Timeline / Data.gov — Environment Datasets
changed Source changed
A new raw object was archived. Both versions are preserved. 2616 line(s) added, 2249 line(s) removed.
Evidence
| Source | Data.gov — Environment Datasets |
|---|---|
| Agency | Data.gov |
| URL | https://api.gsa.gov/technology/datagov/v4/search?q=environment&sort=last_harvested_date&per_page=100&api_key=${DATAGOV_API_KEY} |
| Observed by | Civic Memory, directly, on 2026-09-24T18:29:04+00:00 |
| Content type | application/json |
| Current object |
7d2f26abc5b68df2b1e6b5b2c5936a49dad6021d30458bb9dda0d831a144ff70
download raw
metadata
|
| Previous object |
d0913b8bbd1ed42aca638de0d642143a71275e10ef0646e2eabb966d96757a35
download raw
metadata
|
What changed derived
This diff is not evidence. It was produced by
civic-memory.diff_engine 1.1.0 at
2026-09-24T18:29:04+00:00 by normalizing the two archived objects above. The
objects are authoritative; this reading of them can be regenerated or deleted
without loss. 2616 line(s) added, 2249 line(s) removed.
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Based on the expected 100-year flood flow rate in a given creek, river or surface water system, the flood water level can be mapped as an area of inundation. The resulting floodplain map is referred to as the 100-year floodplain, which may figure very importantly in building permits, environmental regulations, and flood insurance. Flood hazard areas identified on the Flood Insurance Rate Map are identified as a Special Flood Hazard Area (SFHA). SFHA are defined as the area that will be inundated by the flood event having a 1-percent chance of being equaled or exceeded in any given year. 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PCSO Watershed Districts layer is based on the USGS River Basin for Mecklenburg County, with the addition of Six Mile Creek. Six Mile Creek has distinct requirements according to the Sec 18-142 Watershed Districts of the Post Construction Stormwater Ordinance of the City of Charlotte.</span></span></p>", + "distribution": [ + { + "@type": "dcat:Distribution", + "accessURL": "https://data.charlottenc.gov/api/download/v1/items/1885cde77a9b499fbe091a05cd9663ff/csv?layers=0", + "format": "CSV", + "mediaType": "text/csv", + "title": "CSV" + }, + { + "@type": "dcat:Distribution", + "accessURL": "https://data.charlottenc.gov/api/download/v1/items/1885cde77a9b499fbe091a05cd9663ff/geojson?layers=0", + "format": "GeoJSON", + "mediaType": "application/vnd.geo+json", + "title": "GeoJSON" + }, + { + "@type": "dcat:Distribution", + "accessURL": "https://data.charlottenc.gov/api/download/v1/items/1885cde77a9b499fbe091a05cd9663ff/kml?layers=0", + "format": "KML", + "mediaType": "application/vnd.google-earth.kml+xml", + "title": "KML" + }, + { + "@type": "dcat:Distribution", + "accessURL": "https://data.charlottenc.gov/api/download/v1/items/1885cde77a9b499fbe091a05cd9663ff/shapefile?layers=0", + "format": "ZIP", + "mediaType": "application/zip", + "title": "Shapefile" + }, + { + "@type": "dcat:Distribution", + "accessURL": "https://data.charlottenc.gov/datasets/charlotte::pcso-watershed-districts", + "format": "Web Page", + "mediaType": "text/html", + "title": "ArcGIS Hub Dataset" + }, + { + "@type": "dcat:Distribution", + "accessURL": "https://gis.charlottenc.gov/arcgis/rest/services/STM/PCSOWatershedDistricts/MapServer/0", + "format": "ArcGIS GeoServices REST API", + "mediaType": "application/json", + "title": "ArcGIS GeoService" + } + ], + "identifier": "https://www.arcgis.com/home/item.html?id=1885cde77a9b499fbe091a05cd9663ff&sublayer=0", + "issued": "2022-01-25T01:13:57.000Z", + "keyword": [ + "Charlotte", + "Environment", + "Mecklenburg County", + "North Carolina", + "River Basins", + "Storm Water", + "Storm Water Services", + "Stormwater", + "USA" + ], + "landingPage": "https://data.charlottenc.gov/datasets/charlotte::pcso-watershed-districts", + "license": "https://creativecommons.org/licenses/by/4.0", + "modified": "2026-09-23T23:56:43.000Z", + "publisher": { + "name": "City of Charlotte" + }, + "spatial": "-81.0584,34.9986,-80.5565,35.5232", + "theme": [ + "geospatial" + ], + "title": "PCSO Watershed Districts" + }, + "description": "<p><span style='background-color:rgb(255,255,255); color:rgb(42,27,60); font-family:-apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, "Helvetica Neue", Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol", "Noto Color Emoji"; font-size:16px;'><span style='display:inline !important; float:none; font-style:normal; font-variant-caps:normal; font-variant-ligatures:normal; font-weight:400; letter-spacing:normal; text-align:left; text-decoration-color:initial; text-decoration-style:initial; text-indent:0px; text-transform:none; word-spacing:0px;'>Post Construction Stormwater Ordinance (PCSO) Watershed Districts are the areas of land that drain all the streams and rainfall to a common outlet along a stream channel. PCSO Watershed Districts layer is based on the USGS River Basin for Mecklenburg County, with the addition of Six Mile Creek. 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Please consult Land Records to perform research.", + "distribution_titles": [ + "CSV", + "GeoJSON", + "KML", + "Shapefile", + "ArcGIS Hub Dataset", + "ArcGIS GeoService" + ], + "harvest_record": "https://catalog.data.gov/harvest_record/f5fac7c5-31f0-4c2b-aa30-61f21abb2736", + "harvest_record_raw": "https://catalog.data.gov/harvest_record/f5fac7c5-31f0-4c2b-aa30-61f21abb2736/raw", + "has_download": false, + "has_spatial": true, + "identifier": "https://www.arcgis.com/home/item.html?id=16c6f5c77f7145c0b230cfb0457e10b8&sublayer=0", + "keyword": [ + "Charlotte", + "Environment", + "Mecklenburg County", + "North Carolina", + "Storm Water", + "Storm Water Easements", + "Storm Water Services", + "Stormwater", + "USA" + ], + "last_harvested_date": "2026-09-24T17:49:35.193396", + "organization": { + "aliases": [ + "north carolina" + ], + "code_repo_exempt": false, + "code_repo_url": null, + "description": null, + "id": "771e022a-4a81-4cce-ac79-f6e04bdf76d3", + "logo": "", + "name": "City of Charlotte", + "organization_type": "City Government", + "slug": "charlotte-nc" + }, + "parent_identifier": null, + "popularity": 0, + "publisher": "City of Charlