each of these locations represents a distinct combination of climate-driven abiotic conditions. We quantified relationships between plant community composition and structure, soil and porewater physicochemical properties, hydroperiod, and climatic conditions. 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Our study specifically addressed the following questions: (1) How do ecological processes and ecosystem properties differ between salt marshes and mangrove forests; (2) As mangrove forests develop, how do their ecosystem properties change and how do these properties compare to salt marshes; (3) How do plant-soil interactions across mangrove forest structural gradients differ among three distinct locations that span the northern Gulf of Mexico; and (4) What are the implications of mangrove forest encroachment and development into salt marsh in terms of soil development, carbon and nitrogen storage, and soil strength? To address these questions, we utilized the salt marshes and natural mangrove forest structural gradients present at three distinct locations in the northern Gulf of Mexico: Cedar Key (Florida), Port Fourchon (Louisiana), and Port Aransas (Texas). Each of these locations represents a distinct combination of climate-driven abiotic conditions. 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This shapefile identifies regional conservation priority and restoration priority counties and includes information on the extent of pollinator-dependent crops, the mean relative pollinator activity on pollinator-dependent crops, and the proportion of pollinator habitat within pollinator flight distance of pollinator-dependent crops by county for the southeastern United States.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.21429/69zz-7f78","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.5d0a5f35e4b0e3d3115fba16.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_5d0a5f35e4b0e3d3115fba16","keyword":["Alabama","Arkansas","Florida","Georgia","Louisiana","Mississippi","Missouri","North Carolina","South Carolina","Tennessee","USGS:5d0a5f35e4b0e3d3115fba16","agricultural sites","environment","farming","habitats","natural resource management","pollination","pollinators","remediation"],"modified":"2026-09-23T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-95.8139, 23.8934, -74.5003, 40.6853","theme":["geospatial"],"title":"Conservation and Restoration Priorities for Wild Pollinator Habitat in the Southeast United States, by County (2011)"},"description":"Wild insect pollination has significant positive effects on pollinator-dependent crop production.  To assess the spatial distribution of potential wild insect pollination, we mapped the supply of potential wild pollinator habitat (forest, grassland, wetland, and shrubland land cover types) and the demand for pollination (directly pollinator-dependent crops).  A foraging travel distance for temperate native bees (1308 meters) was used to estimate relative pollinator activity on cropland based on distance from habitat.  We also calculated the proportion of pollinator habitat within pollinator travel distance of crops.  This information was summarized by county to identify regional priority areas for conservation and restoration of pollinator habitat.  This shapefile identifies regional conservation priority and restoration priority counties and includes information on the extent of pollinator-dependent crops, the mean relative pollinator activity on pollinator-dependent crops, and the proportion of pollinator habitat within pollinator flight distance of pollinator-dependent crops by county for the southeastern United States.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/b9819478-2d30-4b33-9053-78fa2e1623b5","harvest_record_raw":"https://catalog.data.gov/harvest_record/b9819478-2d30-4b33-9053-78fa2e1623b5/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_5d0a5f35e4b0e3d3115fba16","keyword":["Alabama","Arkansas","Florida","Georgia","Louisiana","Mississippi","Missouri","North Carolina","South Carolina","Tennessee","USGS:5d0a5f35e4b0e3d3115fba16","agricultural sites","environment","farming","habitats","natural resource management","pollination","pollinators","remediation"],"last_harvested_date":"2026-09-27T00:31:13.996338","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":"conservation-and-restoration-priorities-for-wild-pollinator-habitat-in-the-southeast--2011","spatial_centroid":{"lat":30.610159999999997,"lon":-87.28846},"spatial_shape":{"coordinates":[[[-95.8139,23.8934],[-95.8139,40.6853],[-74.5003,40.6853],[-74.5003,23.8934],[-95.8139,23.8934]]],"type":"Polygon"},"theme":["geospatial"],"title":"Conservation and Restoration Priorities for Wild Pollinator Habitat in the Southeast United States, by County (2011)","type":"dataset"},{"_score":12.448236,"_sort":[1790468941104,12.448236,1,"ada40940-ab68-4634-bf7d-f710eea12ade"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Daniel M Wagner","hasEmail":"mailto:dwagner@usgs.gov"},"description":"This dataset contains site information and results of flood frequency analysis for 64 urban streamflow gaging stations (streamgages) operated by the U.S. Geological Survey (USGS) in Alabama and Mississippi. Site information and annual peak-flow data from the 1885 - 2024 water years were obtained from the USGS National Water Information System (NWIS) database (U.S. Geological Survey, 2025). Flood frequency analysis was conducted in version 8.0.0 of USGS PeakFQ software (Siefken and others, 2024) in the R environment (R Core Team, 2024) following the guidelines set forth in Bulletin 17C (England and others, 2018) and using the approaches described in the most recent flood frequency reports for Alabama and Mississippi (Anderson, 2020 and Anderson, 2018, respectively). Site information is provided in .csv format (\"AL_MS_UrbanFFreq_SiteInfo.csv\"). Peak-flow (\"AL_MS_UrbanFFreq_nwis_peak.txt\"), specification (\"AL_MS_UrbanFFreq.psf\"), and output files from PeakFQ (\"AL_MS_UrbanFFreq_emp.csv\", \"AL_MS_UrbanFFreq_lp3.csv\", \"AL_MS_UrbanFFreq_mgb.csv\", \"AL_MS_UrbanFFreq_qnt.csv\", and \"AL_MS_UrbanFFreq_trd.csv\") are provided.  Estimates of the 0.5, 0.2, 0.1, 0.04, 0.02, 0.01, 0.005, and 0.002 annual exceedance probabilities (the 2-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-year recurrence intervals, respectively) are in file \"AL_MS_UrbanFFreq_qnt.csv\".\nThe data release was revised August 4, 2026.  Column \"index_no\" was added to file \"AL_MS_UrbanFFreq_SiteInfo.csv\" and a description of the column was added to the metadata.  The values in column \"index_no\" are used as the streamgage labels in Figure 1 in the related primary publication.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P1JSTYKU","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.67ae1895d34e3f09c0e0f00c.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_67ae1895d34e3f09c0e0f00c","keyword":["Alabama","Lower Mississippi Region - 2-digit Hydrologic Unit Code - 08","Mississippi","South-Atlantic-Gulf Region - 2-digit Hydrologic Unit Code - 03","Tennessee Region - 2-digit Hydrologic Unit Code - 06","USGS:67ae1895d34e3f09c0e0f00c","flood frequency","inlandWaters"],"modified":"2026-09-24T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-91.6550, 30.1741, -84.8882, 35.0080","theme":["geospatial"],"title":"At-site flood frequency estimates for 64 urban streamgages in Alabama and Mississippi using data through water year 2024 (ver. 2.0, August 2026)"},"description":"This dataset contains site information and results of flood frequency analysis for 64 urban streamflow gaging stations (streamgages) operated by the U.S. Geological Survey (USGS) in Alabama and Mississippi. 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Estimates of the 0.5, 0.2, 0.1, 0.04, 0.02, 0.01, 0.005, and 0.002 annual exceedance probabilities (the 2-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-year recurrence intervals, respectively) are in file \"AL_MS_UrbanFFreq_qnt.csv\".\nThe data release was revised August 4, 2026.  Column \"index_no\" was added to file \"AL_MS_UrbanFFreq_SiteInfo.csv\" and a description of the column was added to the metadata.  The values in column \"index_no\" are used as the streamgage labels in Figure 1 in the related primary publication.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/6938ef00-96ac-4c1d-8399-61da90c5928e","harvest_record_raw":"https://catalog.data.gov/harvest_record/6938ef00-96ac-4c1d-8399-61da90c5928e/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_67ae1895d34e3f09c0e0f00c","keyword":["Alabama","Lower Mississippi Region - 2-digit Hydrologic Unit Code - 08","Mississippi","South-Atlantic-Gulf Region - 2-digit Hydrologic Unit Code - 03","Tennessee Region - 2-digit Hydrologic Unit Code - 06","USGS:67ae1895d34e3f09c0e0f00c","flood frequency","inlandWaters"],"last_harvested_date":"2026-09-27T00:29:01.104008","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":"at-site-flood-frequency-estimates-for-64-urban-streamgages-in-alabama-and-mississippi-2024","spatial_centroid":{"lat":32.107659999999996,"lon":-88.94828},"spatial_shape":{"coordinates":[[[-91.655,30.1741],[-91.655,35.008],[-84.8882,35.008],[-84.8882,30.1741],[-91.655,30.1741]]],"type":"Polygon"},"theme":["geospatial"],"title":"At-site flood frequency estimates for 64 urban streamgages in Alabama and Mississippi using data through water year 2024 (ver. 2.0, August 2026)","type":"dataset"},{"_score":10.446892,"_sort":[1790468859579,10.446892,3,"6e8269e2-6c0a-4011-b743-7d854649c37a"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Jesslyn Brown","hasEmail":"mailto:casc-data@usgs.gov"},"description":"NASS USDA estimates the irrigated croplands at county level every five years. But this estimation does not provide the geospatial information of the irrigated croplands. To provide a comprehensive, consistent, and timely geospatially detailed information about irrigated cropland conterminous U.S. (CONUS), the \u201cModerate Resolution Imaging Spectroradiometer (MODIS) Irrigated Agriculture Dataset for the United States (MIrAD-US)\u201d product was produced by the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center with funding from several USGS programs (National Land Imaging and National Water-Quality Assessment). A primary objective was to identify, and map irrigated agricultural areas to factor into water quality studies and drought monitoring investigations. This product uses three primary data inputs, (a) USDA county-level irrigation area statistics for 2002, (b) annual peak eMODIS Normalized Difference Vegetation Index (NDVI), and (c) a land cover mask for agricultural lands derived from NLCD to map the spatial distribution of irrigated lands across the conterminous United States. The MIrAD Version 4 offers the datasets for the years 2002, 2007, 2012, and 2017 at 250-m and 1-km spatial resolutions. The validation of MIrAD-US is a challenge because no other single-source current datasets are available at a national scale for comparison. Thus, this dataset should be considered provisional until a formal accuracy assessment can be completed. The product update is planned for every 5 years, synchronized with the update of the Census of Agriculture by the U.S Department of Agriculture (USDA) but contingent upon availability of Collection 6 (C6) Aqua eMODIS data and funding.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P9NA3EO8","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.5db08e84e4b0b0c58b56e04f.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_5db08e84e4b0b0c58b56e04f","keyword":["USGS:5db08e84e4b0b0c58b56e04f","agriculture","environment","farming","irrigation","multispectral imaging","remote sensing"],"modified":"2020-08-18T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-128.2624, 22.6867, -65.6851, 51.5890","theme":["geospatial"],"title":"Moderate Resolution Imaging Spectroradiometer (MODIS) Irrigated Agriculture Datasets for the Conterminous United States (MIrAD-US)"},"description":"NASS USDA estimates the irrigated croplands at county level every five years. 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Our study specifically addressed the following questions: (1) How do ecological processes and ecosystem properties differ between salt marshes and mangrove forests; (2) As mangrove forests develop, how do their ecosystem properties change and how do these properties compare to salt marshes; (3) How do plant-soil interactions across mangrove forest structural gradients differ among three distinct locations that span the northern Gulf of Mexico; and (4) What are the implications of mangrove forest encroachment and development into salt marsh in terms of soil development, carbon and nitrogen storage, and soil strength? To address these questions, we utilized the salt marshes and natural mangrove forest structural gradients present at three distinct locations in the northern Gulf of Mexico: Cedar Key (Florida), Port Fourchon (Louisiana), and Port Aransas (Texas). Each of these locations represents a distinct combination of climate-driven abiotic conditions. We quantified relationships between plant community composition and structure, soil and porewater physicochemical properties, hydroperiod, and climatic conditions. The suite of measurements that we collected provide initial insights into how different geographic areas of an ecotone, with different environmental conditions, may be impacted by mangrove forest expansion and development, and how these changes may alter the supply of specific ecosystem goods and services. This file includes the scanned field notes associated with this project\nThis work was conducted via a collaborative effort between scientists at the U.S. Geological Survey National Wetland Research Center and the Department of Biology of the University of Louisiana at Lafayette.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/adb4a717-39a3-4429-a4ee-dc92e2baca66","harvest_record_raw":"https://catalog.data.gov/harvest_record/adb4a717-39a3-4429-a4ee-dc92e2baca66/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_545bf875e4b009f8aec9b52a","keyword":["Florida","Gulf of Mexico","Louisiana","Texas","USGS:545bf875e4b009f8aec9b52a","climate change","ecosystem monitoring","environment","field inventory and monitoring","forest","mangrove","migration","wetlands"],"last_harvested_date":"2026-09-27T00:19:20.650149","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":"field-notes-scanned-field-data-sheets-and-field-notebook-pages-for-the-following-2012-2013","spatial_centroid":{"lat":28.377999999999997,"lon":-91.49598},"spatial_shape":{"coordinates":[[[-97.1401,27.83],[-97.1401,29.2],[-83.0298,29.2],[-83.0298,27.83],[-97.1401,27.83]]],"type":"Polygon"},"theme":["geospatial"],"title":"Field Notes: Scanned Field Data Sheets and Field Notebook Pages for the following project - Ecological implications of mangrove forest migration in the southeastern US (2012-2013)","type":"dataset"},{"_score":8.866966,"_sort":[1790468212146,8.866966,0,"98f0a52a-4d91-4e28-a16e-5f68b33b4673"],"dcat":{"accessLevel":"public","bureauCode":["010:12"],"contactPoint":{"@type":"vcard:Contact","fn":"Lindsay E. 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The 2025 open habitat connectivity maps serves as an additional time step for comparison for each fiscal year from pre 2021 into the future.  \nTo create the post FY25 installment of GLRI's Terrestrial Habitats &amp; Connectivity work group's pilot area yearly connectivity maps, we identified the geospatial locations where restoration work benefitting open habitats was completed throughout FY25. These locations were then assigned the lowest resistance value. Then using the open habitat resistance layer from Great Lakes Restoration Initiative's Terrestrial Habitats and Connectivity Work group's Pilot Area's post-fiscal year 2024 we overwrote the post FY24 resistance values with the resistance values assigned to the FY25 locations where work was done. This analysis produced two connectivity maps: a cumulative current map and a normalized current map. The cumulative current map shows where potential movement pathways between open habitat are located within the pilot area, while the normalized current map shows where obstructed movement, diffuse movement, and channelized movement occurs within the pilot area. These maps provide important information on how restoration efforts in the pilot area from both FY21, FY22, FY23, and FY24 are affecting open habitat connectivity.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P1V7S2J9","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.6a3e97431ba49ba6dca26eb6.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_6a3e97431ba49ba6dca26eb6","keyword":["Connectivity","Great Lakes","Keweenaw Peninsula","Lake Superior","Open Habitat","USGS:6a3e97431ba49ba6dca26eb6","biota","dispersal (organisms)","ecology","environment","habitat fragmentation","imageryBaseMapsEarthCover","land use change","remote sensing","structure"],"modified":"2026-09-24T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-93.4094, 44.6675, -85.8861, 48.7713","theme":["geospatial"],"title":"Great Lakes Restoration Initiative's Terrestrial Habitats &amp; Connectivity Work Group's Pilot Area's Post-Fiscal Year 2025 Open Habitat Connectivity"},"description":"This dataset is the sixth installment of a yearly connectivity update for open habitat within the Great Lakes Restoration Initiative's (GLRI) Terrestrial Habitats &amp; Connectivity (TH&amp;C) work group's Pilot Area. The Pilot Area is a region of the northern Great Lakes Basin between Ashland, Wisconsin and the Keweenaw Peninsula and is bounded by Lake Superior in the north and the basin boundary in the south, including a 70 km buffer. Each year the TH&amp;C selects project proposals for funding within the pilot area. These proposals involve either restoration, research, or land acquisition aimed at improving or increasing open connectivity in this area. The intended purpose of each year\u2019s update is to understand the effects of funded projects on the groundwork and help inform the location and purpose of future project proposals. The 2025 open habitat connectivity maps serves as an additional time step for comparison for each fiscal year from pre 2021 into the future.  \nTo create the post FY25 installment of GLRI's Terrestrial Habitats &amp; Connectivity work group's pilot area yearly connectivity maps, we identified the geospatial locations where restoration work benefitting open habitats was completed throughout FY25. These locations were then assigned the lowest resistance value. Then using the open habitat resistance layer from Great Lakes Restoration Initiative's Terrestrial Habitats and Connectivity Work group's Pilot Area's post-fiscal year 2024 we overwrote the post FY24 resistance values with the resistance values assigned to the FY25 locations where work was done. This analysis produced two connectivity maps: a cumulative current map and a normalized current map. The cumulative current map shows where potential movement pathways between open habitat are located within the pilot area, while the normalized current map shows where obstructed movement, diffuse movement, and channelized movement occurs within the pilot area. These maps provide important information on how restoration efforts in the pilot area from both FY21, FY22, FY23, and FY24 are affecting open habitat connectivity.","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/d54c5ed6-1359-45cb-82fa-3e1380bfb988","harvest_record_raw":"https://catalog.data.gov/harvest_record/d54c5ed6-1359-45cb-82fa-3e1380bfb988/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_6a3e97431ba49ba6dca26eb6","keyword":["Connectivity","Great Lakes","Keweenaw Peninsula","Lake Superior","Open Habitat","USGS:6a3e97431ba49ba6dca26eb6","biota","dispersal (organisms)","ecology","environment","habitat fragmentation","imageryBaseMapsEarthCover","land use change","remote sensing","structure"],"last_harvested_date":"2026-09-27T00:16:52.146733","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":"great-lakes-restoration-initiatives-terrestrial-habitats-amp-connectivity-work-groups-pilo-4ab10","spatial_centroid":{"lat":46.30902,"lon":-90.40008},"spatial_shape":{"coordinates":[[[-93.4094,44.6675],[-93.4094,48.7713],[-85.8861,48.7713],[-85.8861,44.6675],[-93.4094,44.6675]]],"type":"Polygon"},"theme":["geospatial"],"title":"Great Lakes Restoration Initiative's Terrestrial Habitats &amp; Connectivity Work Group's Pilot Area's Post-Fiscal Year 2025 Open Habitat Connectivity","type":"dataset"},{"_score":12.4384165,"_sort":[1790468012637,12.4384165,6,"46f7c7a7-7371-48b4-afd7-c9b6214c425e"],"dcat":{"@type":"dcat:Dataset","accessLevel":"non-public","contactPoint":{"@type":"vcard:Contact","fn":"NOAA National Centers for Environmental Information","hasEmail":"mailto:ncei.info@noaa.gov"},"describedByType":"application/octet-stream","description":"This dataset includes physical, chemical, meteorological, and biological data, including zooplankton abundance, primary production, carotenoids, phaeophytin, fluorescence, phaeopigments, fatty acids, chlorophylls, aggregates and particulate matter, \"marine snow\", thymidine and leucine uptake, nitrate and saturated ammonium uptake rates, oxygen production, irradiance, Lu683, PAR, Thorium-234 activity, chemical concentrations, light attenuation and transmission, water temperature, currents, salinity, and other data.\n\nThese data were collected during the Joint Global Ocean Flux Study (JGOFS) Arabian Sea Process Study between 1992 and 1997, the Equatorial Pacific (EqPac) Process Study along 140\u00b0W during 1992, the Antarctic Environment and Southern Ocean Process Study (AESOPS), 1996 to 1998, and the North Atlantic Bloom Experiment (NABE) April through July 1989, as well as the Bermuda Atlantic Time Series (BATS) study which began in 1989. This dataset also includes data from other related JGOFS Antarctic and Southern Ocean expeditions, including the Antarctic Polar Frontal Zone (APFZ) cruises in 1997 and 1998, the ANT X/6 expedition and Oregon State University cruises on POLAR DUKE between 1990 and 1995. As an extra added bonus, this dataset also includes the North Pacific Process Study (NPPS) CD-ROM that was produced by the Japan Oceanographic Data Center (JODC).\n\nThe U.S. Joint Global Ocean Flux Study (JGOFS) Equatorial Pacific (EqPac) process study was conducted along 140\u00b0W during the calendar year 1992. Four process cruises took place, with a fifth benthic cruise and sediment trap legs adding to the overall study.\n\nMost Hawaii Ocean Times Series (HOT) data are available separately, although some HOT data are included in this dataset.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/archive/accession/US-JGOFS-Program","describedByType":"application/octet-stream","description":"Navigate directly to the URL for a descriptive web page with download links.","mediaType":"text/html","title":"NCEI Dataset Landing Page"},{"@type":"dcat:Distribution","accessURL":"https://data.noaa.gov/onestop/collections/granules/1eb718e6-5921-4771-bcf3-193da92e2df3","describedByType":"application/octet-stream","description":"Browse data granules belonging to this collection (a granule is the smallest aggregation of data that can be independently described and retrieved).","mediaType":"text/html","title":"Browse 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datasets","mediaType":"text/html","title":"https://www.ncei.noaa.gov/access/ocean-carbon-acidification-data-system/oceans/Coastal/BATS.html"},{"@type":"dcat:Distribution","accessURL":"https://forum.earthdata.nasa.gov/app.php/tag/GCMD%2BKeywords","describedByType":"application/octet-stream","description":"Global Change Master Directory (GCMD). 2025. GCMD Keywords, Version 21. Greenbelt, MD: Earth Science Data and Information System, Earth Science Projects Division, Goddard Space Flight Center (GSFC), National Aeronautics and Space Administration (NASA). URL (GCMD Keyword Forum Page): https://forum.earthdata.nasa.gov/app.php/tag/GCMD+Keywords","mediaType":"text/html","title":"GCMD Keyword Forum Page"},{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/contact","describedByType":"application/octet-stream","description":"Information for contacts at NCEI.","mediaType":"text/html","title":"NCEI Contact Information"}],"identifier":"https://data.noaa.gov/waf/NOAA/NESDIS/ncei/accessions/iso/xml/US-JGOFS-Program.xml","issued":"1991-01-01T00:00:00.000+00:00","keyword":["0000145","0000285","0000407","0000463","0000498","0000499","0000504","0000519","0000523","0000562","0000887","0000888","0000889","0000890","0000894","0000895","0000896","0000897","0000898","0000899","0000947","0000990","0001155","0001873","0002369","9100172","9200023","9200088","9200089","9200160","9500082","9500091","9600065","9600091","9600115","9600118","9700034","9700039","9700048","9700049","9700050","9700052","9700053","9700054","9700055","9700056","9700058","9700059","9700062","9700068","9700083","9700085","9700086","9700087","9700088","9700106","9700107","9700108","9700109","9700110","9700112","9700115","9700116","9700177","9700178","9700180","9700194","9700195","9700196","9700197","9700205","9700206","9700207","9700208","9700209","9700210","9700221","9800020","9800030","9800032","9800033","9800037","9800042","9800055","9800061","9800071","9800072","9800073","9800077","9800079","9800085","9800086","9800088","9800092","9800093","9800095","9800109","9800116","9800120","9800127","9800128","9800131","9800132","9800154","9800155","9800158","9800160","9800161","9800166","9800183","9800186","9800188","9800200","9900010","9900014","9900051","9900063","9900066","9900067","9900090","9900097","9900106","9900113","9900135","9900143","9900146","9900154","9900162","9900163","9900164","9900167","9900168","9900177","9900183","9900185","9900192","9900196","9900217","9900218","9900219","9900239","AEROSOL OPTICAL THICKNESS","AIR TEMPERATURE","AIR TEMPERATURE - 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THOMPSON","R/V WECOMA","ROVER","RV Alpha Helix","RV Nathaniel B. Palmer","RV Polarstern","SAGAR KANYA","WEATHERBIRD II","Bermuda Biological Station for Research","Bermuda Institute of Ocean Sciences","Bigelow Laboratory for Ocean Sciences","Duke University","Fish Research Institute","Gulf Coast Research Laboratory","Harvard University","Horn Point Laboratory","Lamont-Doherty Earth Observatory","Louisiana Universities Marine Consortium","Moss Landing Marine Laboratories","NASA Goddard Space Flight Center","National Institute of Oceanography - India","North Carolina State University","Old Dominion University","Oregon State University","Oregon State University, College of Earth, Ocean, and Atmospheric Sciences","Royal Netherlands Institute for Sea Research","San Diego State University","San Francisco State University","Scripps Institution of Oceanography","Skidaway Institute of Oceanography","State University of New York at Stony Brook","Texas A&M University","The College of William and Mary","The University of North Carolina at Chapel Hill","University of Bergen","University of California - Santa Cruz","University of Connecticut, Marine Research Laboratory","University of Delaware, College of Earth, Ocean, and Environment, School of Marine Science and Policy","University of Georgia, School of Marine Programs","University of Hawai\u02bbi at M\u0101noa","University of Miami Rosenstiel School of Marine and Atmospheric Science","University of Minnesota - Duluth, Large Lakes Observatory","University of Rhode Island, Graduate School of Oceanography","University of Southern California","University of Tennessee","University of Washington","US NASA/Jet Propulsion Laboratory","US National Aeronautic and Space Administration","Virginia Institute of Marine Science","Woods Hole Oceanographic Institution","Bermuda Institute of Ocean Sciences","Bigelow Laboratory for Ocean Sciences","Duke University","Gulf Coast Research Laboratory","Harvard University","Horn Point Laboratory","Japan Oceanographic Data Center","Lamont-Doherty Earth Observatory","Louisiana Universities Marine Consortium","Moss Landing Marine Laboratories","NASA Goddard Space Flight Center","National Institute of Oceanography - India","North Carolina State University","Old Dominion University","Oregon State University","Oregon State University, College of Earth, Ocean, and Atmospheric Sciences","Royal Netherlands Institute for Sea Research","San Diego State University","San Francisco State University","Scripps Institution of Oceanography","Skidaway Institute of Oceanography","State University of New York at Stony Brook","Texas A&M University","University of Bergen","University of California - Santa Cruz","University of Connecticut, Marine Research Laboratory","University of Delaware, College of Earth, Ocean, and Environment, School of Marine Science and Policy","University of Georgia, School of Marine Programs","University of Hawai\u02bbi at M\u0101noa","University of Miami Rosenstiel School of Marine and Atmospheric Science","University of 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Atlantic Ocean (limit-20 W)","Southern Ocean","TOGA Area - Pacific (30 N to 30 S)","oceanography","BBSR > Bermuda Biological Station for Research","BIGELOW > Bigelow Laboratory of Ocean Sciences","COLUMBIA/LDEO > Lamont-Doherty Earth Observatory, Columbia University","CWM/VIMS > Virginia Institute of Marine Science, College of William and Mary","DOC/NOAA/NESDIS/NODC > National Oceanographic Data Center, NESDIS, NOAA, U.S. Department of Commerce","IN/NIO > National Institute of Oceanography, India","JP/JODC > Japan Oceanographic Data Center","Jet Propulsion Laboratory","MLML > Moss Landing Marine Laboratories","NL/NWO/NIOZ > Royal Netherlands Institute for Sea Research (NIOZ)","OR-STATE/CEOAS > College of Earth, Ocean, and Atmospheric Sciences, Oregon State University","U-MIAMI/RSMAS > Rosenstiel School of Marine and Atmospheric Science, University of Miami","UGA/SkIO > Skidaway Institute of Oceanography, University of Georgia","UMCES/HPL > Horns Point Laboratory, University of Maryland 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ATMOSPHERIC TEMPERATURE","EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC TEMPERATURE > SURFACE TEMPERATURE > AIR TEMPERATURE","EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC WINDS > SURFACE WINDS > WIND DIRECTION","EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC WINDS > SURFACE WINDS > WIND SPEED","EARTH SCIENCE > BIOLOGICAL CLASSIFICATION","EARTH SCIENCE > BIOLOGICAL CLASSIFICATION > BACTERIA/ARCHAEA","EARTH SCIENCE > BIOLOGICAL CLASSIFICATION > BACTERIA/ARCHAEA > CYANOBACTERIA (BLUE-GREEN ALGAE)","EARTH SCIENCE > BIOLOGICAL CLASSIFICATION > PLANTS > MICROALGAE > DIATOMS","EARTH SCIENCE > BIOLOGICAL CLASSIFICATION > PROTISTS > PLANKTON","EARTH SCIENCE > BIOLOGICAL CLASSIFICATION > PROTISTS > PLANKTON > PHYTOPLANKTON","EARTH SCIENCE > BIOSPHERE > ECOLOGICAL DYNAMICS > ECOSYSTEM FUNCTIONS > PHOTOSYNTHESIS","EARTH SCIENCE > BIOSPHERE > ECOLOGICAL DYNAMICS > ECOSYSTEM FUNCTIONS > PRIMARY PRODUCTION","EARTH SCIENCE > BIOSPHERE > ECOLOGICAL DYNAMICS > ECOSYSTEM FUNCTIONS > RESPIRATION RATE","EARTH SCIENCE > BIOSPHERE > ECOSYSTEMS > AQUATIC ECOSYSTEMS > PLANKTON","EARTH SCIENCE > BIOSPHERE > ECOSYSTEMS > AQUATIC ECOSYSTEMS > PLANKTON > ZOOPLANKTON","EARTH SCIENCE > BIOSPHERE > VEGETATION > BIOMASS","EARTH SCIENCE > OCEANS > BATHYMETRY/SEAFLOOR TOPOGRAPHY > WATER DEPTH","EARTH SCIENCE > OCEANS > MARINE SEDIMENTS","EARTH SCIENCE > OCEANS > OCEAN ACOUSTICS > ACOUSTIC VELOCITY","EARTH SCIENCE > OCEANS > OCEAN CHEMISTRY","EARTH SCIENCE > OCEANS > OCEAN CHEMISTRY > ALKALINITY","EARTH SCIENCE > OCEANS > OCEAN CHEMISTRY > AMMONIA","EARTH SCIENCE > OCEANS > OCEAN CHEMISTRY > CARBON","EARTH SCIENCE > OCEANS > OCEAN CHEMISTRY > CARBON DIOXIDE","EARTH SCIENCE > OCEANS > OCEAN CHEMISTRY > CHLOROPHYLL","EARTH SCIENCE > OCEANS > OCEAN CHEMISTRY > HYDROCARBONS","EARTH SCIENCE > OCEANS > OCEAN CHEMISTRY > INORGANIC CARBON","EARTH SCIENCE > OCEANS > OCEAN CHEMISTRY > NITRATE","EARTH SCIENCE > OCEANS > OCEAN CHEMISTRY > NITRITE","EARTH SCIENCE > OCEANS > OCEAN CHEMISTRY > NITROGEN","EARTH SCIENCE > OCEANS > OCEAN CHEMISTRY > NUTRIENTS","EARTH SCIENCE > OCEANS > OCEAN CHEMISTRY > ORGANIC CARBON","EARTH SCIENCE > OCEANS > OCEAN CHEMISTRY > ORGANIC MATTER","EARTH SCIENCE > OCEANS > OCEAN CHEMISTRY > OXYGEN","EARTH SCIENCE > OCEANS > OCEAN CHEMISTRY > PH","EARTH SCIENCE > OCEANS > OCEAN CHEMISTRY > PHOSPHATE","EARTH SCIENCE > OCEANS > OCEAN CHEMISTRY > PIGMENTS","EARTH SCIENCE > OCEANS > OCEAN CHEMISTRY > PIGMENTS > CHLOROPHYLL","EARTH SCIENCE > OCEANS > OCEAN CHEMISTRY > SILICATE","EARTH SCIENCE > OCEANS > OCEAN CHEMISTRY > SUSPENDED SOLIDS","EARTH SCIENCE > OCEANS > OCEAN CIRCULATION > OCEAN CURRENTS","EARTH SCIENCE > OCEANS > OCEAN OPTICS","EARTH SCIENCE > OCEANS > OCEAN OPTICS > ATTENUATION/TRANSMISSION","EARTH SCIENCE > OCEANS > OCEAN OPTICS > FLUORESCENCE","EARTH SCIENCE > OCEANS > OCEAN OPTICS > IRRADIANCE","EARTH SCIENCE > OCEANS > OCEAN OPTICS > PHOTOSYNTHETICALLY ACTIVE RADIATION","EARTH SCIENCE > OCEANS > OCEAN OPTICS > SECCHI DEPTH","EARTH SCIENCE > OCEANS > OCEAN OPTICS > TURBIDITY","EARTH SCIENCE > OCEANS > OCEAN PRESSURE > WATER PRESSURE","EARTH SCIENCE > OCEANS > OCEAN TEMPERATURE > POTENTIAL TEMPERATURE","EARTH SCIENCE > OCEANS > OCEAN TEMPERATURE > SEA SURFACE TEMPERATURE","EARTH SCIENCE > OCEANS > OCEAN TEMPERATURE > WATER TEMPERATURE","EARTH SCIENCE > OCEANS > OCEAN WAVES > SEA STATE","EARTH SCIENCE > OCEANS > OCEAN WAVES > WAVE HEIGHT","EARTH SCIENCE > OCEANS > OCEAN WAVES > WAVE PERIOD","EARTH SCIENCE > OCEANS > SALINITY/DENSITY > CONDUCTIVITY","EARTH SCIENCE > OCEANS > SALINITY/DENSITY > DENSITY","EARTH SCIENCE > OCEANS > SALINITY/DENSITY > SALINITY","EARTH SCIENCE > OCEANS > TIDES","EARTH SCIENCE > OCEANS > TIDES > TIDAL HEIGHT","19'-butanoyloxyfucoxanthin","19'-hexanoyloxyfucoxanthin","alloxanthin","alpha-carotene","beta-carotene","chlorophyll a","chlorophyll b","chlorophyll c3","chlorophyllide a","cis-19'-hexanoyloxyfucoxanthin","cis-fucoxanthin","diadinoxanthin","diatoxanthin","divinyl chlorophyll a","divinyl chlorophyll b","fucoxanthin","lutein","monovinyl chlorophyll a","monovinyl chlorophyll b","peridinin","phaeopigments","prasinoxanthin","violaxanthin","zeaxanthin","BATHYTHERMOGRAPHS","CAMERA > CAMERA","CTD > Conductivity, Temperature, Depth","CURRENT METERS","DRIFTING BUOYS > DRIFTING BUOYS","FLOW CYTOMETRY","FLUORESCENCE MICROSCOPY > FLUORESCENCE MICROSCOPY","FLUOROMETERS > FLUOROMETERS","GAS CHROMATOGRAPHS > GAS CHROMATOGRAPHS","GRAB SAMPLERS","MASS SPECTROMETERS > MASS SPECTROMETERS","MICROSCOPES > MICROSCOPES","MOCNESS > MOCNESS Plankton Net","NETS > NETS","NISKIN BOTTLES","OPTSPEC > Optical Spectrometer","OXYGEN METERS > OXYGEN METERS","PAR SENSORS > Photosynthetically Active Radiation Sensors","PH METERS > PH METERS","PLANKTON NETS","RADIOMETERS","SALINOMETERS","SECCHI DISKS > SECCHI DISKS","SEDIMENT CORERS > SEDIMENT CORERS","THERMOMETERS > THERMOMETERS","TIDE GAUGES > TIDE GAUGES","TRANSMISSOMETERS","TRAPS > TRAPS","VIDEO CAMERA > VIDEO CAMERA","XBT > Expendable Bathythermographs","FIXED OBSERVATION STATIONS > FIXED OBSERVATION STATIONS","Ships","ALPHA HELIX (call sign: WSD7078, ICES code: 31HX, 1966-)","ATLANTIS II (call sign: KADC, ICES code: 31AN, 1963-1996)","CAPE HATTERAS (call sign: WRZ8934, ICES code: 32KZ, 1981-)","CAPE HENLOPEN (ICES code: 32CW)","CROMWELL (ICES code: 31WM)","ENDEAVOR (call sign: WAUW, ICES code: 33EN)","ENDEAVOR (call sign: WCE5063, ICES code: 32EV, 1976-)","MOANA WAVE (call sign: WUS9293, ICES code: 32MW, 1974-2011)","NA'INA (ICES code: 33NA)","NATHANIEL B. PALMER (call sign: WPB3210, ICES code: 3206, 1992-)","NEW HORIZON (call sign: WKWB, ICES code: 32NM, 1978-2015)","POLAR DUKE (call sign: WCX7445, ICES code: 33PD, 1984-1988)","Polarstern (call sign: DBLK, ICES code: 06AQ, 1982-)","ROGER REVELLE (call sign: KAOU, ICES code: 33RR, 1996-)","ROVER (ICES code: 32YS)","SAGAR KANYA (call sign: VTJR, ICES code: 41SG)","THOMAS G. THOMPSON (call sign: KTDQ, ICES code: 3250, 1991-)","WEATHERBIRD (call sign: AGOR, ICES code: 320G)","WECOMA (call sign: WSD7079, ICES code: 32WC, 1976-)","OCEAN > ATLANTIC OCEAN > NORTH ATLANTIC OCEAN","OCEAN > ATLANTIC OCEAN > SOUTH ATLANTIC OCEAN","OCEAN > INDIAN OCEAN","OCEAN > INDIAN OCEAN > ARABIAN SEA","OCEAN > PACIFIC OCEAN","OCEAN > PACIFIC OCEAN > NORTH PACIFIC OCEAN","OCEAN > PACIFIC OCEAN > SOUTH PACIFIC OCEAN","OCEAN > SOUTHERN OCEAN","OCEAN > SOUTHERN OCEAN > ROSS SEA"],"landingPage":"https://www.ncei.noaa.gov/contact","language":[],"license":"https://creativecommons.org/publicdomain/zero/1.0/","modified":"2026-03-23T00:00:00.000+00:00","publisher":{"@type":"org:Organization","name":"NOAA National Centers for Environmental Information"},"references":["https://usjgofs.whoi.edu/research/index.html","https://doi.org/10.1016/s0967-0645(00)00059-x","https://doi.org/10.1016/0967-0645(96)00004-5","https://discover.library.noaa.gov/permalink/01NOAA_INST/1qbesct/alma991001196289707381","https://discover.library.noaa.gov/permalink/01NOAA_INST/1qbesct/alma991000435089707381","https://doi.org/10.5670/oceanog.1992.01","https://www.ncei.noaa.gov/archive/accession/Station-ALOHA-HOT","https://www.ncei.noaa.gov/archive/accession/BIOS-Hydrostation_S","https://www.ncei.noaa.gov/archive/accession/0291424","https://www.ncei.noaa.gov/archive/accession/0299432","https://www.ncei.noaa.gov/archive/accession/0299443","https://www.ncei.noaa.gov/archive/accession/0299541","https://www.ncei.noaa.gov/archive/accession/0299425","https://www.ncei.noaa.gov/access/ocean-carbon-acidification-data-system/oceans/Coastal/BATS.html"],"rights":"otherRestrictions","spatial":"87.97,-78.05,-179.684,66.0","temporal":"1968-01-01T00:00:00+00:00/2003-01-01T00:00:00+00:00","theme":["geospatial"],"title":"Data from the Joint Global Ocean Flux Study (JGOFS) Time Series and Process Studies, 1992 to 1997"},"description":"This dataset includes physical, chemical, meteorological, and biological data, including zooplankton abundance, primary production, carotenoids, phaeophytin, fluorescence, phaeopigments, fatty acids, chlorophylls, aggregates and particulate matter, \"marine snow\", thymidine and leucine uptake, nitrate and saturated ammonium uptake rates, oxygen production, irradiance, Lu683, PAR, Thorium-234 activity, chemical concentrations, light attenuation and transmission, water temperature, currents, salinity, and other data.\n\nThese data were collected during the Joint Global Ocean Flux Study (JGOFS) Arabian Sea Process Study between 1992 and 1997, the Equatorial Pacific (EqPac) Process Study along 140\u00b0W during 1992, the Antarctic Environment and Southern Ocean Process Study (AESOPS), 1996 to 1998, and the North Atlantic Bloom Experiment (NABE) April through July 1989, as well as the Bermuda Atlantic Time Series (BATS) study which began in 1989. This dataset also includes data from other related JGOFS Antarctic and Southern Ocean expeditions, including the Antarctic Polar Frontal Zone (APFZ) cruises in 1997 and 1998, the ANT X/6 expedition and Oregon State University cruises on POLAR DUKE between 1990 and 1995. As an extra added bonus, this dataset also includes the North Pacific Process Study (NPPS) CD-ROM that was produced by the Japan Oceanographic Data Center (JODC).\n\nThe U.S. Joint Global Ocean Flux Study (JGOFS) Equatorial Pacific (EqPac) process study was conducted along 140\u00b0W during the calendar year 1992. Four process cruises took place, with a fifth benthic cruise and sediment trap legs adding to the overall study.\n\nMost Hawaii Ocean Times Series (HOT) data are available separately, although some HOT data are included in this dataset.","distribution_titles":["NCEI Dataset Landing Page","Browse granules","Search for granules","https://usjgofs.whoi.edu/research/index.html","https://doi.org/10.1016/s0967-0645(00)00059-x","https://doi.org/10.1016/0967-0645(96)00004-5","https://discover.library.noaa.gov/permalink/01NOAA_INST/1qbesct/alma991001196289707381","https://discover.library.noaa.gov/permalink/01NOAA_INST/1qbesct/alma991000435089707381","https://doi.org/10.5670/oceanog.1992.01","https://www.ncei.noaa.gov/archive/accession/Station-ALOHA-HOT","https://www.ncei.noaa.gov/archive/accession/BIOS-Hydrostation_S","https://www.ncei.noaa.gov/archive/accession/0291424","https://www.ncei.noaa.gov/archive/accession/0299432","https://www.ncei.noaa.gov/archive/accession/0299443","https://www.ncei.noaa.gov/archive/accession/0299541","https://www.ncei.noaa.gov/archive/accession/0299425","https://www.ncei.noaa.gov/access/ocean-carbon-acidification-data-system/oceans/Coastal/BATS.html","GCMD Keyword Forum Page","NCEI Contact Information"],"harvest_record":"https://catalog.data.gov/harvest_record/8b65680f-6215-4e01-bce0-3746645bf8b5","harvest_record_raw":"https://catalog.data.gov/harvest_record/8b65680f-6215-4e01-bce0-3746645bf8b5/raw","harvest_record_transformed":"https://catalog.data.gov/harvest_record/8b65680f-6215-4e01-bce0-3746645bf8b5/transformed","has_download":true,"has_spatial":true,"identifier":"https://data.noaa.gov/waf/NOAA/NESDIS/ncei/accessions/iso/xml/US-JGOFS-Program.xml","keyword":["0000145","0000285","0000407","0000463","0000498","0000499","0000504","0000519","0000523","0000562","0000887","0000888","0000889","0000890","0000894","0000895","0000896","0000897","0000898","0000899","0000947","0000990","0001155","0001873","0002369","9100172","9200023","9200088","9200089","9200160","9500082","9500091","9600065","9600091","9600115","9600118","9700034","9700039","9700048","9700049","9700050","9700052","9700053","9700054","9700055","9700056","9700058","9700059","9700062","9700068","9700083","9700085","9700086","9700087","9700088","9700106","9700107","9700108","9700109","9700110","9700112","9700115","9700116","9700177","9700178","9700180","9700194","9700195","9700196","9700197","9700205","9700206","9700207","9700208","9700209","9700210","9700221","9800020","9800030","9800032","9800033","9800037","9800042","9800055","9800061","9800071","9800072","9800073","9800077","9800079","9800085","9800086","9800088","9800092","9800093","9800095","9800109","9800116","9800120","9800127","9800128","9800131","9800132","9800154","9800155","9800158","9800160","9800161","9800166","9800183","9800186","9800188","9800200","9900010","9900014","9900051","9900063","9900066","9900067","9900090","9900097","9900106","9900113","9900135","9900143","9900146","9900154","9900162","9900163","9900164","9900167","9900168","9900177","9900183","9900185","9900192","9900196","9900217","9900218","9900219","9900239","AEROSOL OPTICAL THICKNESS","AIR TEMPERATURE","AIR TEMPERATURE - WET BULB","alloxan","Aluminum","AMMONIA (NH3)","AMMONIUM (NH4)","Attenuation/Transmission","bacteria","BACTERIA - BACTERIAL DENSITY","bacteria - cyanobacteria","BACTERIA - HETEROTROPHIC","BACTERIA - PLATE COUNTS","BAROMETRIC PRESSURE","BEAM ATTENUATION COEFFICIENT","biological data","BIOMASS","BIOMASS - PLANKTON","CARBON","CARBON - ORGANIC - SEDIMENT","CARBON - TOTAL ORGANIC","CARBON ASSIMILATION","CAROTENOIDS - PLANT","CAS (CHEMICAL ABSTRACTS SERVICE) PARAMETER CODES","CELL COUNTS","CHLOROFLUOROCARBON-11 (CFC-11)","CHLOROFLUOROCARBON-12 (CFC-12)","CHLOROPHYLL","CHLOROPHYLL A","CHLOROPHYLL A CONCENTRATION","CHLOROPHYLL B","CHLOROPHYLL C","CONDUCTIVITY","CURRENT DIRECTION","CURRENT METER - EAST-WEST COMPONENT (U)","CURRENT METER - NORTH-SOUTH COMPONENT (V)","CURRENT SPEED","CURRENT SPEED - EAST/WEST COMPONENT (U)","CURRENT SPEED - NORTH/SOUTH COMPONENT (V)","DEPTH - OBSERVATION","DEPTH - SENSOR","Diadinoxanthin","diatom","DISSOLVED INORGANIC CARBON (DIC)","DISSOLVED ORGANIC CARBON","DISSOLVED ORGANIC MATTER","DISSOLVED OXYGEN","DOWNWELLING RADIANCE","DYNAMIC DEPTH ANOMALY","Eukaryote","FISHERY SURVEY","FLUORESCENCE","fucoxanthin","HELIUM","HYDROCARBONS - TOTAL RESOLVED","HYDROSTATIC PRESSURE","Iron","irradiance","leucine","LIGHT - PERCENT","LIGHT ATTENUATION","LIGHT TRANSMISSION","MANGANESE","METALS","MICROPLANKTON","NANOPLANKTON","NITRATE","nitrate + nitrite content (concentration)","NITRITE","NITROGEN","NITROGEN - PARTICULATE","NUTRIENTS","OPTICAL BACKSCATTER","OXYGEN","Partial pressure (or fugacity) of carbon dioxide - atmosphere","partial pressure of carbon dioxide - water","PARTICULATE CARBON","Particulate Inorganic Carbon","PARTICULATE MATTER - DRY WEIGHT","PARTICULATE ORGANIC CARBON","PARTICULATE ORGANIC NITROGEN (PON)","pH","PHAEOPHYTIN","PHAEOPIGMENT CONCENTRATION","PHAEOPIGMENTS","phosphate","PHOSPHATE - TOTAL","PHOTOSYNTHETIC ACTIVE RADIATION (PAR)","PHOTOSYNTHETIC CAPACITY - EXPERIMENT ELAPSED TIME","PHYTOPLANKTON","PHYTOPLANKTON - DRY WEIGHT","PHYTOPLANKTON - WET WEIGHT","PHYTOPLANKTON BIOMASS","PIGMENTS","POLYCHLORINATED BIPHENYLS","POLYNUCLEAR AROMATIC HYDROCARBONS (PAH)","Potential temperature (theta)","PRIMARY PRODUCTIVITY","PRIMARY PRODUCTIVITY - PHYTOPLANKTON","Prochlorococcus","RADIATION - TOTAL INCIDENT","RADIUM ISOTOPES","respiration rates","SALINITY","SEA STATE","SEA SURFACE TEMPERATURE","Secchi depth","SEDIMENT PROPERTIES","SEDIMENTS","SEDIMENTS - DRY WEIGHT","SEDIMENTS - PARTICLE SIZE FRACTIONS","SIGMA-T","SIGMA-THETA","silicate","Silicon","SOLAR RADIATION - ATMOSPHERIC","SOUND VELOCITY","species abundance","SPECIES IDENTIFICATION - WET WEIGHT","surface irradiance","suspended solids","Synechococcus","thorium isotope","thymidine","TIDE HEIGHT","TIDE STAGE","total alkalinity","TOTAL CARBON","Total nitrogen","TOTAL PHOSPHATE","TOTAL PHOSPHORUS","TRACE METALS","Tritium (Hydrogen isotope)","turbidity","UPWELLING IRRADIANCE","UPWELLING RADIANCE","UREA","Violaxanthin","WATER DENSITY","water depth","WATER TEMPERATURE","WAVE HEIGHT","WAVE PERIOD","WEATHER","WIND DIRECTION","WIND SPEED","zinc","ZOOPLANKTON","ZOOPLANKTON ABUNDANCE","ZOOPLANKTON BIOMASS","ZOOPLANKTON IDENTITIES","ZOOPLANKTON SPECIES IDENTITIES","ZOOPLANKTON SPECIES NUMBER PER SAMPLE","bathythermograph - AXBT","bathythermograph - BT","bathythermograph - XBT","bottle","buoy - drifting buoy","camera","chromatograph","CTD","CTD - moored CTD","current meter","Flow Cytometer","fluorescence microscope","fluorometer","irradiance detector","laboratory analysis","mass spectrometer","meteorological sensor","microscope","Multiple Opening/Closing Net and Environmental Sensing System (MOCNESS)","net","net - plankton net","net - zooplankton net","Niskin bottle","optical backscatter sensor","oxygen sensor","PAR Sensor","pH sensor","pump casts","radiometer","salinometer","SeaSoar","Secchi disk","sediment sampler - corer","sediment sampler - grab","spectrophotometer","surface seawater intake","thermometer","tide gauge","transmissometer","trap","trap - sediment","video - LAPS - autonomous video camera","visual analysis","benthic","biological","chemical","continuous","current measurements","geological","laboratory analyses","meteorological","optical","physical","plankton","profile","pump cast","surface measurements","time series","tows","tows - plankton tows","tows - undulating tow","underway","water chemistry","AIRCRAFT","ATLANTIS II","CAPE HATTERAS","CAPE HENLOPEN","CROMWELL","ENDEAVOR","ENDEAVOR","FIXED PLATFORM OF UNITED STATES","MOANA WAVE","MULTIPLE SHIPS OF NORWAY","NA'INA","NEW HORIZON","R/V Polar Duke","R/V Roger Revelle","R/V THOMAS G. THOMPSON","R/V WECOMA","ROVER","RV Alpha Helix","RV Nathaniel B. Palmer","RV Polarstern","SAGAR KANYA","WEATHERBIRD II","Bermuda Biological Station for Research","Bermuda Institute of Ocean Sciences","Bigelow Laboratory for Ocean Sciences","Duke University","Fish Research Institute","Gulf Coast Research Laboratory","Harvard University","Horn Point Laboratory","Lamont-Doherty Earth Observatory","Louisiana Universities Marine Consortium","Moss Landing Marine Laboratories","NASA Goddard Space Flight Center","National Institute of Oceanography - India","North Carolina State University","Old Dominion University","Oregon State University","Oregon State University, College of Earth, Ocean, and Atmospheric Sciences","Royal Netherlands Institute for Sea Research","San Diego State University","San Francisco State University","Scripps Institution of Oceanography","Skidaway Institute of Oceanography","State University of New York at Stony Brook","Texas A&M University","The College of William and Mary","The University of North Carolina at Chapel Hill","University of Bergen","University of California - Santa Cruz","University of Connecticut, Marine Research Laboratory","University of Delaware, College of Earth, Ocean, and Environment, School of Marine Science and Policy","University of Georgia, School of Marine Programs","University of Hawai\u02bbi at M\u0101noa","University of Miami Rosenstiel School of Marine and Atmospheric Science","University of Minnesota - Duluth, Large Lakes Observatory","University of Rhode Island, Graduate School of Oceanography","University of Southern California","University of Tennessee","University of Washington","US NASA/Jet Propulsion Laboratory","US National Aeronautic and Space Administration","Virginia Institute of Marine Science","Woods Hole Oceanographic Institution","Bermuda Institute of Ocean Sciences","Bigelow Laboratory for Ocean Sciences","Duke University","Gulf Coast Research Laboratory","Harvard University","Horn Point Laboratory","Japan Oceanographic Data Center","Lamont-Doherty Earth Observatory","Louisiana Universities Marine Consortium","Moss Landing Marine Laboratories","NASA Goddard Space Flight Center","National Institute of Oceanography - India","North Carolina State University","Old Dominion University","Oregon State University","Oregon State University, College of Earth, Ocean, and Atmospheric Sciences","Royal Netherlands Institute for Sea Research","San Diego State University","San Francisco State University","Scripps Institution of Oceanography","Skidaway Institute of Oceanography","State University of New York at Stony Brook","Texas A&M University","University of Bergen","University of California - Santa Cruz","University of Connecticut, Marine Research Laboratory","University of Delaware, College of Earth, Ocean, and Environment, School of Marine Science and Policy","University of Georgia, School of Marine Programs","University of Hawai\u02bbi at M\u0101noa","University of Miami Rosenstiel School of Marine and Atmospheric Science","University of 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TURBIDITY","EARTH SCIENCE > OCEANS > OCEAN PRESSURE > WATER PRESSURE","EARTH SCIENCE > OCEANS > OCEAN TEMPERATURE > POTENTIAL TEMPERATURE","EARTH SCIENCE > OCEANS > OCEAN TEMPERATURE > SEA SURFACE TEMPERATURE","EARTH SCIENCE > OCEANS > OCEAN TEMPERATURE > WATER TEMPERATURE","EARTH SCIENCE > OCEANS > OCEAN WAVES > SEA STATE","EARTH SCIENCE > OCEANS > OCEAN WAVES > WAVE HEIGHT","EARTH SCIENCE > OCEANS > OCEAN WAVES > WAVE PERIOD","EARTH SCIENCE > OCEANS > SALINITY/DENSITY > CONDUCTIVITY","EARTH SCIENCE > OCEANS > SALINITY/DENSITY > DENSITY","EARTH SCIENCE > OCEANS > SALINITY/DENSITY > SALINITY","EARTH SCIENCE > OCEANS > TIDES","EARTH SCIENCE > OCEANS > TIDES > TIDAL HEIGHT","19'-butanoyloxyfucoxanthin","19'-hexanoyloxyfucoxanthin","alloxanthin","alpha-carotene","beta-carotene","chlorophyll a","chlorophyll b","chlorophyll c3","chlorophyllide a","cis-19'-hexanoyloxyfucoxanthin","cis-fucoxanthin","diadinoxanthin","diatoxanthin","divinyl chlorophyll a","divinyl chlorophyll b","fucoxanthin","lutein","monovinyl chlorophyll a","monovinyl chlorophyll b","peridinin","phaeopigments","prasinoxanthin","violaxanthin","zeaxanthin","BATHYTHERMOGRAPHS","CAMERA > CAMERA","CTD > Conductivity, Temperature, Depth","CURRENT METERS","DRIFTING BUOYS > DRIFTING BUOYS","FLOW CYTOMETRY","FLUORESCENCE MICROSCOPY > FLUORESCENCE MICROSCOPY","FLUOROMETERS > FLUOROMETERS","GAS CHROMATOGRAPHS > GAS CHROMATOGRAPHS","GRAB SAMPLERS","MASS SPECTROMETERS > MASS SPECTROMETERS","MICROSCOPES > MICROSCOPES","MOCNESS > MOCNESS Plankton Net","NETS > NETS","NISKIN BOTTLES","OPTSPEC > Optical Spectrometer","OXYGEN METERS > OXYGEN METERS","PAR SENSORS > Photosynthetically Active Radiation Sensors","PH METERS > PH METERS","PLANKTON NETS","RADIOMETERS","SALINOMETERS","SECCHI DISKS > SECCHI DISKS","SEDIMENT CORERS > SEDIMENT CORERS","THERMOMETERS > THERMOMETERS","TIDE GAUGES > TIDE GAUGES","TRANSMISSOMETERS","TRAPS > TRAPS","VIDEO CAMERA > VIDEO CAMERA","XBT > Expendable Bathythermographs","FIXED OBSERVATION STATIONS > FIXED OBSERVATION STATIONS","Ships","ALPHA HELIX (call sign: WSD7078, ICES code: 31HX, 1966-)","ATLANTIS II (call sign: KADC, ICES code: 31AN, 1963-1996)","CAPE HATTERAS (call sign: WRZ8934, ICES code: 32KZ, 1981-)","CAPE HENLOPEN (ICES code: 32CW)","CROMWELL (ICES code: 31WM)","ENDEAVOR (call sign: WAUW, ICES code: 33EN)","ENDEAVOR (call sign: WCE5063, ICES code: 32EV, 1976-)","MOANA WAVE (call sign: WUS9293, ICES code: 32MW, 1974-2011)","NA'INA (ICES code: 33NA)","NATHANIEL B. PALMER (call sign: WPB3210, ICES code: 3206, 1992-)","NEW HORIZON (call sign: WKWB, ICES code: 32NM, 1978-2015)","POLAR DUKE (call sign: WCX7445, ICES code: 33PD, 1984-1988)","Polarstern (call sign: DBLK, ICES code: 06AQ, 1982-)","ROGER REVELLE (call sign: KAOU, ICES code: 33RR, 1996-)","ROVER (ICES code: 32YS)","SAGAR KANYA (call sign: VTJR, ICES code: 41SG)","THOMAS G. THOMPSON (call sign: KTDQ, ICES code: 3250, 1991-)","WEATHERBIRD (call sign: AGOR, ICES code: 320G)","WECOMA (call sign: WSD7079, ICES code: 32WC, 1976-)","OCEAN > ATLANTIC OCEAN > NORTH ATLANTIC OCEAN","OCEAN > ATLANTIC OCEAN > SOUTH ATLANTIC OCEAN","OCEAN > INDIAN OCEAN","OCEAN > INDIAN OCEAN > ARABIAN SEA","OCEAN > PACIFIC OCEAN","OCEAN > PACIFIC OCEAN > NORTH PACIFIC OCEAN","OCEAN > PACIFIC OCEAN > SOUTH PACIFIC OCEAN","OCEAN > SOUTHERN OCEAN","OCEAN > SOUTHERN OCEAN > ROSS SEA"],"last_harvested_date":"2026-09-27T00:13:32.637657","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"5f4f1195-e770-4a2a-8f75-195cd98860ce","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/noaa.png","name":"National Oceanic and Atmospheric Administration, Department of Commerce","organization_type":"Federal Government","slug":"noaa"},"parent_identifier":null,"popularity":6,"publisher":"NOAA National Centers for Environmental Information","slug":"data-from-the-joint-global-ocean-flux-study-jgofs-time-series-and-process-studies-199-1997","spatial_centroid":{"lat":-6.024999999999999,"lon":-27.545799999999996},"spatial_shape":{"coordinates":[[[[87.97,-78.05],[180.0,-78.05],[180.0,66.0],[87.97,66.0],[87.97,-78.05]]],[[[-180.0,66.0],[-180.0,-78.05],[-179.684,-78.05],[-179.684,66.0],[-180.0,66.0]]]],"type":"MultiPolygon"},"theme":["geospatial"],"title":"Data from the Joint Global Ocean Flux Study (JGOFS) Time Series and Process Studies, 1992 to 1997","type":"dataset"},{"_score":0.51562595,"_sort":[1790467987344,0.51562595,2,"5fa739dd-ba93-4c00-9fa7-20b0432aed5f"],"dcat":{"@type":"dcat:Dataset","accessLevel":"non-public","contactPoint":{"@type":"vcard:Contact","fn":"NOAA National Centers for Environmental Information","hasEmail":"mailto:ncei.info@noaa.gov"},"describedByType":"application/octet-stream","description":"This collection includes various coral reef data that was extracted by analyses of Structure-from-Motion (SfM) imagery of coral reef ecosystems across the Pacific Islands Regions by the Ecosystem Sciences Division (ESD) of the Pacific Islands Fisheries Science Center (PIFSC) of NOAA.  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Corals > Reef Monitoring and Assessment","EARTH SCIENCE > Biosphere > Zoology > Corals > Reef Monitoring and Assessment > Benthos Analysis","EARTH SCIENCE > Biosphere > Zoology > Corals > Reef Monitoring and Assessment > Benthos Analysis > Quadrat Monitoring > Photograph Analysis","EARTH SCIENCE > Biosphere > Zoology > Corals > Reef Monitoring and Assessment > Coral Colony Size and Condition","EARTH SCIENCE > Biosphere > Zoology > Corals > Reef Monitoring and Assessment > Damage Assessment > Visual","EARTH SCIENCE > Biosphere > Zoology > Corals > Reef Monitoring and Assessment > GIS","EARTH SCIENCE > Biosphere > Zoology > Corals > Reef Monitoring and Assessment > In Situ Biological","EARTH SCIENCE > Biosphere > Zoology > Corals > Reef Monitoring and Assessment > Photographic Analysis","EARTH SCIENCE > Biosphere > Zoology > Corals > Scleractinia (stony corals)","EARTH SCIENCE > Biosphere > Zoology > Sponges","EARTH SCIENCE > Oceans > Bathymetry/Seafloor Topography > Hard Seafloor Substrate","EARTH SCIENCE > Oceans > Coastal Processes > Coral Reefs","EARTH SCIENCE > Oceans > Coastal Processes > Coral Reefs > Coral Reef Ecology","EARTH SCIENCE > Oceans > Coastal Processes > Coral Reefs > Coral Reef Ecology > Benthic biology","EARTH SCIENCE > Oceans > Coastal Processes > Coral Reefs > Coral Reef Ecology > Coral Cover","EARTH SCIENCE > Oceans > Coastal Processes > Coral Reefs > Coral Reef Ecology > Hard Coral Cover","EARTH SCIENCE > Oceans > Coastal Processes > Coral Reefs > Coral Reef Ecology > Rugosity","EARTH SCIENCE > Oceans > Marine Biology > Coral","EARTH SCIENCE > Oceans > Marine Biology > Coral Communities","EARTH SCIENCE > Oceans > Marine Biology > Marine Invertebrates","EARTH SCIENCE > BIOLOGICAL CLASSIFICATION","EARTH SCIENCE > BIOSPHERE > ECOSYSTEMS > MARINE ECOSYSTEMS > BENTHIC","EARTH SCIENCE > BIOSPHERE > ECOSYSTEMS > MARINE ECOSYSTEMS > REEF > CORAL REEF","EARTH SCIENCE > OCEANS > BATHYMETRY/SEAFLOOR TOPOGRAPHY > WATER DEPTH","EARTH SCIENCE > OCEANS > COASTAL PROCESSES > CORAL REEFS > CORAL BLEACHING","EARTH SCIENCE > OCEANS > MARINE ENVIRONMENT MONITORING > MARINE SUBMERGED DEBRIS","EARTH SCIENCE > SOLID EARTH > GEOMORPHIC LANDFORMS/PROCESSES > COASTAL LANDFORMS > CORAL REEFS","CORAL - CONDITION","CORAL - FISH BITES","CORAL - FISH BITES (count and category)","CORAL - PATCH SIZE","CORAL - SPECIES IDENTIFICATION","Complexity metrics","Corallivory","Fractal dimension","Height range","Reef habitat complexity","Rugosity","SfM","Structure from Motion","Structure from Motion (SfM)","digital elevation model","VISUAL OBSERVATIONS > VISUAL OBSERVATIONS","Agisoft Metashape","Agisoft Metashape software","ArcGIS","ArcGIS Pro","Computer","Dive Computer","GIS","R software","TagLab","Viscore","Ships","Hi'ialakai (call sign: WTEY, ICES code: 33HL, 2004-)","OSCAR ELTON SETTE (call sign: WTEE, ICES code: 33OC, 2003-)","RAINIER (call sign: WTEF, ICES code: 315R, 1968-)","M/V IMUA","Various Small Vessels","COUNTRY/TERRITORY > Northern Mariana Islands > Asuncion Island > Asuncion Island (19N145E0001)","COUNTRY/TERRITORY > Northern Mariana Islands > Maug > Maug Island (20N145E0001)","COUNTRY/TERRITORY > Northern Mariana Islands > Northern Mariana Islands > Northern Mariana Islands ( CNMI ) (18N146E0000)","COUNTRY/TERRITORY > Northern Mariana Islands > Pagan > Pagan Island (18N145E0001)","COUNTRY/TERRITORY > Northern Mariana Islands > Saipan > Saipan Island (15N145E0002)","COUNTRY/TERRITORY > United States of America > Guam > Guam (13N144E0000)","COUNTRY/TERRITORY > United States of America > Hawaii > Honolulu > Oahu (21N157W0003)","OCEAN BASIN > Pacific Ocean > Central Pacific Ocean > Hawaiian Islands > Oahu Island > Oahu (21N157W0003)","OCEAN BASIN > Pacific Ocean > Western Pacific Ocean > Asuncion Island > Asuncion Island (19N145E0001)","OCEAN BASIN > Pacific Ocean > Western Pacific Ocean > Guam > Guam (13N144E0000)","OCEAN BASIN > Pacific Ocean > Western Pacific Ocean > Mariana Archipelago > Northern Mariana Islands ( CNMI ) (18N146E0000)","OCEAN BASIN > Pacific Ocean > Western Pacific Ocean > Maug Island > Maug Island (20N145E0001)","OCEAN BASIN > Pacific Ocean > Western Pacific Ocean > Pagan Island > Pagan Island (18N145E0001)","OCEAN BASIN > Pacific Ocean > Western Pacific Ocean > Saipan Island > Saipan Island (15N145E0002)","COUNTRY/TERRITORY > Northern Mariana Islands > Aguihan > Aguihan Island (Aguijan) (14N145E0006)","COUNTRY/TERRITORY > Northern Mariana Islands > Asuncion Island > Asuncion Island (19N145E0001)","COUNTRY/TERRITORY > Northern Mariana Islands > Maug > Maug Island (20N145E0001)","COUNTRY/TERRITORY > Northern Mariana Islands > Northern Mariana Islands > Northern Mariana Islands ( CNMI ) (18N146E0000)","COUNTRY/TERRITORY > Northern Mariana Islands > Pagan > Pagan Island (18N145E0001)","COUNTRY/TERRITORY > Northern Mariana Islands > Rota > Rota Island ( Luta ) (14N145E0007)","COUNTRY/TERRITORY > Northern Mariana Islands > Saipan > Saipan Island (15N145E0002)","COUNTRY/TERRITORY > Northern Mariana Islands > Sarigan Island > Sarigan Island (16N145E0003)","COUNTRY/TERRITORY > Northern Mariana Islands > Tinian > Tinian Island (14N145E0005)","COUNTRY/TERRITORY > United States of America > American Samoa > American Samoa > American Samoa (14S170W0000)","COUNTRY/TERRITORY > United States of America > American Samoa > American Samoa > Ofu Island (14S169W0013)","COUNTRY/TERRITORY > United States of America > American Samoa > American Samoa > Olosega Island (14S169W0014)","COUNTRY/TERRITORY > United States of America > American Samoa > American Samoa > Rose Atoll (14S168W0001)","COUNTRY/TERRITORY > United States of America > American Samoa > American Samoa > Ta'u Island (14S169W0012)","COUNTRY/TERRITORY > United States of America > American Samoa > American Samoa > Tutuila Island (14S170W0016)","COUNTRY/TERRITORY > United States of America > Guam > Guam (13N144E0000)","COUNTRY/TERRITORY > United States of America > Hawaii > Hawaii > Hawaii (21N160W0000)","COUNTRY/TERRITORY > United States of America > Hawaii > Hawaii > Hawaii Island (19N155W0003)","COUNTRY/TERRITORY > United States of America > Hawaii > Hawaii > Kauai Island (22N159W0001)","COUNTRY/TERRITORY > United States of America > Hawaii > Hawaii > Molokai Island (21N157W0001)","COUNTRY/TERRITORY > United States of America > Hawaii > Honolulu > Kure Atoll (28N178W0001)","COUNTRY/TERRITORY > United States of America > Hawaii > Honolulu > Northwestern Hawaiian Islands (28N178W0000)","COUNTRY/TERRITORY > United States of America > Hawaii > Honolulu > Oahu (21N157W0003)","COUNTRY/TERRITORY > United States of America > Hawaii > Honolulu > Pearl and Hermes Reef (27N176W0001)","COUNTRY/TERRITORY > United States of America > Hawaii > Kauai > Niihau Island (21N160W0001)","COUNTRY/TERRITORY > United States of America > Hawaii > Maui > Lanai Island (20N156W0002)","COUNTRY/TERRITORY > United States of America > Hawaii > Maui > Maui Island (20N156W0004)","COUNTRY/TERRITORY > United States of America > Hawaiian Islands (21N157W0027)","COUNTRY/TERRITORY > United States of America > USA Minor Outlying Islands > Baker Island (00N176W0001)","COUNTRY/TERRITORY > United States of America > USA Minor Outlying Islands > Howland Island (00S176W0001)","OCEAN BASIN > Pacific Ocean > American Samoa > American Samoa (14S170W0000)","OCEAN BASIN > Pacific Ocean > American Samoa > Rose Atoll (14S168W0001)","OCEAN BASIN > Pacific Ocean > American Samoa > Tutuila Island (14S170W0016)","OCEAN BASIN > Pacific Ocean > Central Pacific Ocean > Baker Island > Baker Island (00N176W0001)","OCEAN BASIN > Pacific Ocean > Central Pacific Ocean > Hawaiian Islands (21N157W0027)","OCEAN BASIN > Pacific Ocean > Central Pacific Ocean > Hawaiian Islands > Hawaii > Hawaii (21N160W0000)","OCEAN BASIN > Pacific Ocean > Central Pacific Ocean > Hawaiian Islands > Hawaii Island > Hawaii Island (19N155W0003)","OCEAN BASIN > Pacific Ocean > Central Pacific Ocean > Hawaiian Islands > Kauai Island > Kauai Island (22N159W0001)","OCEAN BASIN > Pacific Ocean > Central Pacific Ocean > Hawaiian Islands > Lanai Island > Lanai Island (20N156W0002)","OCEAN BASIN > Pacific Ocean > Central Pacific Ocean > Hawaiian Islands > Maui Island > Maui Island (20N156W0004)","OCEAN BASIN > Pacific Ocean > Central Pacific Ocean > Hawaiian Islands > Molokai Island > Molokai Island (21N157W0001)","OCEAN BASIN > Pacific Ocean > Central Pacific Ocean > Hawaiian Islands > Niihau Island > Niihau Island (21N160W0001)","OCEAN BASIN > Pacific Ocean > Central Pacific Ocean > Hawaiian Islands > Oahu Island > Oahu (21N157W0003)","OCEAN BASIN > Pacific Ocean > Central Pacific Ocean > Howland Island > Howland Island (00S176W0001)","OCEAN BASIN > Pacific Ocean > Central Pacific Ocean > Northwestern Hawaiian Islands (28N178W0000)","OCEAN BASIN > Pacific Ocean > Central Pacific Ocean > Northwestern Hawaiian Islands > Kure Atoll (28N178W0001)","OCEAN BASIN > Pacific Ocean > Central Pacific Ocean > Northwestern Hawaiian Islands > Pearl and Hermes Reef (27N176W0001)","OCEAN BASIN > Pacific Ocean > Manu'a Group > Ofu Island (14S169W0013)","OCEAN BASIN > Pacific Ocean > Manu'a Group > Olosega Island (14S169W0014)","OCEAN BASIN > Pacific Ocean > Manu'a Group > Ta'u Island (14S169W0012)","OCEAN BASIN > Pacific Ocean > Western Pacific Ocean > Aguihan Island Reefs > Aguihan Island (Aguijan) (14N145E0006)","OCEAN BASIN > Pacific Ocean > Western Pacific Ocean > Asuncion Island > Asuncion Island (19N145E0001)","OCEAN BASIN > Pacific Ocean > Western Pacific Ocean > Guam > Guam (13N144E0000)","OCEAN BASIN > Pacific Ocean > Western Pacific Ocean > Mariana Archipelago > Northern Mariana Islands ( CNMI ) (18N146E0000)","OCEAN BASIN > Pacific Ocean > Western Pacific Ocean > Maug Island > Maug Island (20N145E0001)","OCEAN BASIN > Pacific Ocean > Western Pacific Ocean > Pagan Island > Pagan Island (18N145E0001)","OCEAN BASIN > Pacific Ocean > Western Pacific Ocean > Rota Island > Rota Island ( Luta ) (14N145E0007)","OCEAN BASIN > Pacific Ocean > Western Pacific Ocean > Saipan Island > Saipan Island (15N145E0002)","OCEAN BASIN > Pacific Ocean > Western Pacific Ocean > Sarigan Island > Sarigan Island (16N145E0003)","OCEAN BASIN > Pacific Ocean > Western Pacific Ocean > Tinian Island Reefs > Tinian Island (14N145E0005)","CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA > HAWAII","OCEAN > PACIFIC OCEAN > CENTRAL PACIFIC OCEAN > AMERICAN SAMOA","OCEAN > PACIFIC OCEAN > CENTRAL PACIFIC OCEAN > HAWAIIAN ISLANDS","OCEAN > PACIFIC OCEAN > NORTH PACIFIC OCEAN","OCEAN > PACIFIC OCEAN > SOUTH PACIFIC OCEAN","Mariana Archipelago","Papahanaumokuakea Marine National Monument","0T3EBB","0X8B6K","2J39XL","4KDA2E","6RT3B5","8UFY62","E00U92","HB8J3W","KXC5TK","MTG8N5"],"landingPage":"https://www.ncei.noaa.gov/contact","language":[],"license":"https://creativecommons.org/publicdomain/zero/1.0/","modified":"2025-10-31T00:00:00.000+00:00","publisher":{"@type":"org:Organization","name":"NOAA National Centers for Environmental Information"},"references":["https://www.fisheries.noaa.gov/inport/item/63093","https://www.fisheries.noaa.gov/inport/item/67851","https://www.fisheries.noaa.gov/inport/item/59172","https://www.fisheries.noaa.gov/inport/item/65764","https://www.fisheries.noaa.gov/inport/item/63097","https://doi.org/10.25923/h2q8-jv47","https://doi.org/10.25923/a9se-k649","https://doi.org/10.25923/w1k2-0y84","https://doi.org/10.25923/f19b-je14","https://repository.library.noaa.gov/view/noaa/48782"],"rights":"otherRestrictions","spatial":"145.812292,-14.54871,-178.34,28.385","temporal":"2014-05-06T00:00:00+00:00/2023-08-05T00:00:00+00:00","theme":["geospatial"],"title":"Benthic cover and other related datasets derived from Structure-from-Motion (SfM) imagery of coral reef ecosystems in Pacific Islands Regions"},"description":"This collection includes various coral reef data that was extracted by analyses of Structure-from-Motion (SfM) imagery of coral reef ecosystems across the Pacific Islands Regions by the Ecosystem Sciences Division (ESD) of the Pacific Islands Fisheries Science Center (PIFSC) of NOAA.  This collection includes coral reef benthic cover, vital rates (growth, mortality, recruitment), structural complexity, and coral demographic data.  Coral reef benthic cover, vital rates, and demographic data were produced by annotations of orthoprojections generated from SfM imagery, whereas structural complexity was derived from the digital elevation models, which were produced from orthomosaics, also generated from SfM imagery. Source SfM imagery is archived separately due to filesize.  Refer to specific accession pages for funding agencies, dates, and regions.","distribution_titles":["NCEI Dataset Landing Page","Browse granules","Search for granules","https://www.fisheries.noaa.gov/inport/item/63093","https://www.fisheries.noaa.gov/inport/item/67851","https://www.fisheries.noaa.gov/inport/item/59172","https://www.fisheries.noaa.gov/inport/item/65764","https://www.fisheries.noaa.gov/inport/item/63097","https://doi.org/10.25923/h2q8-jv47","https://doi.org/10.25923/a9se-k649","https://doi.org/10.25923/w1k2-0y84","https://doi.org/10.25923/f19b-je14","https://repository.library.noaa.gov/view/noaa/48782","GCMD Keyword Forum Page","NCEI Contact Information","NOAA Library website"],"harvest_record":"https://catalog.data.gov/harvest_record/fbe13af9-7b61-4b5e-a109-54941d28e8d9","harvest_record_raw":"https://catalog.data.gov/harvest_record/fbe13af9-7b61-4b5e-a109-54941d28e8d9/raw","harvest_record_transformed":"https://catalog.data.gov/harvest_record/fbe13af9-7b61-4b5e-a109-54941d28e8d9/transformed","has_download":false,"has_spatial":true,"identifier":"https://data.noaa.gov/waf/NOAA/NESDIS/ncei/accessions/iso/xml/PIFSC-SfM-DerivedData.xml","keyword":["0209247","0244392","0253462","0257945","0268310","0282457","0283598","0286084","0307802","0308745","BENTHIC SPECIES","biological data","CORAL","CORAL - BLEACHING","CORAL - CENSUS","CORAL - COLONY SIZE","CORAL - FISH BITES","CORAL - SPECIES IDENTIFICATION","DEBRIS","DEPTH - BOTTOM","HABITAT - BENTHIC","REEF AND/OR BOTTOM REGIME - PERCENT COVER","photograph","scale","swimmer/diver","visual observation","biological","derived products","GIS product","imagery","in situ","laboratory analyses","survey - biological","survey - coral reef","NOAA Ship Hi'ialakai","NOAA Ship Oscar Elton Sette","NOAA Ship Rainier","NOAA Pacific Islands Fisheries Science Center","NOAA Pacific Islands Fisheries Science Center, Ecosystem Sciences Division","NOAA Pacific Islands Fisheries Science Center","Coral Reef Conservation Program (CRCP)","CORAL REEF STUDIES","National Coral Reef Monitoring Program (NCRMP)","Pacific Reef and Assessment Monitoring Program (Pacific RAMP)","US DOC; NOAA; Office of Oceanic and Atmospheric Research; Ocean Acidification Program (OAP)","Coastal Waters of Hawaii","Hawaiian Islands Humpback Whale National Marine Sanctuary","Marianas Trench Marine National Monument","National Marine Sanctuary of American Samoa","North Pacific Ocean","Northwest Pacific Ocean (limit-180)","Pacific Remote Islands Marine National Monument","Papah\u0101naumoku\u0101kea Marine National Monument","Philippine Sea","Rose Atoll Marine National Monument","South Pacific Ocean","oceanography","CRED","CREP","Coral Reef Ecosystem Division","Coral Reef Ecosystem Program","ESD","Ecosystem Sciences Division","NCRMP","National Coral Reef Monitoring Proram","PIFSC","Pacific Island Fisheries Science Center","RAMP","Reef Assessment and Monitoring Program","Scripps Institution of Oceanography","CRED","CREP","Coral Reef Ecosystem Division","Coral Reef Ecosystem Program","DAR","DLNR","Division of Aquatic Resources","ESD","Ecosystem Sciences Division","Hawai'i Department of Land and Natural Resources","NCRMP","National Coral Reef Monitoring Proram","PIFSC","Pacific Island Fisheries Science Center","Pacific Islands Fisheries Science Center","RAMP","Reef Assessment and Monitoring Program","Scripps Institution of Oceanography","DOC/NOAA/NMFS > National Marine Fisheries Service, NOAA, U.S. Department of Commerce","DOC/NOAA/NMFS/PIFSC/ESD > Ecosystem Sciences Division, Pacific Islands Fisheries Science Center, National Marine Fisheries Service, NOAA, U.S. Department of Commerce","31283","31349","31360","31361","31430","31525","743","Assessing impacts of Hawaii's 2019 coral bleaching event on coral recovery and coral communities","Determining whether herbivore-focused management strategies enhance critical ecosystem functions provided by fishes","Hawai'i coral bleaching assessment and analysis","Mapping Reef Fish Patterns Across the Marianas Archipelago","Maximizing information and resilience indicators extracted from monitoring efforts to inform fisheries management","National Coral Reef Monitoring Program (NCRMP)","Scaling up coral reef science through Photogrammetry and Artificial Intelligence","Hawaii Coral Bleaching Collaborative (HCBC)","Papahanaumokuakea Marine Debris Project","Numeric Data Sets > Benthic","Map Images > Coral Mapping","Numeric Data Sets > Benthic","Numeric Data Sets > Biology","EARTH SCIENCE > Biosphere > Zoology > Corals > Feeding Scars On Hard Coral > COTS","EARTH SCIENCE > Biosphere > Zoology > Corals > Feeding Scars On Hard Coral > Fish","EARTH SCIENCE > Biosphere > Zoology > Corals > Feeding Scars On Hard Coral > Gastropod","EARTH SCIENCE > Biosphere > Zoology > Corals > Reef Damage Assessment > Biological","EARTH SCIENCE > Biosphere > Zoology > Corals > Reef Monitoring and Assessment > Benthos Analysis > Quadrat Monitoring > In Situ","EARTH SCIENCE > Biosphere > Zoology > Corals > Reef Monitoring and Assessment > Benthos Analysis > Quadrat Monitoring > Photograph Analysis","EARTH SCIENCE > Biosphere > Aquatic Habitat > Benthic Habitat","EARTH SCIENCE > Biosphere > Aquatic Habitat > Reef Habitat","EARTH SCIENCE > Biosphere > Ecological Dynamics > Predation > Coral Predation","EARTH SCIENCE > Biosphere > Vegetation > Algae","EARTH SCIENCE > Biosphere > Vegetation > Algae > Algal Cover","EARTH SCIENCE > Biosphere > Vegetation > Algae > Coralline Algae","EARTH SCIENCE > Biosphere > Vegetation > Algae > Crustose Coralline Algae","EARTH SCIENCE > Biosphere > Vegetation > Algae > Fleshy Macroalgae","EARTH SCIENCE > Biosphere > Vegetation > Algae > Turf Algae","EARTH SCIENCE > Biosphere > Zoology > Corals","EARTH SCIENCE > Biosphere > Zoology > Corals > Coral Condition","EARTH SCIENCE > Biosphere > Zoology > Corals > Coral Diseases > Bleaching","EARTH SCIENCE > Biosphere > Zoology > Corals > Coral Growth","EARTH SCIENCE > Biosphere > Zoology > Corals > Feeding Scars On Hard Coral > COTS","EARTH SCIENCE > Biosphere > Zoology > Corals > Feeding Scars On Hard Coral > Fish","EARTH SCIENCE > Biosphere > Zoology > Corals > Feeding Scars On Hard Coral > Gastropod","EARTH SCIENCE > Biosphere > Zoology > Corals > Reef Damage Assessment > Biological","EARTH SCIENCE > Biosphere > Zoology > Corals > Reef Damage Assessment > Marine Debris","EARTH SCIENCE > Biosphere > Zoology > Corals > Reef Monitoring and Assessment","EARTH SCIENCE > Biosphere > Zoology > Corals > Reef Monitoring and Assessment > Benthos Analysis","EARTH SCIENCE > Biosphere > Zoology > Corals > Reef Monitoring and Assessment > Benthos Analysis > Quadrat Monitoring > Photograph Analysis","EARTH SCIENCE > Biosphere > Zoology > Corals > Reef Monitoring and Assessment > Coral Colony Size and Condition","EARTH SCIENCE > Biosphere > Zoology > Corals > Reef Monitoring and Assessment > Damage Assessment > Visual","EARTH SCIENCE > Biosphere > Zoology > Corals > Reef Monitoring and Assessment > GIS","EARTH SCIENCE > Biosphere > Zoology > Corals > Reef Monitoring and Assessment > In Situ Biological","EARTH SCIENCE > Biosphere > Zoology > Corals > Reef Monitoring and Assessment > Photographic Analysis","EARTH SCIENCE > Biosphere > Zoology > Corals > Scleractinia (stony corals)","EARTH SCIENCE > Biosphere > Zoology > Sponges","EARTH SCIENCE > Oceans > Bathymetry/Seafloor Topography > Hard Seafloor Substrate","EARTH SCIENCE > Oceans > Coastal Processes > Coral Reefs","EARTH SCIENCE > Oceans > Coastal Processes > Coral Reefs > Coral Reef Ecology","EARTH SCIENCE > Oceans > Coastal Processes > Coral Reefs > Coral Reef Ecology > Benthic biology","EARTH SCIENCE > Oceans > Coastal Processes > Coral Reefs > Coral Reef Ecology > Coral Cover","EARTH SCIENCE > Oceans > Coastal Processes > Coral Reefs > Coral Reef Ecology > Hard Coral Cover","EARTH SCIENCE > Oceans > Coastal Processes > Coral Reefs > Coral Reef Ecology > Rugosity","EARTH SCIENCE > Oceans > Marine Biology > Coral","EARTH SCIENCE > Oceans > Marine Biology > Coral Communities","EARTH SCIENCE > Oceans > Marine Biology > Marine Invertebrates","EARTH SCIENCE > BIOLOGICAL CLASSIFICATION","EARTH SCIENCE > BIOSPHERE > ECOSYSTEMS > MARINE ECOSYSTEMS > BENTHIC","EARTH SCIENCE > BIOSPHERE > ECOSYSTEMS > MARINE ECOSYSTEMS > REEF > CORAL REEF","EARTH SCIENCE > OCEANS > BATHYMETRY/SEAFLOOR TOPOGRAPHY > WATER DEPTH","EARTH SCIENCE > OCEANS > COASTAL PROCESSES > CORAL REEFS > CORAL BLEACHING","EARTH SCIENCE > OCEANS > MARINE ENVIRONMENT MONITORING > MARINE SUBMERGED DEBRIS","EARTH SCIENCE > SOLID EARTH > GEOMORPHIC LANDFORMS/PROCESSES > COASTAL LANDFORMS > CORAL REEFS","CORAL - CONDITION","CORAL - FISH BITES","CORAL - FISH BITES (count and category)","CORAL - PATCH SIZE","CORAL - SPECIES IDENTIFICATION","Complexity metrics","Corallivory","Fractal dimension","Height range","Reef habitat complexity","Rugosity","SfM","Structure from Motion","Structure from Motion (SfM)","digital elevation model","VISUAL OBSERVATIONS > VISUAL OBSERVATIONS","Agisoft Metashape","Agisoft Metashape software","ArcGIS","ArcGIS Pro","Computer","Dive Computer","GIS","R software","TagLab","Viscore","Ships","Hi'ialakai (call sign: WTEY, ICES code: 33HL, 2004-)","OSCAR ELTON SETTE (call sign: WTEE, ICES code: 33OC, 2003-)","RAINIER (call sign: WTEF, ICES code: 315R, 1968-)","M/V IMUA","Various Small Vessels","COUNTRY/TERRITORY > Northern Mariana Islands > Asuncion Island > Asuncion Island (19N145E0001)","COUNTRY/TERRITORY > Northern Mariana Islands > Maug > Maug Island (20N145E0001)","COUNTRY/TERRITORY > Northern Mariana Islands > Northern Mariana Islands > Northern Mariana Islands ( CNMI ) (18N146E0000)","COUNTRY/TERRITORY > Northern Mariana Islands > Pagan > Pagan Island (18N145E0001)","COUNTRY/TERRITORY > Northern Mariana Islands > Saipan > Saipan Island (15N145E0002)","COUNTRY/TERRITORY > United States of America > Guam > Guam (13N144E0000)","COUNTRY/TERRITORY > United States of America > Hawaii > Honolulu > Oahu (21N157W0003)","OCEAN BASIN > Pacific Ocean > Central Pacific Ocean > Hawaiian Islands > Oahu Island > Oahu (21N157W0003)","OCEAN BASIN > Pacific Ocean > Western Pacific Ocean > Asuncion Island > Asuncion Island (19N145E0001)","OCEAN BASIN > Pacific Ocean > Western Pacific Ocean > Guam > Guam (13N144E0000)","OCEAN BASIN > Pacific Ocean > Western Pacific Ocean > Mariana Archipelago > Northern Mariana Islands ( CNMI ) (18N146E0000)","OCEAN BASIN > Pacific Ocean > Western Pacific Ocean > Maug Island > Maug Island (20N145E0001)","OCEAN BASIN > Pacific Ocean > Western Pacific Ocean > Pagan Island > Pagan Island (18N145E0001)","OCEAN BASIN > Pacific Ocean > Western Pacific Ocean > Saipan Island > Saipan Island (15N145E0002)","COUNTRY/TERRITORY > Northern Mariana Islands > Aguihan > Aguihan Island (Aguijan) (14N145E0006)","COUNTRY/TERRITORY > Northern Mariana Islands > Asuncion Island > Asuncion Island (19N145E0001)","COUNTRY/TERRITORY > Northern Mariana Islands > Maug > Maug Island (20N145E0001)","COUNTRY/TERRITORY > Northern Mariana Islands > Northern Mariana Islands > Northern Mariana Islands ( CNMI ) (18N146E0000)","COUNTRY/TERRITORY > Northern Mariana Islands > Pagan > Pagan Island (18N145E0001)","COUNTRY/TERRITORY > Northern Mariana Islands > Rota > Rota Island ( Luta ) (14N145E0007)","COUNTRY/TERRITORY > Northern Mariana Islands > Saipan > Saipan Island (15N145E0002)","COUNTRY/TERRITORY > Northern Mariana Islands > Sarigan Island > Sarigan Island (16N145E0003)","COUNTRY/TERRITORY > Northern Mariana Islands > Tinian > Tinian Island (14N145E0005)","COUNTRY/TERRITORY > United States of America > American Samoa > 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This program addresses the many factors at organismal, population, community, and ecosystem levels that determine how HAB species respond to, and potentially alter their environment, the manner in which HAB species affect food-web and community interactions. 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These data were generated using a suite of landscape and thermal predictor variables and point data from walleye electrofishing surveys. Data are represented as probabilities (range 0-1) of recruitment during each time period (current, mid-century and late-century). Data were generated using a Random Forest approach. The final model contained three variables: lake area, growing degree days (base 5 \u00b0C), and the upstream probability of adults in the connected river system. Lake area and growing degree days were the most influential predictor variables (measured by variable importance).","distribution":[{"@type":"dcat:Distribution","accessURL":"https://doi.org/10.5066/P9ZLM6UK","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.646ed3e0d34e4e58932cf826.xml","format":"XML","mediaType":"text/xml","title":"Original Metadata"}],"identifier":"http://datainventory.doi.gov/id/dataset/USGS_646ed3e0d34e4e58932cf826","keyword":["Midwest","USGS:646ed3e0d34e4e58932cf826","Wisconsin","biota","climate change","environment","farming","fisheries"],"modified":"2026-09-24T00:00:00Z","publisher":{"@type":"org:Organization","name":"U.S. Geological Survey"},"spatial":"-92.8894, 42.4721, -86.7700, 46.7700","theme":["geospatial"],"title":"Current and projected mid- and late-century walleye recruitment in inland lakes of Wisconsin, USA"},"description":"These data represent current and projected mid- and late-century adult walleye recruitment in inland lakes of Wisconsin, USA. These data were generated using a suite of landscape and thermal predictor variables and point data from walleye electrofishing surveys. Data are represented as probabilities (range 0-1) of recruitment during each time period (current, mid-century and late-century). Data were generated using a Random Forest approach. The final model contained three variables: lake area, growing degree days (base 5 \u00b0C), and the upstream probability of adults in the connected river system. Lake area and growing degree days were the most influential predictor variables (measured by variable importance).","distribution_titles":["Digital Data","Original Metadata"],"harvest_record":"https://catalog.data.gov/harvest_record/d07d1686-44c3-4fa1-8a6b-6b4c41da32fd","harvest_record_raw":"https://catalog.data.gov/harvest_record/d07d1686-44c3-4fa1-8a6b-6b4c41da32fd/raw","has_download":true,"has_spatial":true,"identifier":"http://datainventory.doi.gov/id/dataset/USGS_646ed3e0d34e4e58932cf826","keyword":["Midwest","USGS:646ed3e0d34e4e58932cf826","Wisconsin","biota","climate change","environment","farming","fisheries"],"last_harvested_date":"2026-09-27T00:10:51.947928","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":"current-and-projected-mid-and-late-century-walleye-recruitment-in-inland-lakes-of-wisconsi","spatial_centroid":{"lat":44.19126,"lon":-90.44163999999999},"spatial_shape":{"coordinates":[[[-92.8894,42.4721],[-92.8894,46.77],[-86.77,46.77],[-86.77,42.4721],[-92.8894,42.4721]]],"type":"Polygon"},"theme":["geospatial"],"title":"Current and projected mid- and late-century walleye recruitment in inland lakes of Wisconsin, USA","type":"dataset"},{"_score":12.538296,"_sort":[1790467846092,12.538296,1,"8ccf2101-d072-4bd1-8b5f-26717e00cb09"],"dcat":{"@type":"dcat:Dataset","accessLevel":"non-public","contactPoint":{"@type":"vcard:Contact","fn":"NOAA National Centers for Environmental Information","hasEmail":"mailto:ncei.info@noaa.gov"},"describedByType":"application/octet-stream","description":"Near-shore shallow water Conductivity-Temperature-Depth (CTD) surveys provided in this collection were conducted at selected sites around the Pacific Remote Island Areas as part of the ongoing National Coral Reef Monitoring Program (NCRMP). 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Our study specifically addressed the following questions: (1) How do ecological processes and ecosystem properties differ between salt marshes and mangrove forests; (2) As mangrove forests develop, how do their ecosystem properties change and how do these properties compare to salt marshes; (3) How do plant-soil interactions across mangrove forest structural gradients differ among three distinct locations that span the northern Gulf of Mexico; and (4) What are the implications of mangrove forest encroachment and development into salt marsh in terms of soil development, carbon and nitrogen storage, and soil strength? To address these questions, we utilized the salt marshes and natural mangrove forest structural gradients present at three distinct locations in the northern Gulf of Mexico: Cedar Key (Florida), Port Fourchon (Louisiana), and Port Aransas (Texas). Each of these locations represents a distinct combination of climate-driven abiotic conditions. We quantified relationships between plant community composition and structure, soil and porewater physicochemical properties, hydroperiod, and climatic conditions. The suite of measurements that we collected provide initial insights into how different geographic areas of an ecotone, with different environmental conditions, may be impacted by mangrove forest expansion and development, and how these changes may alter the supply of specific ecosystem goods and services. 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cylinder","Petite Ponar benthic grab","Ponar grab sampler","Pump","Purse seine net","Remotely operated vehicle","Sabiki hook and line fishing","Sediment grab sampler","Shipek grab sampler","Stainless steel bucket","Stainless steel spoon","Steel bucket","Surface water intake","Trowel","Van Dorn sampler","Van Veen grab","Van Veen grab sampler","Water pump","beam trawl","bottom trawling","box corer","cage","cylindrical crab trap","glass jar","hand collection","hand line","handpicking","longline with hooks","market purchase","metal shovel","metallic trowel","minnow trap","polycarbonate bottles","quadrat","shovel","stainless steel sampler","stainless steel shovel","stainless steel spatula","stainless-steel spatula","steel corer","stranding","surface gillnet","zooplankton net","SUBMARINE","Ships","AKADEMIK TRYOSHNIKOV (call sign: UBXH3, ICES code: RUB3, 2012-)","CELTIC VOYAGER (call sign: EIQN, ICES code: 45CV, 1997-)","CORWITH CRAMER (call sign: WTF3319, ICES code: 33CC, 1988-)","Cabo de Hornos (call sign: CB7960, ICES code: 20HZ, 2004-)","Celtic Explorer (call sign: EIGB, ICES code: 45CE, 2003-)","Discovery (call sign: 2FGX5, ICES code: 74EQ, 2013-)","G.O. SARS (call sign: LMEL, ICES code: 58G2, 2003-)","LA PELAGIA (call sign: FTNJ, ICES code: 35LG, 1965-1986)","NEW HORIZON (call sign: WKWB, ICES code: 32NM, 1978-2015)","ODEN (call sign: SMLQ, ICES code: 77DN)","OKEANOS EXPLORER (call sign: WTDH, ICES code: 334A, 2008-)","ORION (ICES code: 28OR)","PELAGIA (call sign: PGRQ, ICES code: 64PE, 1991-)","POINT SUR (call sign: WSC2276, ICES code: 32P0, 1980-)","Polarstern (call sign: DBLK, ICES code: 06AQ, 1982-)","Robert C. Seamans (call sign: WDA4486, ICES code: 33GY, 2001-)","S. A. Agulhas II (call sign: ZSNO, ICES code: 91AH, 2009-)","SEA DRAGON (ICES code: 32S2)","SIR JAMES CLARK ROSS (ICES code: 587O, 1923-1930)","SOLANDER (call sign: VMQ9273, ICES code: 09CX)","SOUTHERN SURVEYOR (call sign: VLHJ, ICES code: 09SS, 1988-2014)","Tara (call sign: FVNM, ICES code: 35XI, 2009-)","URANIA (ICES code: 64UR)","XIANG YANG HONG 03 (call sign: BNVB, ICES code: 76X3)","\u00c1ngeles Alvari\u00f1o (call sign: EASE, ICES code: 29AJ, 2012-)","\u0410\u043a\u0430\u0434\u0435\u043c\u0438\u043a \u041c\u0441\u0442\u0438\u0441\u043b\u0430\u0432 \u041a\u0435\u043b\u0434\u044b\u0448 (ICES code: 90BP, 1981-1992)","\u041f\u0420\u041e\u0424\u0415\u0421\u0421\u041e\u0420 \u041a\u0410\u0413\u0410\u041d\u041e\u0412\u0421\u041a\u0418\u0419 (call sign: UTTW, ICES code: 90ZH, 1987-1991)","AKADEMIK TRYOSHNIKOV (call sign UBXH3 - ICES code RUB3)","Angeles Alvarino (call sign EASE - ICES code 29AJ)","Comac Enterprise","Dongfeng Race Team","MRV Alba na Mara","MRV Scotia","MS Malippo","MS \u201cMalippo\u201d","MV Maersk Launcher","MV Maersk Transporter","Mapfre","NEW HORIZON (call sign WKWB - ICES code 32NM)","ORV Alguita","Okeanos Explorer (call sign WTDH - ICES code 334A)","R.V Celtic Explorer","R.V. G. O. Sars","R.V. Minerva","R/V Aegeao","R/V Akademik Mstislav Keldysh","R/V Angeles Alvari\u00f1o","R/V Cap\u2019n Bert","R/V Celtic Voyager","R/V Filia","R/V Kiya","R/V Mediterranean Explorer","R/V Mtafiti","R/V SURAT ARASTIRMA","R/V Tara","R/V Xuelong","ROVs","RRS Discovery","RRS James Clark Ross","RV Celtic Explorer","RV IV Lluerna","RV Orion","RV Pelagia","RV Polarstern","RV Professor Kaganovskiy","RV Sir John Murray","RV Stad Amsterdam","RV XIANG YANG HONG 03","S.A. AGULHAS II (call sign ZSNO - ICES code 91AH)","SV Mir","SV Rainbow Warrior","SV Sea Dragon","Sun Hung Kai Scallywag","Team AkzoNobel","Team Brunel","Turn the Tide on Plastic","Vestas 11th Hour Racing","GEOGRAPHIC REGION > GLOBAL OCEAN","Waterbodies > Gulf of Mexico","Alaska","Atlantic Ocean","Australia","Bahamas","Barents Seas","Bay of Calvi","Beibu Gulf","Brazil","Bulgarian Black Sea","Canada","Chile","Columbia","Costa Rica","Dominican Republic","East-Siberian Sea","Eastern Mediterranean Sea","Eastern Pacific Ocean","Equatorial Guinea","France","Gabes Gulf","Gal\u00e1pagos","Global","Global Ocean","Great Barrier Reef","Greece","Guatemela","Gulf of Guayaquil","Gulf of Lion","Gulf of Oristano","Gulf of Venice","Kenya","Kuroshio Current","Laptev Sea","Levantine Sea","Manila Bay","Mexico","NW Mediterranean Sea","Narragansett Bay","New Zealand","North Atlantic Subtropical Gyre","North-West Mediterranean Sea","Northern Adriatic Sea","Northwest Pacific","Northwestern Mediterranean Sea","Pacific Ocean","Playa Grande beach: Tenerife, Canary Islands, Spain","San Francisco Bay","Saronikos Gulf","Scotland","Sea of Oman","Sri Lanka","Taiwan","United Arab Emirates","United Kingdom","United States","Western Indian Ocean","Western Mediterranean","Western North Pacific Ocean","0370R2","06NWEE","09PKB9","0CCB5U","0WBCYL","123CE1","139DEU","1RP301","226PKB","22YR0K","26430G","2DM697","2M20XB","2X9KKU","31JGEX","35F99T","37Y05A","383Y9U","3BFHT5","3JK15T","3KC69K","4252PG","4520RA","4JPDWP","4M115G","56JD45","575D5A","5XFHCF","6D80CE","6NGB2H","74EPET","77WG2K","7AB52E","83849B","897C1N","8A0WYC","8HHW34","93J4B6","96BCU7","9J3P32","9RFULE","9XJUG9","9XWYE5","A03JJG","A6C6B1","A8RCBD","B0C93N","B8LX93","BAU8LM","BFFY91","BMEKJC","C1W8UH","C75PAK","CU2GE7","D7B70T","DCK5W1","DFTHMR","DMM5WT","DTXFX2","E28YL3","EA11N3","EDE1PT","EFD6MK","EKJ0L9","ERWNCY","ETL10F","F1KAUU","FJM26N","FR44XP","G4X6P2","G5HM13","GFGLY1","GY7KLK","H1MENE","H1R14M","H34EKT","H4MBXJ","HKP7PB","J1XPR6","K2U4C5","KF4KLC","KTLDD1","KXW1J8","LA71JF","LPRRLM","LUBKCP","M5FARJ","M8NU9G","MK0DL7","N1PPYL","N37EY9","NBM4KM","NCLL0F","NCWWEH","NDFWW7","NETMK9","NMMXKB","P1282M","P6L6AF","PNUBR9","PYTFGE","RCR7LN","RJ6BCX","TGPMFR","TKM7FJ","TTMNDE","U21DKX","UGU4PM","W8JMJG","WDPK8Y","WU1NRY","X3TWUH","X54F7A","Y8EGBM","YMF0NM","YMXDHP","YPXRBR","YY6CU4"],"landingPage":"https://www.ncei.noaa.gov/contact","language":[],"license":"https://creativecommons.org/publicdomain/zero/1.0/","modified":"2026-05-04T00:00:00.000+00:00","publisher":{"@type":"org:Organization","name":"NOAA National Centers for Environmental Information"},"references":["https://doi.org/10.1038/s41597-023-02632-y"],"rights":"otherRestrictions","spatial":"180.0,-72.0,-180.0,90.0","temporal":"1972-04-20T00:00:00+00:00/1972-04-20T00:00:00+00:00","theme":["geospatial"],"title":"The NOAA NCEI Global Marine Microplastics Data Collection (1972-present)"},"description":"Microplastics (i.e., plastics measuring less than 5mm) pollution is a growing problem affecting coastal communities, marine ecosystems, aquatic life, and human health. The widespread occurrence of marine microplastics, and the need to curb its threats, require expansive, and continuous monitoring. While microplastic research has increased in recent years and generated significant volumes of data, there is a lack of a robust, open access, and long-term aggregation of this data. The National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Information (NCEI) marine microplastic data collection provides a global open access to marine microplastic data on an easily discoverable and accessible GIS web map and data portal (https://www.ncei.noaa.gov/products/microplastics). The objective of this data portal is to develop a repository where microplastics data are aggregated, archived, and served in a user friendly, consistent, and reliable manner. This work contributes to NCEI\u2019s efforts towards data standardization, integration, harmonization, and interoperability among national and international collaborators for monitoring global marine microplastics.","distribution_titles":["Marine Microplastics","NCEI Dataset Landing Page","Browse granules","Search for granules","https://doi.org/10.1038/s41597-023-02632-y","GCMD Keyword Forum Page","NCEI Contact Information","National Oceanic and Atmospheric Administration (NOAA) website"],"harvest_record":"https://catalog.data.gov/harvest_record/2f901948-d702-4796-a6bc-b991c2587813","harvest_record_raw":"https://catalog.data.gov/harvest_record/2f901948-d702-4796-a6bc-b991c2587813/raw","harvest_record_transformed":"https://catalog.data.gov/harvest_record/2f901948-d702-4796-a6bc-b991c2587813/transformed","has_download":false,"has_spatial":true,"identifier":"https://data.noaa.gov/waf/NOAA/NESDIS/ncei/accessions/iso/xml/NCEI-Marine-Microplastics.xml","keyword":["0170967","0211007","0211008","0211009","0232040","0252260","0253140","0253447","0253448","0253450","0253923","0259486","0259524","0259525","0259526","0259692","0260245","0270520","0270528","0270530","0270539","0270542","0271964","0275966","0275967","0275968","0276017","0276018","0276019","0276020","0276021","0276263","0276264","0276265","0276266","0276267","0276422","0276482","0277496","0277497","0277532","0277839","0277995","0277996","0277997","0277998","0277999","0278002","0278059","0278060","0278269","0278270","0279321","0279322","0279323","0279324","0279325","0279326","0280519","0280675","0280922","0281206","0282701","0282703","0284765","0285699","0285700","0288866","0289355","0289356","0289931","0290791","0290836","0291179","0291180","0292552","0292615","0292616","0292621","0292622","0292623","0292729","0292955","0294675","0294676","0294865","0295115","0295694","0295696","0296746","0297601","0297602","0298195","0298196","0299220","0301239","0302465","0304891","0305020","0305021","0305567","0306232","0307628","0308014","0308031","0313391","0313392","0313393","0314176","0314177","0314178","0314179","0314180","0314555","0314556","0314557","0314558","0314559","microplastic concentration","Avani trawl net","barometer","bottle","compass","corer","dredge","Flow-through pump","fluorescence microscope","Fourier-transform infrared (FTIR) spectrometer","GPS","Manta net","metallic bucket","microscope","net","net - plankton net","net - zooplankton net","Neuston net","Niskin bottle","pump sampler","Raman spectrometer","sediment sampler - corer","sediment sampler - grab","sediment sieve","temperature sensor","thermosalinograph","trap","trawl","in situ","laboratory analyses","AKADEMIK MSTISLAV KELDYSH","AKADEMIK TRYOSHNIKOV (Akademik Treshnikov)","Angeles Alvarino","Cabo de Hornos","Celtic Explorer","CELTIC VOYAGER","CORWITH CRAMER","G.O. 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SEAMANS","Tara","URANIA","USS Sea Dragon","XIANG YANG HONG 03","5 Gyres Institute","Adventure Scientists","Atlantic Technological University","Auburn University","Bangladesh Agricultural University","Beibu Gulf University","Bulgarian Academy of Sciences","Catholic University of Valencia Saint Vincent Martyr","Centre for Environment, Fisheries and Aquaculture Science","Chulalongkorn University","City University of Hong Kong","Duke University","EAN University","Federal University of Par\u00e1","Fisheries College and Research Institute, Thoothukudi","GEOMAR Helmholtz Centre for Ocean Research Kiel","Goa University","Hellenic Centre for Marine Research","Italian Institute for Environmental Protection and Research","Kenya Marine and Fisheries Research Institute","Manipal Institute of Technology","Marine Scotland Science","Mediterranean Agronomic Institute of Bari","Metropolitan Autonomous University","National Research Council","National Research Council, Institute of Marine Sciences","National School of Marine Science and Coastal Planning","National Taiwan University, Department of Geosciences","NOAA National Centers for Coastal Ocean Science","Norwegian Institute for Water Research","NOVA University Lisbon","Oceaneye Association","Plymouth Marine Laboratory","Polytechnic University of Tapachula","Pontifical Catholic University of Rio de Janeiro","Recep Tayyip Erdo\u011fan University","Scion Research","Scottish Association for Marine Science","Scripps Institution of Oceanography","Sea Education Association","Sorbonne University","State Oceanic Administration, Third Institute of Oceanography","Sultan Qaboos University","The Ocean Cleanup","The University of Newcastle, Australia","The University of Southern Mississippi","The University of Texas at Austin","The University of Western Australia","Tokyo University of Marine Science and Technology","University of Alaska Anchorage","University of Barcelona","University of Copenhagen","University of Cuenca","University of C\u00e1diz","University of Exeter","University of Ferrara","University of Fribourg","University of Ghana","University of Haifa","University of La Laguna","University of Li\u00e8ge","University of Nova Gorica","University of Rhode Island, Graduate School of Oceanography","University of Rovira i Virgili","University of South Florida","University of the Philippines Diliman","University of the South Pacific","University of the West Indies","University of Tokyo","University of Toronto","University of Washington Joint Institute for the Study of the Atmosphere and Ocean","UT Austin Marine Science Institute","Woods Hole Oceanographic Institution","Zhejiang University of Technology","5 Gyres Institute","Atlantic Technological University","Auburn University","Bangladesh Agricultural University","Beibu Gulf University","Bulgarian Academy of Sciences","Catholic University of Valencia Saint Vincent Martyr","Centre for Environment, Fisheries and Aquaculture Science","Chulalongkorn University","City University of Hong Kong","Duke University","EAN University","Federal University of Par\u00e1","Fisheries College and Research Institute, Thoothukudi","GEOMAR Helmholtz Centre for Ocean Research Kiel","Goa University","Hellenic Centre for Marine Research","Italian Institute for Environmental Protection and Research","Kenya Marine and Fisheries Research Institute","Manipal Institute of Technology","Marine Scotland Science","Mediterranean Agronomic Institute of Bari","Metropolitan Autonomous University","Minjiang University","Mississippi State University","National Research Council","National Research Council, Institute of Marine Sciences","National School of Marine Science and Coastal Planning","National Taiwan University, Department of Geosciences","NOAA National Centers for Coastal Ocean Science","Norwegian Institute for Water Research","NOVA University Lisbon","Oceaneye Association","Plymouth Marine Laboratory","Polytechnic University of Tapachula","Pontifical Catholic University of Rio de Janeiro","Recep Tayyip Erdo\u011fan University","Sail and Explore Association","Scion Research","Scottish Association for Marine Science","Scripps Institution of Oceanography","Sorbonne University","State Oceanic Administration, Third Institute of Oceanography","Sultan Qaboos University","The Ocean Cleanup","The University of Texas at Austin","The University of Western Australia","Tokyo University of Marine Science and Technology","University of Alaska Anchorage","University of Barcelona","University of Copenhagen","University of Cuenca","University of C\u00e1diz","University of Exeter","University of Ferrara","University of Ghana","University of Haifa","University of La Laguna","University of Li\u00e8ge","University of Nova Gorica","University of Rhode Island, Graduate School of Oceanography","University of Rovira i Virgili","University of South Florida","University of the Philippines Diliman","University of the South Pacific","University of the West Indies","University of Tokyo","University of Toronto","University of Washington Joint Institute for the Study of the Atmosphere and Ocean","UT Austin Marine Science Institute","Woods Hole Oceanographic Institution","Zhejiang University of Technology","California Cooperative Fisheries Investigation (CalCOFI)","Ecosystems &  Fisheries-Oceanography Coordinated Investigations (EcoFOCI)","World-Wide Distribution","oceanography","DE/GEOMAR > GEOMAR - Helmholtz Centre for Ocean Research Kiel, Germany","DOC/NOAA/NOS/NCCOS > National Centers for Coastal Ocean Science, National Ocean Service, NOAA, U.S. Department of Commerce","NO/NIVA > Norwegian Institute for Water Research, Norway","TUMST > Tokyo University of Marine Science and Technology","UH&I-UK/SAMS > Scottish Association for Marine Science, University of Highlands and Islands, UK","UK/NERC/PML > Plymouth Marine Laboratory, Natural Environment Research Council, United Kingdom","URI/GSO > Graduate School 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cylinder","Petite Ponar benthic grab","Ponar grab sampler","Pump","Purse seine net","Remotely operated vehicle","Sabiki hook and line fishing","Sediment grab sampler","Shipek grab sampler","Stainless steel bucket","Stainless steel spoon","Steel bucket","Surface water intake","Trowel","Van Dorn sampler","Van Veen grab","Van Veen grab sampler","Water pump","beam trawl","bottom trawling","box corer","cage","cylindrical crab trap","glass jar","hand collection","hand line","handpicking","longline with hooks","market purchase","metal shovel","metallic trowel","minnow trap","polycarbonate bottles","quadrat","shovel","stainless steel sampler","stainless steel shovel","stainless steel spatula","stainless-steel spatula","steel corer","stranding","surface gillnet","zooplankton net","SUBMARINE","Ships","AKADEMIK TRYOSHNIKOV (call sign: UBXH3, ICES code: RUB3, 2012-)","CELTIC VOYAGER (call sign: EIQN, ICES code: 45CV, 1997-)","CORWITH CRAMER (call sign: WTF3319, ICES code: 33CC, 1988-)","Cabo de Hornos (call sign: CB7960, ICES code: 20HZ, 2004-)","Celtic Explorer (call sign: EIGB, ICES code: 45CE, 2003-)","Discovery (call sign: 2FGX5, ICES code: 74EQ, 2013-)","G.O. 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Agulhas II (call sign: ZSNO, ICES code: 91AH, 2009-)","SEA DRAGON (ICES code: 32S2)","SIR JAMES CLARK ROSS (ICES code: 587O, 1923-1930)","SOLANDER (call sign: VMQ9273, ICES code: 09CX)","SOUTHERN SURVEYOR (call sign: VLHJ, ICES code: 09SS, 1988-2014)","Tara (call sign: FVNM, ICES code: 35XI, 2009-)","URANIA (ICES code: 64UR)","XIANG YANG HONG 03 (call sign: BNVB, ICES code: 76X3)","\u00c1ngeles Alvari\u00f1o (call sign: EASE, ICES code: 29AJ, 2012-)","\u0410\u043a\u0430\u0434\u0435\u043c\u0438\u043a \u041c\u0441\u0442\u0438\u0441\u043b\u0430\u0432 \u041a\u0435\u043b\u0434\u044b\u0448 (ICES code: 90BP, 1981-1992)","\u041f\u0420\u041e\u0424\u0415\u0421\u0421\u041e\u0420 \u041a\u0410\u0413\u0410\u041d\u041e\u0412\u0421\u041a\u0418\u0419 (call sign: UTTW, ICES code: 90ZH, 1987-1991)","AKADEMIK TRYOSHNIKOV (call sign UBXH3 - ICES code RUB3)","Angeles Alvarino (call sign EASE - ICES code 29AJ)","Comac Enterprise","Dongfeng Race Team","MRV Alba na Mara","MRV Scotia","MS Malippo","MS \u201cMalippo\u201d","MV Maersk Launcher","MV Maersk Transporter","Mapfre","NEW HORIZON (call sign WKWB - ICES code 32NM)","ORV Alguita","Okeanos Explorer (call sign WTDH - ICES code 334A)","R.V Celtic Explorer","R.V. G. O. Sars","R.V. Minerva","R/V Aegeao","R/V Akademik Mstislav Keldysh","R/V Angeles Alvari\u00f1o","R/V Cap\u2019n Bert","R/V Celtic Voyager","R/V Filia","R/V Kiya","R/V Mediterranean Explorer","R/V Mtafiti","R/V SURAT ARASTIRMA","R/V Tara","R/V Xuelong","ROVs","RRS Discovery","RRS James Clark Ross","RV Celtic Explorer","RV IV Lluerna","RV Orion","RV Pelagia","RV Polarstern","RV Professor Kaganovskiy","RV Sir John Murray","RV Stad Amsterdam","RV XIANG YANG HONG 03","S.A. AGULHAS II (call sign ZSNO - ICES code 91AH)","SV Mir","SV Rainbow Warrior","SV Sea Dragon","Sun Hung Kai Scallywag","Team AkzoNobel","Team Brunel","Turn the Tide on Plastic","Vestas 11th Hour Racing","GEOGRAPHIC REGION > GLOBAL OCEAN","Waterbodies > Gulf of Mexico","Alaska","Atlantic Ocean","Australia","Bahamas","Barents Seas","Bay of Calvi","Beibu Gulf","Brazil","Bulgarian Black Sea","Canada","Chile","Columbia","Costa Rica","Dominican Republic","East-Siberian Sea","Eastern Mediterranean Sea","Eastern Pacific Ocean","Equatorial Guinea","France","Gabes Gulf","Gal\u00e1pagos","Global","Global Ocean","Great Barrier Reef","Greece","Guatemela","Gulf of Guayaquil","Gulf of Lion","Gulf of Oristano","Gulf of Venice","Kenya","Kuroshio Current","Laptev Sea","Levantine Sea","Manila Bay","Mexico","NW Mediterranean Sea","Narragansett Bay","New Zealand","North Atlantic Subtropical Gyre","North-West Mediterranean Sea","Northern Adriatic Sea","Northwest Pacific","Northwestern Mediterranean Sea","Pacific Ocean","Playa Grande beach: Tenerife, Canary Islands, Spain","San Francisco Bay","Saronikos Gulf","Scotland","Sea of Oman","Sri Lanka","Taiwan","United Arab Emirates","United Kingdom","United States","Western Indian Ocean","Western Mediterranean","Western North Pacific Ocean","0370R2","06NWEE","09PKB9","0CCB5U","0WBCYL","123CE1","139DEU","1RP301","226PKB","22YR0K","26430G","2DM697","2M20XB","2X9KKU","31JGEX","35F99T","37Y05A","383Y9U","3BFHT5","3JK15T","3KC69K","4252PG","4520RA","4JPDWP","4M115G","56JD45","575D5A","5XFHCF","6D80CE","6NGB2H","74EPET","77WG2K","7AB52E","83849B","897C1N","8A0WYC","8HHW34","93J4B6","96BCU7","9J3P32","9RFULE","9XJUG9","9XWYE5","A03JJG","A6C6B1","A8RCBD","B0C93N","B8LX93","BAU8LM","BFFY91","BMEKJC","C1W8UH","C75PAK","CU2GE7","D7B70T","DCK5W1","DFTHMR","DMM5WT","DTXFX2","E28YL3","EA11N3","EDE1PT","EFD6MK","EKJ0L9","ERWNCY","ETL10F","F1KAUU","FJM26N","FR44XP","G4X6P2","G5HM13","GFGLY1","GY7KLK","H1MENE","H1R14M","H34EKT","H4MBXJ","HKP7PB","J1XPR6","K2U4C5","KF4KLC","KTLDD1","KXW1J8","LA71JF","LPRRLM","LUBKCP","M5FARJ","M8NU9G","MK0DL7","N1PPYL","N37EY9","NBM4KM","NCLL0F","NCWWEH","NDFWW7","NETMK9","NMMXKB","P1282M","P6L6AF","PNUBR9","PYTFGE","RCR7LN","RJ6BCX","TGPMFR","TKM7FJ","TTMNDE","U21DKX","UGU4PM","W8JMJG","WDPK8Y","WU1NRY","X3TWUH","X54F7A","Y8EGBM","YMF0NM","YMXDHP","YPXRBR","YY6CU4"],"last_harvested_date":"2026-09-27T00:10:07.836311","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"5f4f1195-e770-4a2a-8f75-195cd98860ce","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/noaa.png","name":"National Oceanic and Atmospheric Administration, Department of Commerce","organization_type":"Federal Government","slug":"noaa"},"parent_identifier":null,"popularity":40,"publisher":"NOAA National Centers for Environmental Information","slug":"the-noaa-ncei-global-marine-microplastics-data-collection-1972-present","spatial_centroid":{"lat":-7.2,"lon":36.0},"spatial_shape":{"coordinates":[[[180.0,-72.0],[180.0,90.0],[-180.0,90.0],[-180.0,-72.0],[180.0,-72.0]]],"type":"Polygon"},"theme":["geospatial"],"title":"The NOAA NCEI Global Marine Microplastics Data Collection (1972-present)","type":"dataset"},{"_score":16.901436,"_sort":[1790467805884,16.901436,5,"0e064d33-814b-4806-9c91-2cf2b515f6d6"],"dcat":{"@type":"dcat:Dataset","accessLevel":"non-public","contactPoint":{"@type":"vcard:Contact","fn":"NOAA National Centers for Environmental Information","hasEmail":"mailto:ncei.info@noaa.gov"},"describedByType":"application/octet-stream","description":"This collection contains GIS data layers and aerial imagery for the three coastal counties of Mississippi (Hancock County, Harrison County, and Jackson County) from a project developed after Hurricane Katrina in 2005.\n\t  \nThe Katrina Impact Assessment project was created after Hurricane Katrina caused significant damage in South Mississippi in late August, 2005. The data layers and aerial imagery included in this project were first made available via ESRI's ArcIMS interactive mapping applications and then distributed on DVD media for reference and to assist with evaluations of the storm's effects on the people, the commercial entities, and the natural environment in the area.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/archive/accession/NCEI-Katrina-Impact","describedByType":"application/octet-stream","description":"Navigate directly to the URL for a descriptive web page with download links.","mediaType":"text/html","title":"NCEI Dataset Landing Page"},{"@type":"dcat:Distribution","accessURL":"https://data.noaa.gov/onestop/collections/granules/e7b832bf-48f9-4a52-ae0c-95d9a93c6e4b","describedByType":"application/octet-stream","description":"Browse data granules belonging to this collection (a granule is the smallest aggregation of data that can be independently described and retrieved).","mediaType":"text/html","title":"Browse granules"},{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/metadata/granule/geoportal/?from=0&size=10&esdsl=%7B%22query%22%3A%7B%22bool%22%3A%7B%22must%22%3A%5B%7B%22query_string%22%3A%7B%22analyze_wildcard%22%3Atrue%2C%22query%22%3A%22fileid%3ANCEI-Katrina-Impact.*%22%7D%7D%5D%7D%7D%7D#searchPanel","describedByType":"application/octet-stream","description":"Search for data granules belonging to this collection (a granule is the smallest aggregation of data that can be independently described and retrieved).","mediaType":"text/html","title":"Search for granules"},{"@type":"dcat:Distribution","accessURL":"https://forum.earthdata.nasa.gov/app.php/tag/GCMD%2BKeywords","describedByType":"application/octet-stream","description":"Global Change Master Directory (GCMD). 2025. GCMD Keywords, Version 21. Greenbelt, MD: Earth Science Data and Information System, Earth Science Projects Division, Goddard Space Flight Center (GSFC), National Aeronautics and Space Administration (NASA). URL (GCMD Keyword Forum Page): https://forum.earthdata.nasa.gov/app.php/tag/GCMD+Keywords","mediaType":"text/html","title":"GCMD Keyword Forum Page"},{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/contact","describedByType":"application/octet-stream","description":"Information for contacts at NCEI.","mediaType":"text/html","title":"NCEI Contact Information"}],"identifier":"https://data.noaa.gov/waf/NOAA/NESDIS/ncei/accessions/iso/xml/NCEI-Katrina-Impact.xml","issued":"2025-12-15T00:00:00.000+00:00","keyword":["0310717","0310719","0310720","images","LATITUDE","LONGITUDE","camera","GPS","aerial photography","derived products","GIS product","in situ","NOAA National Centers for Environmental Information","Coastal Waters of Gulf of America","Coastal Waters of Gulf of Mexico","Coastal Waters of Mississippi","Gulf of America","Gulf of Mexico","oceanography","DOC/NOAA/NESDIS/NCEI > National Centers for Environmental Information, NESDIS, NOAA, U.S. Department of Commerce","CAMERA > CAMERA","GPS RECEIVERS > GPS RECEIVERS","OCEAN > ATLANTIC OCEAN > NORTH ATLANTIC OCEAN > GULF OF AMERICA","OCEAN > ATLANTIC OCEAN > NORTH ATLANTIC OCEAN > GULF OF MEXICO","C6LLRP","H293CX","L1Y3R8"],"landingPage":"https://www.ncei.noaa.gov/contact","language":[],"license":"https://creativecommons.org/publicdomain/zero/1.0/","modified":"2026-01-06T00:00:00.000+00:00","publisher":{"@type":"org:Organization","name":"NOAA National Centers for Environmental Information"},"rights":"otherRestrictions","spatial":"-88.377025,30.169617,-89.690048,30.73605","temporal":"1983-01-01T00:00:00+00:00/2005-11-18T00:00:00+00:00","theme":["geospatial"],"title":"GIS data layers and aerial imagery from the Hurricane Katrina Impact Assessment in 2005 for Hancock County, Harrison County, and Jackson County, Mississippi"},"description":"This collection contains GIS data layers and aerial imagery for the three coastal counties of Mississippi (Hancock County, Harrison County, and Jackson County) from a project developed after Hurricane Katrina in 2005.\n\t  \nThe Katrina Impact Assessment project was created after Hurricane Katrina caused significant damage in South Mississippi in late August, 2005. The data layers and aerial imagery included in this project were first made available via ESRI's ArcIMS interactive mapping applications and then distributed on DVD media for reference and to assist with evaluations of the storm's effects on the people, the commercial entities, and the natural environment in the area.","distribution_titles":["NCEI Dataset Landing Page","Browse granules","Search for granules","GCMD Keyword Forum Page","NCEI Contact Information"],"harvest_record":"https://catalog.data.gov/harvest_record/4bb604ba-5a20-4b1d-9e20-059e6b47087b","harvest_record_raw":"https://catalog.data.gov/harvest_record/4bb604ba-5a20-4b1d-9e20-059e6b47087b/raw","harvest_record_transformed":"https://catalog.data.gov/harvest_record/4bb604ba-5a20-4b1d-9e20-059e6b47087b/transformed","has_download":false,"has_spatial":true,"identifier":"https://data.noaa.gov/waf/NOAA/NESDIS/ncei/accessions/iso/xml/NCEI-Katrina-Impact.xml","keyword":["0310717","0310719","0310720","images","LATITUDE","LONGITUDE","camera","GPS","aerial photography","derived products","GIS product","in situ","NOAA National Centers for Environmental Information","Coastal Waters of Gulf of America","Coastal Waters of Gulf of Mexico","Coastal Waters of Mississippi","Gulf of America","Gulf of Mexico","oceanography","DOC/NOAA/NESDIS/NCEI > National Centers for Environmental Information, NESDIS, NOAA, U.S. Department of Commerce","CAMERA > CAMERA","GPS RECEIVERS > GPS RECEIVERS","OCEAN > ATLANTIC OCEAN > NORTH ATLANTIC OCEAN > GULF OF AMERICA","OCEAN > ATLANTIC OCEAN > NORTH ATLANTIC OCEAN > GULF OF MEXICO","C6LLRP","H293CX","L1Y3R8"],"last_harvested_date":"2026-09-27T00:10:05.884630","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"5f4f1195-e770-4a2a-8f75-195cd98860ce","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/noaa.png","name":"National Oceanic and Atmospheric Administration, Department of Commerce","organization_type":"Federal Government","slug":"noaa"},"parent_identifier":null,"popularity":5,"publisher":"NOAA National Centers for Environmental Information","slug":"gis-data-layers-and-aerial-imagery-from-the-hurricane-katrina-impact-assessment-in-2005-fo","spatial_centroid":{"lat":30.3961902,"lon":-88.9022342},"spatial_shape":{"coordinates":[[[-88.377025,30.169617],[-88.377025,30.73605],[-89.690048,30.73605],[-89.690048,30.169617],[-88.377025,30.169617]]],"type":"Polygon"},"theme":["geospatial"],"title":"GIS data layers and aerial imagery from the Hurricane Katrina Impact Assessment in 2005 for Hancock County, Harrison County, and Jackson County, Mississippi","type":"dataset"},{"_score":1.5419197,"_sort":[1790467786460,1.5419197,13,"a31eacee-17c9-4ca2-8ff6-1d81941d84bf"],"dcat":{"@type":"dcat:Dataset","accessLevel":"non-public","contactPoint":{"@type":"vcard:Contact","fn":"NOAA National Centers for Environmental Information","hasEmail":"mailto:ncei.info@noaa.gov"},"describedByType":"application/octet-stream","description":"This collection contains comprehensive datasets and reports collected in support of the Mamala Bay Study during 1993-1995. Physical, chemical, biological, and geological datasets and reports are included.\n\nReports included in this collection include the following:\n\nMB-1 Mamala Bay Study Management Mamala Bay Study Commission: R. R. Colwell, G. T. Orlob, and J. R. Schubel, Commissioners.\nMB-2 Mamala Bay Database: W. J. Kimmerer, Garcia and Associates (formerly with BioSystems, Inc.), Tiburon, CA.\nMB-3 Pollutant Source Identification: M. Stevenson, and J. M. O'Connor, Kinnetic Laboratories, Inc., Lahaina, HI.\nMB-4 Plume Modeling: P. J. W. Roberts, Georgia Institute of Technology, Atlanta, GA.\nMB-5 Modeling Transport and Fate of Pathogenic Organisms in Mamala Bay: A. F. Blumberg and J. P. Connolly, HydroQual, Inc., Mahwah, NJ.\nMB-6 Ocean Current Measurements: P. Hamilton, J. Singer and E. Waddell, Science Application International Corporation, Raleigh, NC.\nMB-7 Characterization of the Microbiological Quality of Water in Mamala Bay: R. S. Fujioka, University of Hawaii, Honolulu, HI.\nMB-7 Overall Impact of Sand Island Outfall on the Incidence of Pathogens in Mamala Bay: C. P. Gerba and I. L. Pepper, University of Arizona, Tucson, AZ.\nMB-7 Risk of Swimming-Acquired Illnesses in Mamala Bay: C. P. Gerba, University of Arizona, Tucson, AZ; C. N. Haas, Drexel University, Philadelphia, PA; J. B. Rose, University of South Florida, St. Petersburg, FL.\nMB-7 Molecular Investigation of the Effects of Pollution on Pathogenic and Indigenous Bacteria in Mamala Bay: R. T. Hill, University of Maryland, Baltimore, MD.\nMB-7 Molecular Detection of Staphylococcus aureus in Waters of Mamala Bay, Hawaii: R. T. Hill, University of Maryland, Baltimore, MD.\nMB-7 Microbiological Aspects of Point and Non-Point Source Pollution in Mamala Bay: M. R. Landry, University of Hawaii, Honolulu, Hawaii; F. C. Dobbs, Old Dominion University, Norfolk, VA.\nMB-7 Coliphage and Indigenous Phage in Mamala Bay: J. H. Paul and J. B. Rose, University of South Florida, St. Petersburg, FL.\nMB-7 Viability of cryptosporidium parvum in Marine Waters: J. B. Rose, University of South Florida, St. Petersburg, FL.\nMB-9 Definition of Indicator Species for Pollution Monitoring in Mamala Bay, Oahu, Hawaii: J. H. Bailey-Brock, University of Hawaii, Honolulu, HI.\nMB-9 Impact of Point and Non-Point Source Pollution on Coral Reef Ecosystems in Mamala Bay: R. W. Grigg, University of Hawaii, Honolulu, HI.\nMB-9 Shallow Marine Community Response to Point and Non-Point Sources of Pollution in Mamala Bay, Oahu, Part A: Fish and Coral Communities: E. A. Kay, J. H. Bailey-Brock, R. E. Brock, University of Hawaii, Honolulu, HI.\nMB-9 Shallow Marine Community Response to Point and Non-Point Sources of Pollution in Mamala Bay, Oahu, Part B: Micromolluscan Assemblages and Algal Biomass: E. A. Kay, J. H. Bailey-Brock, R. E. Brock, University of Hawaii, Honolulu, HI.\nMB-9 Effects of Sewage Discharges and Stream Runoff on Phytoplankton Communities and Water Quality in Mamala Bay: E. A. Laws and D. Ziemann, University of Hawaii, Honolulu, HI.\nMB-9 Temporal Variability in Macrobenthic Community Structure and the Effect of Freshwater Runoff: S. A. McCarthy, E. A. Kay and J. H. Bailey-Brock, University of Hawaii, Honolulu, HI.\nMB-9 Recruitment Patterns of Marine Benthic Invertebrates in Mamala Bay: A Process-Oriented Measure of Ecosystem Response to Pollution: C. R. Smith and P. E. Parnell, University of Hawaii, Honolulu, HI.\nMB-10 Part I: Management Alternatives and Management Measures for Waste Discharges to the Mamala Bay Ecosystem: K. Courtney, PRC Environmental Management, Inc., Honolulu, HI; J. M. O'Connor, Kinnetic Laboratories, Inc., Santa Cruz, CA.\nMB-10 Part II: Identification of Stressors of Concern in the Mamala Bay Ecosystem: J. M. O'Connor, Kinnetic Laboratories, Inc., Santa Cruz, CA.\nMB-10 Part III: Effects of Effluent from the Barbers Point and Sand Island Outfalls on the Mamala Bay Ecosystem: W. J. Kimmerer, Romberg Tiburon Center, Tiburon, CA; J. M. O'Connor, Kinnetic Laboratories, Inc., Santa Cruz, CA.\nMB-10 Part IV: Proposed Monitoring Plan to Assess the Efficacy of Waste Treatment Alternatives Applied in the Mamala Bay Watershed: J. M. O'Connor, Kinnetic Laboratories, Inc., Santa Cruz, CA.\nMB-10 Infectious Disease Public Health Risk Assessment: A. W. Oliveri and R. C. Cooper, Eisenberg, Oliveri, and Associates, Oakland, CA.\nMB-11 Water Quality Management in Mamala Bay: Mamala Bay Study Commissioners and project PIs.\nMB-11A Wastewater Management Strategies in an Integrated Coastal Management Plan for Mamala Bay: D. R. F. Harleman, Consulting Engineers, Cambridge, MA.\nMB-SP2 Plume Dynamics and Dispersion in Mamala Bay, Hawaii: B. H. Jones and T. D. Dickey, University of Southern California, Los Angeles, CA.","distribution":[{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/archive/accession/Mamala_Bay_Study_1993-1995","describedByType":"application/octet-stream","description":"Navigate directly to the URL for a descriptive web page with download links.","mediaType":"text/html","title":"NCEI Dataset Landing Page"},{"@type":"dcat:Distribution","accessURL":"https://data.noaa.gov/onestop/collections/granules/7c226222-6e09-4e8c-83a1-d4a172174864","describedByType":"application/octet-stream","description":"Browse data granules belonging to this collection (a granule is the smallest aggregation of data that can be independently described and retrieved).","mediaType":"text/html","title":"Browse granules"},{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/metadata/granule/geoportal/?from=0&size=10&esdsl=%7B%22query%22%3A%7B%22bool%22%3A%7B%22must%22%3A%5B%7B%22query_string%22%3A%7B%22analyze_wildcard%22%3Atrue%2C%22query%22%3A%22fileid%3AMamala_Bay_Study_1993-1995.*%22%7D%7D%5D%7D%7D%7D#searchPanel","describedByType":"application/octet-stream","description":"Search for data granules belonging to this collection (a granule is the smallest aggregation of data that can be independently described and retrieved).","mediaType":"text/html","title":"Search for granules"},{"@type":"dcat:Distribution","accessURL":"https://www.wrrc.hawaii.edu/publications/project-reports/","describedByType":"application/octet-stream","description":"UH Water Resources Research Center Project Reports","mediaType":"text/html","title":"https://www.wrrc.hawaii.edu/publications/project-reports/"},{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/archive/accession/0189890","describedByType":"application/octet-stream","description":"documentation","mediaType":"text/html","title":"https://www.ncei.noaa.gov/archive/accession/0189890"},{"@type":"dcat:Distribution","accessURL":"https://forum.earthdata.nasa.gov/app.php/tag/GCMD%2BKeywords","describedByType":"application/octet-stream","description":"Global Change Master Directory (GCMD). 2025. GCMD Keywords, Version 21. Greenbelt, MD: Earth Science Data and Information System, Earth Science Projects Division, Goddard Space Flight Center (GSFC), National Aeronautics and Space Administration (NASA). URL (GCMD Keyword Forum Page): https://forum.earthdata.nasa.gov/app.php/tag/GCMD+Keywords","mediaType":"text/html","title":"GCMD Keyword Forum Page"},{"@type":"dcat:Distribution","accessURL":"https://www.ncei.noaa.gov/contact","describedByType":"application/octet-stream","description":"Information for contacts at NCEI.","mediaType":"text/html","title":"NCEI Contact Information"}],"identifier":"https://data.noaa.gov/waf/NOAA/NESDIS/ncei/accessions/iso/xml/Mamala_Bay_Study_1993-1995.xml","issued":"1996-01-01T00:00:00.000+00:00","keyword":["0000030","0000624","0001172","0001188","9600024","9600041","9800089","9800147","9800149","9800151","9800152","9800169","9800170","9800174","9900064","9900112","9900120","9900121","9900151","AIR TEMPERATURE - DRY BULB","AIR TEMPERATURE - WET BULB","AMMONIA (NH3)","AMMONIUM (NH4)","ANIMALS - INDIVIDUAL","ANIMALS - INDIVIDUAL - COUNTS","bacteria","BACTERIA - BACTERIAL DENSITY","BAROMETRIC PRESSURE","BEACH TAR - WATERLINE TO SAMPLE DISTANCE","BENTHIC COMMUNITIES","BENTHIC SPECIES","BENTHIC SPECIES - TAXA COUNTS","BENTHIC SPECIES - TAXA IDENTITIES","BENTHIC SPECIES - TAXA WET WEIGHTS","biological data","BIOMASS","CAS (CHEMICAL ABSTRACTS SERVICE) PARAMETER CODES","CHEMISTRY - SEDIMENT","CHLOROPHYLL A","CHLOROPHYLL B","CHLOROPHYLL C","cloud amount/frequency","cloud type","CONDUCTIVITY","CORAL","CORE - BOTTOM","CRUSTACEANS","CURRENT METER - EAST-WEST COMPONENT (U)","CURRENT METER - NORTH-SOUTH COMPONENT (V)","CURRENT METER - SPEED","CURRENT SPEED","CURRENT SPEED - UP/DOWN COMPONENT (W)","DEPTH - OBSERVATION","DEPTH - SENSOR","DISSOLVED ORGANIC CARBON","DISSOLVED ORGANIC MATTER","DISSOLVED OXYGEN","EFFLUENT - DISCHARGE DESCRIPTION","EFFLUENT - DISCHARGE IDENTIFIER","EFFLUENT - DISCHARGE POINT","EFFLUENT - DISCHARGE PRIMARY INDUSTRY","EFFLUENT - DISCHARGE QUANTITY","EFFLUENT - ZONE OF INITIAL DILUTION","FISH SPECIES","FLUORESCENCE","HABITAT - BENTHIC","HABITAT - SEDIMENT SIZE","HYDROCARBONS - TOTAL RESOLVED","HYDROSTATIC PRESSURE","INVERTEBRATE SPECIES","LIGHT ATTENUATION","LIGHT TRANSMISSION","MACROFAUNA","MICROBIOLOGY","MOLLUSKS","NITRATE","nitrate + nitrite content (concentration)","NITRITE","NITROGEN","NITROGEN - PARTICULATE","NUTRIENTS","Ocean pollution and marine debris","OPTICAL PROPERTIES","OXYGEN","PARTICULATE ORGANIC CARBON","PARTICULATE ORGANIC NITROGEN (PON)","pH","PHAEOPHYTIN","PHAEOPIGMENTS","phosphate","PHOSPHATE - TOTAL FILTER PASSING","PHOTOSYNTHETIC ACTIVE RADIATION (PAR)","PLANKTON","POLYCHLORINATED BIPHENYLS","PRIMARY PRODUCTIVITY","PRIMARY PRODUCTIVITY - PHYTOPLANKTON","SALINITY","SEA STATE","Secchi depth","SEDIMENT - GRAIN SIZE","SEDIMENT PROPERTIES","SEDIMENTS","SEDIMENTS - DRY WEIGHT","SEDIMENTS - PARTICLE SIZE FRACTIONS","SIGMA-T","silicate","SOUND VELOCITY","SPECIES IDENTIFICATION","SPECIES IDENTIFICATION - COUNT","SPECIES IDENTIFICATION - LIFE STAGE","SPECIES IDENTIFICATION - SEX","SPECIES IDENTIFICATION - WET WEIGHT","suspended solids","TOTAL PHOSPHATE","TOTAL PHOSPHORUS","TOXIN","TRANSMISSIVITY","turbidity","UPWELLING IRRADIANCE","VERTEBRATES","VISIBILITY","WATER DENSITY","water depth","WATER TEMPERATURE","WEATHER","WIND DIRECTION","WIND SPEED","ZOOPLANKTON ABUNDANCE","ZOOPLANKTON BIOMASS","ZOOPLANKTON IDENTITIES","ZOOPLANKTON SPECIES IDENTITIES","ZOOPLANKTON SPECIES NUMBER PER SAMPLE","ADCP","bathythermograph - BT","bottle","conductivity sensor","corer","CTD","current meter","fluorometer","laboratory analysis","mass spectrometer","meteorological sensor","mooring","multi-parameter water quality sensor","net - zooplankton net","pH sensor","photograph","pressure gauge","pump sampler","salinometer","Secchi disk","sediment sampler - corer","sediment sampler - grab","sediment sieve","swimmer/diver","thermistor","thermograph","thermometer","tide gauge","transmissometer","trap - sediment","visual analysis","visual observation","benthic","biological","chemical","continuous","current measurements","laboratory analyses","optical","physical","profile","sediment analysis","survey","survey - biological","survey - coral reef","survey - swimmer/diver","time series","FIXED PLATFORM OF UNITED STATES","RV Nathaniel B. 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cover","bacteria","bioerosion of P.Lobata","calcification of P.Lobata","coastal data","coral ecosystem","moored ADCP","salinity","sedimentation","species diversity","temperature","water quality","ADCP > Acoustic Doppler Current Profiler","BATHYTHERMOGRAPHS","CONDUCTIVITY METERS > CONDUCTIVITY METERS","CTD > Conductivity, Temperature, Depth","CURRENT METERS","FLUOROMETERS > FLUOROMETERS","GRAB SAMPLERS","GRANULOMETRIC SIEVES","MASS SPECTROMETERS > MASS SPECTROMETERS","PH METERS > PH METERS","PLANKTON NETS","PRESSURE GAUGES","SALINOMETERS","SECCHI DISKS > SECCHI DISKS","SEDIMENT CORERS > SEDIMENT CORERS","THERMISTORS > THERMISTORS","THERMOMETERS > THERMOMETERS","TIDE GAUGES > TIDE GAUGES","TRANSMISSOMETERS","TRAPS > TRAPS","VISUAL OBSERVATIONS > VISUAL OBSERVATIONS","FIXED OBSERVATION STATIONS > FIXED OBSERVATION STATIONS","Ships","NATHANIEL B. PALMER (call sign: WPB3210, ICES code: 3206, 1992-)","SWIMMER/DIVER (ICES code: 33DV)","OCEAN > PACIFIC OCEAN > CENTRAL PACIFIC OCEAN > HAWAIIAN ISLANDS","OCEAN > PACIFIC OCEAN > NORTH PACIFIC OCEAN","Airport Reef Runway","Ala Wai Canal","C & H SUGAR CO. Aiea Refinery","CHEVRON USA HONOLULU MAIN PLANT","CHEVRON USA HONOLULU TERMINAL","CHEVRON USA INC. (Barbers Point)","CHEVRON USA KAPALAMAMA TERMINAL","Central Pacific","DEMONSTRATION DESALINIZATION PLANT","Diamond Head","Ewa Beach","HAWAII FUELING FACILITIES","HAWAIIAN ELECTRIC CO. Honolulu Gen. Station","HAWAIIAN ELECTRIC CO. Waiau Gen. Station (Pearl Harbor)","HONOLULU SHIP YARD","HONOULIULI WWTP","Hawaii","Honolulu","Honouliuli Sewage Outfall, Honolulu, Hawaii","Mamala Bay","Mamala Bay, Oahu, Hawaii","Naval Submarine Base B","Naval Submarine Base D","Naval Submarine Base E","Naval Submarine Base G","Naval Submarine Base H","North Pacific","Oahu","Oahu, Hawaii","PACIFIC RESOURCES TERMINAL","PEARL HARBOR NAVAL SHIPYARD","Pacific Ocean","SAND ISLAND WWTP","SHELL OIL HONOLULU PLANT","Sand Island Outfall, Mamala Bay, Oahu","Sand Island Sewage Outfall","U.S. NAVY, Fort Kamehameha","WAIKIKI AQUARIUM","Waikiki","YACHT HARBOR TOWERS","coastal ocean"],"landingPage":"https://www.ncei.noaa.gov/contact","language":[],"license":"https://creativecommons.org/publicdomain/zero/1.0/","modified":"2026-05-13T00:00:00.000+00:00","publisher":{"@type":"org:Organization","name":"NOAA National Centers for Environmental Information"},"references":["https://www.wrrc.hawaii.edu/publications/project-reports/","https://www.ncei.noaa.gov/archive/accession/0189890"],"rights":"otherRestrictions","spatial":"157.5,21.0,158.0,21.5","temporal":"1975-01-01T00:00:00+00:00/1998-08-31T00:00:00+00:00","theme":["geospatial"],"title":"Comprehensive Dataset and Reports of the Mamala Bay Study during 1993-1995 on Oahu, Hawaii"},"description":"This collection contains comprehensive datasets and reports collected in support of the Mamala Bay Study during 1993-1995. Physical, chemical, biological, and geological datasets and reports are included.\n\nReports included in this collection include the following:\n\nMB-1 Mamala Bay Study Management Mamala Bay Study Commission: R. R. Colwell, G. T. Orlob, and J. R. Schubel, Commissioners.\nMB-2 Mamala Bay Database: W. J. Kimmerer, Garcia and Associates (formerly with BioSystems, Inc.), Tiburon, CA.\nMB-3 Pollutant Source Identification: M. Stevenson, and J. M. O'Connor, Kinnetic Laboratories, Inc., Lahaina, HI.\nMB-4 Plume Modeling: P. J. W. Roberts, Georgia Institute of Technology, Atlanta, GA.\nMB-5 Modeling Transport and Fate of Pathogenic Organisms in Mamala Bay: A. F. Blumberg and J. P. Connolly, HydroQual, Inc., Mahwah, NJ.\nMB-6 Ocean Current Measurements: P. Hamilton, J. Singer and E. Waddell, Science Application International Corporation, Raleigh, NC.\nMB-7 Characterization of the Microbiological Quality of Water in Mamala Bay: R. S. Fujioka, University of Hawaii, Honolulu, HI.\nMB-7 Overall Impact of Sand Island Outfall on the Incidence of Pathogens in Mamala Bay: C. P. Gerba and I. L. Pepper, University of Arizona, Tucson, AZ.\nMB-7 Risk of Swimming-Acquired Illnesses in Mamala Bay: C. P. Gerba, University of Arizona, Tucson, AZ; C. N. Haas, Drexel University, Philadelphia, PA; J. B. Rose, University of South Florida, St. Petersburg, FL.\nMB-7 Molecular Investigation of the Effects of Pollution on Pathogenic and Indigenous Bacteria in Mamala Bay: R. T. Hill, University of Maryland, Baltimore, MD.\nMB-7 Molecular Detection of Staphylococcus aureus in Waters of Mamala Bay, Hawaii: R. T. Hill, University of Maryland, Baltimore, MD.\nMB-7 Microbiological Aspects of Point and Non-Point Source Pollution in Mamala Bay: M. R. Landry, University of Hawaii, Honolulu, Hawaii; F. C. Dobbs, Old Dominion University, Norfolk, VA.\nMB-7 Coliphage and Indigenous Phage in Mamala Bay: J. H. Paul and J. B. Rose, University of South Florida, St. Petersburg, FL.\nMB-7 Viability of cryptosporidium parvum in Marine Waters: J. B. Rose, University of South Florida, St. Petersburg, FL.\nMB-9 Definition of Indicator Species for Pollution Monitoring in Mamala Bay, Oahu, Hawaii: J. H. Bailey-Brock, University of Hawaii, Honolulu, HI.\nMB-9 Impact of Point and Non-Point Source Pollution on Coral Reef Ecosystems in Mamala Bay: R. W. Grigg, University of Hawaii, Honolulu, HI.\nMB-9 Shallow Marine Community Response to Point and Non-Point Sources of Pollution in Mamala Bay, Oahu, Part A: Fish and Coral Communities: E. A. Kay, J. H. Bailey-Brock, R. E. Brock, University of Hawaii, Honolulu, HI.\nMB-9 Shallow Marine Community Response to Point and Non-Point Sources of Pollution in Mamala Bay, Oahu, Part B: Micromolluscan Assemblages and Algal Biomass: E. A. Kay, J. H. Bailey-Brock, R. E. Brock, University of Hawaii, Honolulu, HI.\nMB-9 Effects of Sewage Discharges and Stream Runoff on Phytoplankton Communities and Water Quality in Mamala Bay: E. A. Laws and D. Ziemann, University of Hawaii, Honolulu, HI.\nMB-9 Temporal Variability in Macrobenthic Community Structure and the Effect of Freshwater Runoff: S. A. McCarthy, E. A. Kay and J. H. Bailey-Brock, University of Hawaii, Honolulu, HI.\nMB-9 Recruitment Patterns of Marine Benthic Invertebrates in Mamala Bay: A Process-Oriented Measure of Ecosystem Response to Pollution: C. R. Smith and P. E. Parnell, University of Hawaii, Honolulu, HI.\nMB-10 Part I: Management Alternatives and Management Measures for Waste Discharges to the Mamala Bay Ecosystem: K. Courtney, PRC Environmental Management, Inc., Honolulu, HI; J. M. O'Connor, Kinnetic Laboratories, Inc., Santa Cruz, CA.\nMB-10 Part II: Identification of Stressors of Concern in the Mamala Bay Ecosystem: J. M. O'Connor, Kinnetic Laboratories, Inc., Santa Cruz, CA.\nMB-10 Part III: Effects of Effluent from the Barbers Point and Sand Island Outfalls on the Mamala Bay Ecosystem: W. J. Kimmerer, Romberg Tiburon Center, Tiburon, CA; J. M. O'Connor, Kinnetic Laboratories, Inc., Santa Cruz, CA.\nMB-10 Part IV: Proposed Monitoring Plan to Assess the Efficacy of Waste Treatment Alternatives Applied in the Mamala Bay Watershed: J. M. O'Connor, Kinnetic Laboratories, Inc., Santa Cruz, CA.\nMB-10 Infectious Disease Public Health Risk Assessment: A. W. Oliveri and R. C. Cooper, Eisenberg, Oliveri, and Associates, Oakland, CA.\nMB-11 Water Quality Management in Mamala Bay: Mamala Bay Study Commissioners and project PIs.\nMB-11A Wastewater Management Strategies in an Integrated Coastal Management Plan for Mamala Bay: D. R. F. Harleman, Consulting Engineers, Cambridge, MA.\nMB-SP2 Plume Dynamics and Dispersion in Mamala Bay, Hawaii: B. H. Jones and T. D. 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The inventory was compiled by the Mesophotic and Deep Benthic Communities (MDBC): Mapping Ground-truthing, and Predictive Habitat Modeling Project. This project is one of many selected by the Open Ocean Trustee Implementation Group to restore natural resources injured by the 2010 Deepwater Horizon oil spill in the Gulf of Mexico. Data collected from 1980 to 2021 were sourced from federal and state agencies, as well as from academia and industry. Each dataset is represented in the inventory as a spatial footprint with corresponding quantitative and qualitative attributes. The seafloor mapping data are primarily remote sensing observations used to survey and derive depth, shape, and texture of the seafloor and characterize the geomorphological forms, substrates, and biota used to define MDBC habitats. Ground-truthing data are in-situ observations that provide visual and analytical characterization of information documenting the abundance and distribution of MDBC, substrate, and geomorphology. Predictive habitat models analyze habitat-environment or species-environment relationships from seafloor mapping data, in situ observations, and environmental data to predict MDBC habitat. The spatial extent of the dataset is as follows, except for predictive habitat models which have a more global extent.","distribution_titles":["NCEI Dataset Landing Page","Browse granules","Search for granules","Open Ocean Restoration Area","NOAA Gulf Spill Restoration","https://coastalscience.noaa.gov/project/scientific-support-for-mesophotic-and-deep-benthic-community-restoration-in-the-gulf-of-mexico/","GCMD Keyword Forum Page","NCEI Contact Information","NOAA National Centers for Coastal Ocean Science (NCCOS) website"],"harvest_record":"https://catalog.data.gov/harvest_record/1adda861-4bbd-4c87-9a81-0c25b946d319","harvest_record_raw":"https://catalog.data.gov/harvest_record/1adda861-4bbd-4c87-9a81-0c25b946d319/raw","harvest_record_transformed":"https://catalog.data.gov/harvest_record/1adda861-4bbd-4c87-9a81-0c25b946d319/transformed","has_download":false,"has_spatial":true,"identifier":"https://data.noaa.gov/waf/NOAA/NESDIS/ncei/accessions/iso/xml/MDBC-MGM-Inventory.xml","keyword":["0268765","0295552","BATHYMETRY","CORAL","HABITAT - BENTHIC","SEDIMENTS","multibeam sonar","sediment sampler - corer","sediment sampler - grab","seismic reflection profiler","sonar","in situ","model output","NOAA National Centers for Coastal Ocean Science","NOAA National Centers for Coastal Ocean Science","Deepwater Horizon oil spill event (DWH)","Mesophotic and Deep Benthic Communities (MDBC)","Natural Resources Damage Assessment Process (NRDA Process)","World-Wide Distribution","oceanography","DOC/NOAA/NOS/NCCOS > National Centers for Coastal Ocean Science, National Ocean Service, NOAA, U.S. Department of Commerce","MDBC > Mesophotic and Deep Benthic Communities","Bureau of Ocean Energy Management (BOEM)","Deepwater Horizon (DWH)","Mesophotic and Deep Benthic Communities (MDBC)","NOAA National Centers for Environmental Information (NCEI)","NOAA National Marine Fisheries Service (NMFS)","NOAA National Ocean Service (NOS) National Centers for Coastal Ocean Science (NCCOS)","NOS Office of National Marine Sanctuaries (OCMS)","Natural Resource Damage Assessment (NRDA)","Open Ocean Trustee Implementation Group (OOTIG)","U.S. Geological Survey (USGS)","EARTH SCIENCE > BIOSPHERE > ECOSYSTEMS > MARINE ECOSYSTEMS > BENTHIC","EARTH SCIENCE > OCEANS > BATHYMETRY/SEAFLOOR TOPOGRAPHY > BATHYMETRY","EARTH SCIENCE > OCEANS > MARINE SEDIMENTS","EARTH SCIENCE > SOLID EARTH > GEOMORPHIC LANDFORMS/PROCESSES > COASTAL LANDFORMS > CORAL REEFS","Marine Spatial Ecology > Ecological and Biogeographic Assessments","Marine Spatial Ecology > Habitat Mapping","Marine Spatial Ecology > Regional Ecosystem Science","Derived Data Product","Geospatial","Model","Acoustic Backscatter","Annotations","Observations","Predictive Habitat Model Predictions","Seafloor Bathymetry","GRAB SAMPLERS","MBES > Multibeam Mapping System","SEDIMENT CORERS > SEDIMENT CORERS","SEISMIC REFLECTION PROFILERS","SONAR > Sound Navigation and Ranging","Biological Sampler","Geological Sampler","Laser-line Scanner","Multibeam Sonar","Multimedia devices","Phase Differential Bathymetric Sonar","Sediment Sampler","Seismic profiler","Side-scan Sonar","Sub-bottom Profiler","GEOGRAPHIC REGION > GLOBAL OCEAN","U.S. States and Territories > Alabama","U.S. States and Territories > Florida","U.S. States and Territories > Louisiana","U.S. States and Territories > Mississippi","U.S. States and Territories > Texas","Waterbodies > Atlantic Ocean","Waterbodies > Gulf of Mexico","Atlantic Ocean","9UA6GG","E1H7J8"],"last_harvested_date":"2026-09-27T00:09:33.871122","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"5f4f1195-e770-4a2a-8f75-195cd98860ce","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/noaa.png","name":"National Oceanic and Atmospheric Administration, Department of Commerce","organization_type":"Federal Government","slug":"noaa"},"parent_identifier":null,"popularity":4,"publisher":"NOAA National Centers for Environmental Information","slug":"comprehensive-inventory-of-seafloor-mapping-ground-truthing-and-predictive-habitat-modelin","spatial_centroid":{"lat":-18.0,"lon":36.0},"spatial_shape":{"coordinates":[[[180.0,-90.0],[180.0,90.0],[-180.0,90.0],[-180.0,-90.0],[180.0,-90.0]]],"type":"Polygon"},"theme":["geospatial"],"title":"Comprehensive inventory of seafloor mapping, ground-truthing, and predictive habitat modeling datasets to support Deepwater Horizon mesophotic and deep benthic community restoration","type":"dataset"},{"_score":0.6049967,"_sort":[1790467771500,0.6049967,1,"c63b5464-0dd1-42c7-b34b-d10504b83127"],"dcat":{"@type":"dcat:Dataset","accessLevel":"non-public","contactPoint":{"@type":"vcard:Contact","fn":"NOAA National Centers for Environmental Information","hasEmail":"mailto:ncei.info@noaa.gov"},"describedByType":"application/octet-stream","description":"CTD data were taken during surveys of the Louisiana continental shelf during yearly Shelfwide Hypoxia cruises. Hydrographic data were obtained using CTD. 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GCMD Keywords, Version 21. Greenbelt, MD: Earth Science Data and Information System, Earth Science Projects Division, Goddard Space Flight Center (GSFC), National Aeronautics and Space Administration (NASA). 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sounder","flow injection analyzer","fluorometer","GPS","laboratory analysis","multi-parameter water quality sensor","nutrient autoanalyzer","oxygen sensor","PAR Sensor","pH sensor","pressure sensor","refractometer","salinometer","Secchi disk","sediment sampler - corer","spectrophotometer","temperature sensor","thermosalinograph","titrator","transmissometer","trap - plankton","biological","chemical","in situ","laboratory analyses","physical","plankton","profile","sediment analysis","surface measurements","survey","water chemistry","GYRE","LONGHORN","NOAA Ship Chapman","NOAA Ship Malcolm Baldrige","NOAA Ship Researcher","R/V Acadiana","R/V Pelican","Tommy Munro","Florida Institute of Technology","Louisiana State University","Louisiana Universities Marine Consortium","NOAA Atlantic Oceanographic and Meteorological Laboratory","NOAA Great Lakes Environmental Research Laboratory","Texas A&M University","The University of Southern Mississippi","The University of Texas at Austin","University of Maryland, College Park","University of Miami Rosenstiel School of Marine and Atmospheric Science","University of Michigan","University of Minnesota Twin Cities","Louisiana Universities Marine Consortium","Gulf of Mexico Ecosystems and Hypoxia Assessment (NGOMEX)","Hypoxia Studies in the Northern Gulf of Mexico","NUTRIENT ENHANCED COASTAL OCEAN PRODUCTIVITY (NECOP)","Coastal Waters of Gulf of America","Coastal Waters of Gulf of Mexico","Coastal Waters of Louisiana","Coastal Waters of Texas","Gulf of Mexico","Mississippi River","North Atlantic Ocean","oceanography","DOC/NOAA/NESDIS/NODC > National Oceanographic Data Center, NESDIS, NOAA, U.S. Department of Commerce","DOC/NOAA/OAR/AOML > Atlantic Oceanographic and Meteorological Laboratory, OAR, NOAA, U.S. Department of Commerce","DOC/NOAA/OAR/GLERL > Great Lakes Environmental Research Laboratory, OAR, NOAA, U.S. Department of Commerce","U-MIAMI/RSMAS > Rosenstiel School of Marine and Atmospheric Science, University of Miami","Hypoxia National Office Technical Assistance, Observation and Monitoring, and Coordination Support Activities, Mississippi State University, NA16OAR432019","Hypoxia National Office Technical Assistance, Observation and Monitoring, and Coordination Support Activities, Mississippi State University, NA16OAR4320199","DISSOLVED OXYGEN","Inorganic suspended particulate matter","Mean Fo/Fa","SONAR ALTIMETER","SURFACE PHOTOSYNTHETIC ACTIVE RADIATION (PAR)","Time","Total Suspended Sediments","organic suspended particulate material","pH mV","EARTH SCIENCE > BIOLOGICAL CLASSIFICATION","EARTH SCIENCE > BIOLOGICAL CLASSIFICATION > PROTISTS > PLANKTON > PHYTOPLANKTON","EARTH SCIENCE > BIOSPHERE > ECOLOGICAL DYNAMICS > ECOSYSTEM FUNCTIONS > BIOGEOCHEMICAL CYCLES","EARTH SCIENCE > BIOSPHERE > ECOLOGICAL DYNAMICS > ECOSYSTEM FUNCTIONS > NUTRIENT CYCLING","EARTH SCIENCE > BIOSPHERE > ECOLOGICAL DYNAMICS > ECOSYSTEM FUNCTIONS > OXYGEN DEMAND","EARTH SCIENCE > BIOSPHERE > ECOLOGICAL DYNAMICS > ECOSYSTEM FUNCTIONS > PRIMARY PRODUCTION","EARTH SCIENCE > BIOSPHERE > ECOSYSTEMS > AQUATIC ECOSYSTEMS > PLANKTON > ZOOPLANKTON","EARTH SCIENCE > CLIMATE INDICATORS > ATMOSPHERIC/OCEAN INDICATORS > SURFACE SALINITY","EARTH SCIENCE > HUMAN DIMENSIONS > HABITAT CONVERSION/FRAGMENTATION > EUTROPHICATION","EARTH SCIENCE > OCEANS > BATHYMETRY/SEAFLOOR TOPOGRAPHY > WATER DEPTH","EARTH SCIENCE > OCEANS > MARINE SEDIMENTS","EARTH SCIENCE > OCEANS > OCEAN CHEMISTRY","EARTH SCIENCE > OCEANS > OCEAN CHEMISTRY > AMMONIA","EARTH SCIENCE > OCEANS > OCEAN CHEMISTRY > CARBON","EARTH SCIENCE > OCEANS > OCEAN CHEMISTRY > CARBON DIOXIDE","EARTH SCIENCE > OCEANS > OCEAN CHEMISTRY > CHLOROPHYLL","EARTH SCIENCE > OCEANS > OCEAN CHEMISTRY > HYPOXIA","EARTH SCIENCE > OCEANS > OCEAN CHEMISTRY > NITRATE","EARTH SCIENCE > OCEANS > OCEAN CHEMISTRY > NITRITE","EARTH SCIENCE > OCEANS > OCEAN CHEMISTRY > NITROGEN","EARTH SCIENCE > OCEANS > OCEAN CHEMISTRY > NUTRIENTS","EARTH SCIENCE > OCEANS > OCEAN CHEMISTRY > ORGANIC MATTER","EARTH SCIENCE > OCEANS > OCEAN CHEMISTRY > OXYGEN","EARTH SCIENCE > OCEANS > OCEAN CHEMISTRY > PH","EARTH SCIENCE > OCEANS > OCEAN CHEMISTRY > PHOSPHATE","EARTH SCIENCE > OCEANS > OCEAN CHEMISTRY > PIGMENTS","EARTH SCIENCE > OCEANS > OCEAN CHEMISTRY > PIGMENTS > CHLOROPHYLL","EARTH SCIENCE > OCEANS > OCEAN CHEMISTRY > SILICATE","EARTH SCIENCE > OCEANS > OCEAN CHEMISTRY > SUSPENDED SOLIDS","EARTH SCIENCE > OCEANS > OCEAN OPTICS","EARTH SCIENCE > OCEANS > OCEAN OPTICS > ATTENUATION/TRANSMISSION","EARTH SCIENCE > OCEANS > OCEAN OPTICS > FLUORESCENCE","EARTH SCIENCE > OCEANS > OCEAN OPTICS > IRRADIANCE","EARTH SCIENCE > OCEANS > OCEAN OPTICS > PHOTOSYNTHETICALLY ACTIVE RADIATION","EARTH SCIENCE > OCEANS > OCEAN OPTICS > SECCHI DEPTH","EARTH SCIENCE > OCEANS > OCEAN OPTICS > TURBIDITY","EARTH SCIENCE > OCEANS > OCEAN TEMPERATURE > WATER TEMPERATURE","EARTH SCIENCE > OCEANS > SALINITY/DENSITY > CONDUCTIVITY","EARTH SCIENCE > OCEANS > SALINITY/DENSITY > DENSITY","EARTH SCIENCE > OCEANS > 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QUALITY/WATER CHEMISTRY > WATER CHARACTERISTICS > LIGHT TRANSMISSION","EARTH SCIENCE > TERRESTRIAL HYDROSPHERE > WATER QUALITY/WATER CHEMISTRY > WATER CHARACTERISTICS > NITROGEN COMPOUNDS","EARTH SCIENCE > TERRESTRIAL HYDROSPHERE > WATER QUALITY/WATER CHEMISTRY > WATER CHARACTERISTICS > WATER TEMPERATURE","EARTH SCIENCE > TERRESTRIAL HYDROSPHERE > WATER QUALITY/WATER CHEMISTRY > WATER CHARACTERISTICS > pH","Stressor Impacts and Mitigation > Biological Effects of Contaminants and Nutrients","Field Observation","Inorganic suspended particulate matter","Mean Fo/Fa","Surface Photosynthetic Active Radiation (PAR)","Time","Total Suspended Sediments","organic suspended particulate material","pH mV","Colored Dissolved Organic Matter","DISSOLVED OXYGEN","Depth - YSI","Depth \u2013 Fathometer","INSTRUMENT - DEPTH","Inorganic suspended particulate matter","Mean Fo/Fa","Nitrite + Nitrate content (concentration)","Organic suspended particulate material","Organic suspended particulate matter","Oxygen \u2013 Percent Saturation","SONAR ALTIMETER","Salinity \u2013 Surface Water","Sonar Altimeter\u2013 in Station Log","Specific Conductance","Surface Photosynthetic Active Radiation (PAR)","Temperature \u2013 Water","Time","Total Dissolved Solids","Total Pigments","Total Suspended Sediments","pH mV","AUTOANALYZER > AUTOANALYZER","CONDUCTIVITY METERS > CONDUCTIVITY METERS","CTD > Conductivity, Temperature, Depth","ECHO SOUNDERS > ECHO SOUNDERS","FIA > FLOW INJECTION ANALYSIS","FLUOROMETERS > FLUOROMETERS","GPS RECEIVERS > GPS RECEIVERS","OPTSPEC > Optical Spectrometer","OXYGEN METERS > OXYGEN METERS","PAR SENSORS > Photosynthetically Active Radiation Sensors","PH METERS > PH METERS","PRESSURE SENSORS > PRESSURE SENSORS","SALINOMETERS","SECCHI DISKS > SECCHI DISKS","SEDIMENT CORERS > SEDIMENT CORERS","TEMPERATURE SENSORS > TEMPERATURE SENSORS","THERMOSALINOGRAPHS","TRANSMISSOMETERS","TRAPS > TRAPS","Biospherical Instruments 2-QSP-200L","Biospherical Instruments QSP-2300","Biospherical Instruments QSP-2300 (in water PAR)","Biospherical Instruments QSP-2300 and QSR2200","Biospherical Instruments QSP-2300 in water PAR and QSR-2000/240 Surface PAR","Biospherical Instruments QSR-2000/240 Surface PAR","Biospherical Instruments Surface PAR QSR2200","Chelsea Instruments Aquatraka III","Chelsea Instruments Aquatraka III fluorometer","Dual pumped SBE 3 temperature sensor","Dual pumped SBE 4 conductivity sensor","Furuno GPS Navagation GP-90","Furuno-SC50","GF/F Filter","Hanna HI2003-01","Knudsen Chirp Model 3260 (100kHz/12kHz)","Lachat QuikChem","Mettler Toledo DL28 Titrator","Mettler Toledo G20 Titrator","Multiple Instrument Data Acquisition System (MIDAS)","Odom Echotrac II Fathometer","SBE 13-01","SBE 18 pH/O.R.P (Redox) sensor","SBE 27 pH/O.R.P (Redox) sensor","SBE 3-01/F","SBE 4-01/0","SBE CTD","SBE CTD and SBE 43 dissolved oxygen sensor","SBE CTD, SBE 43 dissolved oxygen sensors","SBE-9+, Paroscientific Digiquartz(r) pressure sensor","SONAR ALTIMETER","Scientific Computer System (SCS)","Scientific Computer System (SCS) and YSI 6820 handheld unit","Scientific Computer System (SCS) and YSI EXO3 handheld unit","Sea-Bird SBE 43 dissolved oxygen sensor","Sea-Bird SBE 43 dissolved oxygen sensors","Seabird model SBE-21 Thermosalinograph","Seapoint Ultraviolet Fluorometer","Sonar Altimeter, Teledyne Benthos Altimeter PSA-916","Sonar Altimeter, Teledyne Benthos PSA-900","Sonar Altimeter, Teledyne Benthos PSA-916","Turner digital 10-AU","WETLabs C-Star 25 cm path length transmissometer","WETLabs CDOM Fluorometer","Wetlabs Transmissometer","YSI - handheld multi-parameter instrument","YSI EXO3 \u2013 handheld multi-parameter instrument","YSI \u2013 handheld multi-parameter instrumen","YSI \u2013 handheld multi-parameter instrument","Biospherical Instruments QSP-2300","Biospherical Instruments QSP-2300 in water PAR and QSR Surface PAR","Biospherical Instruments QSR Surface PAR","Chelsea Instruments Aquatraka III","Dual pumped SBE 3 temperature sensor","Dual pumped SBE 4 conductivity sensor","Furuno GPS Navagation GP-90","Furuno GPS Navigation GP-90","GF/F Filter","Guildline Instruments Portasal","Lachat QuikChem","Mettler Toledo DL28 Titrator","Multiple Instrument Data Acquisition System (MIDAS)","Odom Echotrac II Fathometer","SBE CTD","SBE-9+, Paroscientific Digiquartz(r) pressure sensor","Sea-Bird SBE 43 dissolved oxygen sensor","Sonar Altimeter, Teledyne Benthos PSA-900","Turner digital 10-AU","WETLabs C-Star 25 cm path length transmissometer","WETLabs CDOM fluorometer","YSI - handheld multi-parameter instrument","Ships","ACADIANA (call sign: WDG3928, ICES code: 33SZ, 1985-)","CHAPMAN (call sign: WTED, ICES code: 32YN, 1980-1998)","GYRE (ICES code: 32GY)","LONGHORN (ICES code: 32LH)","Malcolm Baldrige (call sign: WTER, ICES code: 33MW, 1988-1996)","PELICAN (call sign: WSK3051, ICES code: 32PE, 1985-)","Researcher (call sign: WTER, ICES code: 3175, 1970-1987)","Tommy Munro (call sign: WDE4584, ICES code: 33TM)","PELICAN (Call Sign WDD6114 - NODC Code 32PE)","CONTINENT > NORTH AMERICA","CONTINENT > NORTH AMERICA > UNITED STATES OF AMERICA","GEOGRAPHIC REGION > NORTHERN HEMISPHERE","OCEAN > ATLANTIC OCEAN > NORTH ATLANTIC OCEAN","OCEAN > ATLANTIC OCEAN > NORTH ATLANTIC OCEAN > GULF OF AMERICA","OCEAN > ATLANTIC OCEAN > NORTH ATLANTIC OCEAN > GULF OF MEXICO","U.S. States and Territories > Louisiana","Waterbodies > Gulf of Mexico","VERTICAL LOCATION > SEA SURFACE","106TPR","7C298N","82BCLC","AL726U","AWW41G","E92Y1L","FU0FJ8","FY1EKF","KRW314","TAPHP4","UH8MYB","Y7MTJ5"],"landingPage":"https://www.ncei.noaa.gov/contact","language":[],"license":"https://creativecommons.org/publicdomain/zero/1.0/","modified":"2025-12-12T00:00:00.000+00:00","publisher":{"@type":"org:Organization","name":"NOAA National Centers for Environmental 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Hydrographic data were obtained using CTD. 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Santa Cruz Island, CA","SCNB - Newport Beach, CA","SCOV - Sandy Cove, NS","SCPF - Point Fermin, CA","SCRZ - Santa Cruz","SCTB - Torrance Beach, CA","SDBP - San Diego, Border Park","SDCI - San Diego, Coronado Islands","SDCP - Camp Pendleton, CA","SDDP - Dana Point, CA","SDPD - Susan Dionne Pad, Kenai, AK","SDPL - San Diego, Point Loma","SDSC - San Clemente Is, CA","SDSE - San Elijo State Beach, CA","SDSL - San Diego, Scripps Long-range","SDSM - San Mateo Point, CA","SDSN - San Clemente Island North, CA","SDUT - Upper Trestles, San Diego, CA","SDWW - Point Loma Waste Water Treatment Plant, CA","SEA1 - Seaside, OR","SEAB - Sea Bright, NJ","SGRV - Singing River, MS","SHEL - Shelter Cove, CA","SHSH - Shishmaref, AK","SILD - Staten Island, NY","SIMP - Cape Simpson, AK","SISL - Silver Slipper Casino, MS","SLID - Slide Ranch, CA","SLTR - Slaughter Beach, DE","SMOA - Humboldt Bay, Samoa, CA","SMPT - Smith Point, Anahuac,TX (SMPT)","SMR1 - Summerland, CA","SNI1 - San Nicolas Island, CA","SOB2 - South Beach, Martha's Vineyard, MA","SPRK - Seaside Park, NJ","SQUB - Squibnocket Farms, MA","SSD1 - Summerland Sanitary District","SSDE - Surfside, TX","STF - Dania Beach, FL","STLI - Stehli Beach, NY","STV1 - Fort Stevens, OR","STV2 - Fort Stevens, OR","SUNS - Sunset Beach Resort, Cape Charles, VA","SWPP - Southwest Pass, LA","THOM - St. Thomas, USVI","TLSP - Two Lights State Park, ME","TRES - Treasure Island, CA","TRIN - Trinidad, CA","TRL1 - NULL","TRS - Treasure Shores, FL","UABC - Universidad Autonoma de Baja Califonia","VATK - Point Atkinson, West Vancouver","VCOL - Westshore Coal Terminal, Tsawwassen","VDIG - Digby Island, Prince Rupert","VDIG - IDigby Island, Prince Rupert","VEN - Venice, FL","VENI - Venice, FL","VGPT - Georgina Point, Canada","VIEW - Ocean View Beach, VA","VIL - Villarino, Mexico","VION - Iona Wastewater Treatment Plant, Vancouver","VIR - Virginia Key, FL","VJOR - Jordan River, BC, Canada","VRID - Ridley Island, Canada","VROC - Race Rocks, Canada","VSPT - Iona Jetty, B.C., Canada","WAIN - Wainwright, AK","WAUW - Wauwermans Islands","WCDN - Crandon, FL","WEST - Key West, FL","WILD - Wildwood","WIN1 - Winchester Bay, OR","WLD2 - Waldport, OR","WNKL - North Key Largo, FL","WODI - Wood Island, MA","WOOD - North Wildwood, NJ","WSH1 - Washburne, OR","WSP1 - Westport State Park, WA","YHL1 - Yaquina Head Long, OR","YHS1 - Yaquina Head South, OR","YHS2 - Yaquina Head South, OR"],"landingPage":"https://www.ncei.noaa.gov/contact","language":[],"license":"https://creativecommons.org/publicdomain/zero/1.0/","modified":"2026-08-25T00:00:00.000+00:00","publisher":{"@type":"org:Organization","name":"NOAA National Centers for Environmental Information"},"references":["https://www.ncei.noaa.gov/archive/accession/0126755/data/0-data/Bibliography_of_HF_Radar_Comparisons_with_Other_Sensors.pdf","https://www.ncei.noaa.gov/archive/accession/0126755/data/0-data/CODAR_SeaSonde_QA-QC_Setup_and_Diagnostics.pdf","https://www.ncei.noaa.gov/archive/accession/0126755/data/0-data/High-Frequency_Radar_for_Ocean_Surface_Current_Mapping:_Best_Practices.pdf","https://www.ncei.noaa.gov/archive/accession/0126755/data/0-data/High_Frequency_Radar_101_Presentation.pdf","https://www.ncei.noaa.gov/archive/accession/0126755/data/0-data/IOOS_HF_Radar_Data_and_Its_Use_by_the_U.S._Coast_Guard_for_Search_and_Rescue.pdf","https://www.ncei.noaa.gov/archive/accession/0126755/data/0-data/IOOS_and_U.S._Coast_Guard_Search_and_Rescue_Responsibilities.pdf","https://www.ncei.noaa.gov/archive/accession/0126755/data/0-data/National_HF_Radar_Technical_Steering_Team_Position_Paper_on_the_Use_of_HF_Radar_in_Freshwater.pdf","https://www.ncei.noaa.gov/archive/accession/0126755/data/0-data/National_HF_Radar_Technical_Steering_Team_Position_Paper_on_Use_of_HF_Radar_for_Wave_Measurement.pdf","https://www.ncei.noaa.gov/archive/accession/0126755/data/0-data/Search_and_Rescue_Operations_(SAROPS)_Environmental_Data%20Sources:_Their_Uncertainties.pdf","https://doi.org/10.4031/mtsj.44.6.6","https://cdn.ioos.noaa.gov/media/2017/12/hfrarticle_092007.pdf","https://hfradar.ndbc.noaa.gov/","https://cordc.ucsd.edu/"],"rights":"otherRestrictions","spatial":"-62.8876,-64.9183,-166.0785,71.3789","temporal":"2000-03-27T00:00:00+00:00/2000-03-27T00:00:00+00:00","theme":["geospatial"],"title":"Surface ocean radial velocities obtained by HF-radar from stations located along coastal waters of Hawaii, North Slope Alaska, Gulf of Alaska, Puerto Rico/Virgin Islands, eastern U.S./Gulf of America, western U.S., and the Great Lakes"},"description":"This dataset contains surface ocean radial velocities data obtained by HF-radar from stations located along coastal waters of the United States. Radial velocity files contain metadata in a key-value format, while the measured velocities and associated ancillary data are reported in a tab-delimited format.\n\nThe National Data Buoy Center (NDBC) \u2014 in collaboration with the Scripps Institution of Oceanography through June 2025 and thereafter with NOAA\u2019s National Environmental Satellite, Data, and Information Service (NESDIS) \u2014 assembles the data from the Integrated Ocean Observing System (IOOS) Surface Currents Program\u2019s High-Frequency (HF) Radar National Network and submits the data on a monthly basis to NOAA\u2019s National Centers for Environmental Information (NCEI).\n\nRemote sensing of ocean surface velocity from shore-based HF-radar sensors bridges an operational observational gap between point samples obtained from in-situ sampling and synoptic scale relatively low resolution data obtained from satellites by providing continuous mesoscale coverage at relatively high resolution near the coast. HF-radar systems measure the speed of ocean surface currents in directions radial to the antenna in near real time. Radial velocities alone are a measurement of surface ocean velocity projected along the direction radial to the antenna, which only show those currents\u2019 movement towards or away from the HF-radar sensor\u2019s antenna. Radial measurements of ocean velocity may be used directly in some applications such as model assimilation but are commonly used in combination with overlapping sites to estimate the total vector ocean velocity.\n\nSystems operate continuously in all weather conditions and are installed near the coastline. Range resolution of measured currents is determined by the radar transmit bandwidth used. Bandwidth is controlled by radio frequency licenses and translates to range resolutions of 0.5 to 6 kilometers. Maximum ranges of current measurements also depend on radar transmit frequency and vary from about 40 km offshore to about 200 km offshore. 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Nantucket Island, MA","NAPL - Naples, FL","NAUS - Nauset, MA","NIC1 - Nicholas Canyon, CA","NKL - North Key Largo, FL","NPGS - Naval Postgraduate School","NWTP - Nantucket, MA","OBSP - Orange Beach State Park, AL","OCRA - Ocracoke Island, NC","OKKO - Steve Okkonen's House, AK","OLDB - Old Bridge Waterfront Park, NJ","OSPY - Osprey Drilling Platform, AK","PAFS - Point Arena Field Station","PBON - Point Bonita, CA","PBRW - Point Barrow, AK","PCYC - Pass Christian Yacht Club, MS","PESC - Pescadero, CA","PILR - Pillar Point Air Force Station, CA, USA","PINS - Padre Island, TX","PLA8 - Placement 8, Port Arthur,TX (PLA8)","PLPI - Pleasure Pier Blvd, Port Arthur, TX (PLPI)","PMGC - Port Mansfield GERG Codar","POPB - Popham Beach State Park, ME","PORT - Port Monmouth, NJ","PPK - Pepe'ekeo, HI","PPNS - Point Pinos, Pacific Grove, CA","PREY - Point Reyes, CA","PRI - Pritchard's Island, SC","PSG1 - Point St. George, CA","PSLR - Point Sur Long Range, CA","PSUR - Point Sur","PTC1 - Point Conception, CA","PTLY - Point Lay, AK","PTM1 - Point Mugu, CA","PTWN - Provincetown, MA","PYFC - Ponce Yacht and Fishing Club at Ponce, Puerto Rico","QTA - Quinta, Mexico","RAGG - Ragged Point, CA","RATH - Strathmere, NJ","RDSR - Reddington, FL","RFG1 - Refugio State Beach","RLVR - Rollover Pass, TX","RTC1 - Romberg Tiburon Center, CA","SAND - Sandspit, Hecate Strait, BC","SARB - Sargent Beach, TX","SAU - Sauzal, Mexico","SAUS - Sausalito-Marin City Sanitary District, CA, USA","SBAY - Club de Pesca Rec Isla de Cabras, San Juan Bay","SBSR - Salisbury Beach State Reservation, MA","SCCI - Catalina Island, CA","SCDB - Dan Blocker, CA","SCDH - Dockweiler Headquarters, CA","SCI1 - Santa Cruz Island, CA","SCNB - Newport Beach, CA","SCOV - Sandy Cove, NS","SCPF - Point Fermin, CA","SCRZ - Santa Cruz","SCTB - Torrance Beach, CA","SDBP - San Diego, Border Park","SDCI - San Diego, Coronado Islands","SDCP - Camp Pendleton, CA","SDDP - Dana Point, CA","SDPD - Susan Dionne Pad, Kenai, AK","SDPL - San Diego, Point Loma","SDSC - San Clemente Is, CA","SDSE - San Elijo State Beach, CA","SDSL - San Diego, Scripps Long-range","SDSM - San Mateo Point, CA","SDSN - San Clemente Island North, CA","SDUT - Upper Trestles, San Diego, CA","SDWW - Point Loma Waste Water Treatment Plant, CA","SEA1 - Seaside, OR","SEAB - Sea Bright, NJ","SGRV - Singing River, MS","SHEL - Shelter Cove, CA","SILD - Staten Island, NY","SIMP - Cape Simpson, AK","SISL - Silver Slipper Casino, MS","SLID - Slide Ranch, CA","SLTR - Slaughter Beach, DE","SMOA - Humboldt Bay, Samoa, CA","SMPT - Smith Point, Anahuac,TX (SMPT)","SNI1 - San Nicolas Island, CA","SOB2 - South Beach, Martha's Vineyard, MA","SPRK - Seaside Park, NJ","SQUB - Squibnocket Farms, MA","SSD1 - Summerland Sanitary District","SSDE - Surfside, TX","STF - Dania Beach, FL","STLI - Stehli Beach, NY","STV2 - Fort Stevens, OR","SUNS - Sunset Beach Resort, Cape Charles, VA","SWPP - Southwest Pass, LA","THOM - St. Thomas, USVI","TLSP - Two Lights State Park, ME","TRES - Treasure Island, CA","TRIN - Trinidad, CA","TRL1 - NULL","TRS - Treasure Shores, FL","VATK - Point Atkinson, West Vancouver","VCOL - Westshore Coal Terminal, Tsawwassen","VDIG - Digby Island, Prince Rupert","VEN - Venice, FL","VENI - Venice, FL","VGPT - Georgina Point, Canada","VIEW - Ocean View Beach, VA","VIL - Villarino, Mexico","VION - Iona Wastewater Treatment Plant, Vancouver","VIR - Virginia Key, FL","VJOR - Jordan River, BC, Canada","VRID - Ridley Island, Canada","VROC - Race Rocks, Canada","VSPT - Iona Jetty, B.C., Canada","WAIN - Wainwright, AK","WCDN - Crandon, FL","WEST - Key West, FL","WILD - Wildwood","WIN1 - Winchester Bay, OR","WLD2 - Waldport, OR","WNKL - North Key Largo, FL","WOOD - North Wildwood, NJ","WSH1 - Washburne, OR","WSP1 - Westport State Park, WA","YHL1 - Yaquina Head Long, OR","YHS2 - Yaquina Head South, OR"],"landingPage":"https://www.ncei.noaa.gov/contact","language":[],"license":"https://creativecommons.org/publicdomain/zero/1.0/","modified":"2026-08-24T00:00:00.000+00:00","publisher":{"@type":"org:Organization","name":"NOAA National Centers for Environmental Information"},"references":["https://www.ncei.noaa.gov/archive/accession/0126755","https://www.ncei.noaa.gov/archive/accession/0126755/data/0-data/Bibliography_of_HF_Radar_Comparisons_with_Other_Sensors.pdf","https://www.ncei.noaa.gov/archive/accession/0126755/data/0-data/CODAR_SeaSonde_QA-QC_Setup_and_Diagnostics.pdf","https://www.ncei.noaa.gov/archive/accession/0126755/data/0-data/High-Frequency_Radar_for_Ocean_Surface_Current_Mapping:_Best_Practices.pdf","https://www.ncei.noaa.gov/archive/accession/0126755/data/0-data/High_Frequency_Radar_101_Presentation.pdf","https://www.ncei.noaa.gov/archive/accession/0126755/data/0-data/IOOS_HF_Radar_Data_and_Its_Use_by_the_U.S._Coast_Guard_for_Search_and_Rescue.pdf","https://www.ncei.noaa.gov/archive/accession/0126755/data/0-data/IOOS_and_U.S._Coast_Guard_Search_and_Rescue_Responsibilities.pdf","https://www.ncei.noaa.gov/archive/accession/0126755/data/0-data/National_HF_Radar_Technical_Steering_Team_Position_Paper_on_the_Use_of_HF_Radar_in_Freshwater.pdf","https://www.ncei.noaa.gov/archive/accession/0126755/data/0-data/National_HF_Radar_Technical_Steering_Team_Position_Paper_on_Use_of_HF_Radar_for_Wave_Measurement.pdf","https://www.ncei.noaa.gov/archive/accession/0126755/data/0-data/Search_and_Rescue_Operations_(SAROPS)_Environmental_Data%20Sources:_Their_Uncertainties.pdf","https://doi.org/10.4031/mtsj.44.6.6","https://cdn.ioos.noaa.gov/media/2017/12/hfrarticle_092007.pdf","https://doi.org/10.1109/oceans.2006.306883","https://hfradar.ndbc.noaa.gov/","https://cordc.ucsd.edu/"],"rights":"otherRestrictions","spatial":"-62.8876,17.7364,-163.014867,71.3789","temporal":"2006-06-22T00:00:00+00:00/2006-06-22T00:00:00+00:00","theme":["geospatial"],"title":"Near-real-time surface ocean velocities derived from HF-radar stations located along coastal waters of North Slope Alaska, Gulf of Alaska, Puerto Rico/Virgin Islands, eastern U.S./Gulf of America, Hawaii, Great Lakes, and western U.S."},"description":"This dataset contains near-real-time ocean surface velocities, also known as total vector velocities, derived from high-frequency (HF) radar stations. The velocities are arranged in a horizontal latitude/longitude grid. Measured velocities are indicative of the upper 0.3 - 2.5 meters of the ocean depending on the operating frequency of the HF-radar and the vertical velocity profile of the water column. Data files are in NetCDF format following the CF (Climate and Forecast) Metadata Conventions. Velocities are reported in CF variables surface_eastward_sea_water_velocity and surface_northward_sea_water_velocity.\n\nThe National Data Buoy Center (NDBC) \u2013 in collaboration with the Scripps Institution of Oceanography through June 2025 and thereafter with NOAA\u2019s National Environmental Satellite, Data, and Information Service (NESDIS) \u2013 assembles the data from the Integrated Ocean Observing System (IOOS) Surface Currents Program\u2019s HF-Radar National Network and submits the data on a monthly basis to NOAA\u2019s National Centers for Environmental Information (NCEI).\n\nRemote sensing of ocean surface velocity from shore-based HF-radar sensors bridges the operational observational gap between point samples obtained from in-situ sampling and synoptic scale relatively low resolution data obtained from satellites by providing continuous mesoscale coverage at relatively high resolution near the coast.","distribution_titles":["NCEI Dataset Landing Page","Browse granules","Search for granules","THREDDS","HTTPS","FTP","https://www.ncei.noaa.gov/archive/accession/0126755","Codar Intercomparison and Validation Bibliography","CODAR SeaSonde QA/QC Remote Monitoring Checklist","High-Frequency Radar for Ocean Surface Current Mapping: Best Practices","HF Radar Ocean Current Mapping: IOOS Perspective","IOOS HF Radar Data and Its Use by the U.S Coast Guard for Search and Rescue","IOOS and United States Coast Guard Search and Rescue Responsibilities","NOAA's Integrated Ocean Observing System High Frequency Radar Science Steering Team Freshwater Performance Evaluation","National HF Radar Technical Steering Team Position Paper on Use of HF Radar for Wave Measurement","SAROPS Environmental Data Sources: Their Uncertainties","https://doi.org/10.4031/mtsj.44.6.6","https://cdn.ioos.noaa.gov/media/2017/12/hfrarticle_092007.pdf","https://doi.org/10.1109/oceans.2006.306883","https://hfradar.ndbc.noaa.gov/","https://cordc.ucsd.edu/","GCMD Keyword Forum Page","NCEI Contact Information","Scripps Institution of Oceanography (SIO) website"],"harvest_record":"https://catalog.data.gov/harvest_record/4f8d76e6-6f36-42a0-bc4a-92aff618c3dc","harvest_record_raw":"https://catalog.data.gov/harvest_record/4f8d76e6-6f36-42a0-bc4a-92aff618c3dc/raw","harvest_record_transformed":"https://catalog.data.gov/harvest_record/4f8d76e6-6f36-42a0-bc4a-92aff618c3dc/transformed","has_download":true,"has_spatial":true,"identifier":"https://data.noaa.gov/waf/NOAA/NESDIS/ncei/accessions/iso/xml/IOOS-HFRadarRTVector.xml","keyword":["0129913","0131074","0131884","0131908","0131932","0131956","0131976","0131989","0137285","0138228","0139551","0141105","0144286","0145743","0148078","0151726","0154389","0155978","0156399","0156623","0156801","0157039","0157646","0159409","0161124","0162202","0162433","0162827","0163650","0164432","0165174","0170793","0170794","0170795","0170805","0170823","0170847","0171508","0175628","0175985","0176415","0176874","0177852","0181692","0181694","0181896","0182927","0182939","0183056","0183098","0183188","0183197","0183633","0184275","0184848","0184859","0184866","0185111","0185705","0185765","0186285","0186615","0186757","0186913","0187010","0187101","0187245","0187272","0187419","0187515","0187721","0187986","0188254","0188410","0188677","0188705","0188814","0189037","0189106","0189214","0189252","0189342","0189438","0189439","0189494","0189524","0189577","0189578","0189587","0189620","0189730","0189989","0190231","0190724","0190725","0190878","0190954","0191084","0191820","0191898","0193547","0195032","0195407","0196819","0197917","0199634","0200363","0201036","0201388","0201486","0201495","0201702","0201879","0202223","0202301","0202456","0202602","0202653","0203368","0203652","0203761","0203911","0204401","0204739","0204988","0205288","0210796","0210798","0210973","0213853","0218893","0220076","0221138","0222335","0223732","0225089","0225580","0227186","0230674","0234025","0237589","0239567","0240499","0241437","0242335","0243479","0244586","0249146","0249176","0249237","0249520","0249547","0250425","0250433","0250463","0250493","0250575","0250826","0250827","0250979","0251000","0256911","0259400","0259401","0259410","0260099","0260134","0267180","0272769","0276147","0276420","0276837","0277180","0277783","0278740","0279394","0280908","0282024","0283183","0284513","0286563","0287565","0289625","0290483","0291863","0293098","0294244","0295521","0296625","0297593","0298250","0299336","0300074","0301137","0302062","0302264","0302299","0302393","0302470","0302475","0302483","0302485","0302523","0302605","0302626","0302677","0302735","0302837","0302882","0302933","0302934","0302937","0302940","0302942","0302993","0303023","0303025","0303026","0303758","0304570","0305587","0306517","0307599","0307612","0307613","0307624","0307625","0308298","0309066","0309067","0309818","0311055","0311166","0311918","0312873","0313480","0313610","0314610","0315313","0316153","0317044","0317918","CURRENT SPEED - 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Anacapa Island, CA","AGL1 - Pt. Arguello, CA","AMAG - Amagansett, New York","ANGL - Angel Island, CA","ANWR - Aransas National Wildlife Refuge, TX","ARG1 - Pt. Arguello, CA","ASSA - Assateague, MD","BASC - Barrow, AK","BELM - Belmar, NJ","BIGC - Big Creek","BISL - Block Island, RI","BLCK - Block Island","BML1 - Bodega Marine Laboratory, CA","BMLR - Bodega Marine Laboratory Long Range","BONI - Bonilla Island, Hecate Strait, BC","BP01 - San Diego, Scripps Pier, CA","BPAT - BP Rig Atlantis, Gulf of Mexico","BPTH - BP Rig Thunder Horse, Gulf of Mexico","BRAD - Bradley Beach, NJ","BRAG - Fort Bragg, CA","BRIG - Brigantine, NJ","BRMR - Brigantine, NJ","BRNT - Brant Beach, NJ","BRVW - Bridgeview Park, MI","BRZY - Breezy Point, NJ","CAPE - Cape Shore Lab, NJ","CAT - St. Catherine's, GA","CBBT - Chesapeake Bay Bridge Tunnel, VA","CBL1 - Cape Blanco, OR","CCB1 - North Beach, Corpus Christi Bay, TX","CCB2 - University Beach, Corpus Christi Bay, TX","CDDO - Cabo Rojo, Puerto Rico","CDN - Crandon, FL","CEDR - Cedar Island, VA","CLHB - Clarke's Harbour, NS","CLMH - Clam Harbour, NS","CLUB - Cape May Point, NJ","CMPT - Cape May Point, NJ","CNS - Canaveral National Seashore, FL","COMM - Commonweal Center, Bolinas, CA","CON - Conalep, Mexico","CONA - Conalep, Mexico","COP1 - Coal Oil Pt.","CORE - Core Banks, NC","CPHN - Cape Henry, VA, USA","CPLF - Chevron Pipeline Facility, LA","CPVN - Camp Varnum, RI","CRIS - Crissy Field, CA","CSTM - Cape St. Mary, NS, CA","CSW - Fort Caswell, NC","DCLR - Diablo Canyon Long Range, CA","DCSR - Diablo Canyon Standard Range, CA","DUCK - Duck, NC","ERE - Erendira, Mexico","ERRA - Low Beach, Nantucket, MA","ESPT - Eastern Point Retreat House, MA","ESTR - Point Estero, CA","EXPL - The Exploratorium Museum, CA","FARO - Cabo Rojo Lighthouse at Cabo Rojo, Puerto Rico","FBK1 - FallBack22, Pt. Sal, CA","FDS - Ft. De Soto, FL","FLND - First Landing State Park, VA","FOCF - Fourth Cliff Recreation Area, MA","FORT - Fort Funston, CA","FRDO - Reserva Natural Cabezas de San Juan, Fajardo","FTMK - Fort Michilimackinac, MI","FURA - Anasco, Puerto Rico","GCAP - Great Captain Island, CT","GCVE - Gerstle Cove, Salt Point State Park, Sonoma County, CA","GCYN - Granite Canyon, CA","GMNB - Grand Manan, NB, CA","GPTP - Gulfport, MS","GRNI - Green's Island, Maine, USA","GTN - Georgetown, SC","HATY - Cape Hatteras, NC","HAUL - Haulover Inlet, FL","HBSP - Henderson Beach State Park, FL","HBSR - Horseneck Beach State Reserve, MA","HEMP - Hempstead, NY","HILL - Hillsboro, FL","HLGT - Holgate, NJ","HLPN - Cape Henlopen, DE","HOMR - Sandy Hook, NJ","HOOK - Sandy Hook, NJ","HOSR - Sandy Hook, NJ","HTR - Hightower Beach, FL","ICYC - Icy Cape, AK","JEFF - Ft Jefferson, FL","JEK - Jekyll Island, GA, USA","JENN - Jennettes Pier, NC","KAK - Kaka'ako, HI","KAL - Kalaeloa, HI","KAL1 - Kalaloch, WA","KAP - Kapolei, HI","KBCH - Kalifornsky Beach, Cook Inlet, AK","KING - Briscoe King Pavilion, TX","KKH - Keaukaha, HI","KNA - Kaena, HI","KOK - Koko Head, HI","KSC - Kennedy Space Center, FL","LEND - Land's End, CA","LEWE - Lewes, DE","LISL - Little Island Park, VA","LOO1 - Loomis Lake, OR","LOOK - Point Lookout, NY","LOPT - Lockport, NS","LOVE - Loveladies","LPWR - Long Point Wildlife Refuge, MA","LUIS - Point San Luis, CA","MABO - Punta Tuna Lighthouse, Maunabo, Puerto Rico","MAN1 - Manhattan Beach, OR","MARA - Marathon, FL","MATA - Matagorda Island, TX","MBAC - Monterey Bay Academy, California","MBNP - Matagorda Bay Nature Park","MBP - Myrtle Beach State Park","MCPK - McCollum Park Beach City, TX","METL - Metal Magic, AK","METS - MVCO Meteorological Mast, MA","MGS1 - Mandalay Generating Station","MISQ - Misquamicut, RI","MLML - Moss Landing Marine Laboratories, CA","MNTK - Montauk, NY","MOLA - Moses Lake Floodgate, Texas City, TX","MONT - Montara Sanitary District, Montara, CA","MRCH - Moriches, NY","MVCO - Martha's Vineyard, MA","NANT - Nantucket Island, MA","NAPL - Naples, FL","NAUS - Nauset, MA","NIC1 - Nicholas Canyon, CA","NKL - North Key Largo, FL","NPGS - Naval Postgraduate School","NWTP - Nantucket, MA","OBSP - Orange Beach State Park, AL","OCRA - Ocracoke Island, NC","OKKO - Steve Okkonen's House, AK","OLDB - Old Bridge Waterfront Park, NJ","OSPY - Osprey Drilling Platform, AK","PAFS - Point Arena Field Station","PBON - Point Bonita, CA","PBRW - Point Barrow, AK","PCYC - Pass Christian Yacht Club, MS","PESC - Pescadero, CA","PILR - Pillar Point Air Force Station, CA, USA","PINS - Padre Island, TX","PLA8 - Placement 8, Port Arthur,TX (PLA8)","PLPI - Pleasure Pier Blvd, Port Arthur, TX (PLPI)","PMGC - Port Mansfield GERG Codar","POPB - Popham Beach State Park, ME","PORT - Port Monmouth, NJ","PPK - Pepe'ekeo, HI","PPNS - Point Pinos, Pacific Grove, CA","PREY - Point Reyes, CA","PRI - Pritchard's Island, SC","PSG1 - Point St. George, CA","PSLR - Point Sur Long Range, CA","PSUR - Point Sur","PTC1 - Point Conception, CA","PTLY - Point Lay, AK","PTM1 - Point Mugu, CA","PTWN - Provincetown, MA","PYFC - Ponce Yacht and Fishing Club at Ponce, Puerto Rico","QTA - Quinta, Mexico","RAGG - Ragged Point, CA","RATH - Strathmere, NJ","RDSR - Reddington, FL","RFG1 - Refugio State Beach","RLVR - Rollover Pass, TX","RTC1 - Romberg Tiburon Center, CA","SAND - Sandspit, Hecate Strait, BC","SARB - Sargent Beach, TX","SAU - Sauzal, Mexico","SAUS - Sausalito-Marin City Sanitary District, CA, USA","SBAY - Club de Pesca Rec Isla de Cabras, San Juan Bay","SBSR - Salisbury Beach State Reservation, MA","SCCI - Catalina Island, CA","SCDB - Dan Blocker, CA","SCDH - Dockweiler Headquarters, CA","SCI1 - Santa Cruz Island, CA","SCNB - Newport Beach, CA","SCOV - Sandy Cove, NS","SCPF - Point Fermin, CA","SCRZ - Santa Cruz","SCTB - Torrance Beach, CA","SDBP - San Diego, Border Park","SDCI - San Diego, Coronado Islands","SDCP - Camp Pendleton, CA","SDDP - Dana Point, CA","SDPD - Susan Dionne Pad, Kenai, AK","SDPL - San Diego, Point Loma","SDSC - San Clemente Is, CA","SDSE - San Elijo State Beach, CA","SDSL - San Diego, Scripps Long-range","SDSM - San Mateo Point, CA","SDSN - San Clemente Island North, CA","SDUT - Upper Trestles, San Diego, CA","SDWW - Point Loma Waste Water Treatment Plant, CA","SEA1 - Seaside, OR","SEAB - Sea Bright, NJ","SGRV - Singing River, MS","SHEL - Shelter Cove, CA","SILD - Staten Island, NY","SIMP - Cape Simpson, AK","SISL - Silver Slipper Casino, MS","SLID - Slide Ranch, CA","SLTR - Slaughter Beach, DE","SMOA - Humboldt Bay, Samoa, CA","SMPT - Smith Point, Anahuac,TX (SMPT)","SNI1 - San Nicolas Island, CA","SOB2 - South Beach, Martha's Vineyard, MA","SPRK - Seaside Park, NJ","SQUB - Squibnocket Farms, MA","SSD1 - Summerland Sanitary District","SSDE - Surfside, TX","STF - Dania Beach, FL","STLI - Stehli Beach, NY","STV2 - Fort Stevens, OR","SUNS - Sunset Beach Resort, Cape Charles, VA","SWPP - Southwest Pass, LA","THOM - St. Thomas, USVI","TLSP - Two Lights State Park, ME","TRES - Treasure Island, CA","TRIN - Trinidad, CA","TRL1 - NULL","TRS - Treasure Shores, FL","VATK - Point Atkinson, West Vancouver","VCOL - Westshore Coal Terminal, Tsawwassen","VDIG - Digby Island, Prince Rupert","VEN - Venice, FL","VENI - Venice, FL","VGPT - Georgina Point, Canada","VIEW - Ocean View Beach, VA","VIL - Villarino, Mexico","VION - Iona Wastewater Treatment Plant, Vancouver","VIR - Virginia Key, FL","VJOR - Jordan River, BC, Canada","VRID - Ridley Island, Canada","VROC - Race Rocks, Canada","VSPT - Iona Jetty, B.C., Canada","WAIN - Wainwright, AK","WCDN - Crandon, FL","WEST - Key West, FL","WILD - Wildwood","WIN1 - Winchester Bay, OR","WLD2 - Waldport, OR","WNKL - North Key Largo, FL","WOOD - North Wildwood, NJ","WSH1 - Washburne, OR","WSP1 - Westport State Park, WA","YHL1 - Yaquina Head Long, OR","YHS2 - Yaquina Head South, OR"],"last_harvested_date":"2026-09-27T00:09:08.075975","organization":{"aliases":[""],"code_repo_exempt":false,"code_repo_url":null,"description":null,"id":"5f4f1195-e770-4a2a-8f75-195cd98860ce","logo":"https://raw.githubusercontent.com/GSA/logo/refs/heads/master/noaa.png","name":"National Oceanic and Atmospheric Administration, Department of Commerce","organization_type":"Federal Government","slug":"noaa"},"parent_identifier":null,"popularity":0,"publisher":"NOAA National Centers for Environmental Information","slug":"near-real-time-surface-ocean-velocities-derived-from-hf-radar-stations-located-along-coast","spatial_centroid":{"lat":39.193400000000004,"lon":-102.9385068},"spatial_shape":{"coordinates":[[[-62.8876,17.7364],[-62.8876,71.3789],[-163.014867,71.3789],[-163.014867,17.7364],[-62.8876,17.7364]]],"type":"Polygon"},"theme":["geospatial"],"title":"Near-real-time surface ocean velocities derived from HF-radar stations located along coastal waters of North Slope Alaska, Gulf of Alaska, Puerto Rico/Virgin Islands, eastern U.S./Gulf of America, Hawaii, Great Lakes, and western U.S.","type":"dataset"}],"sort":"last_harvested_date"}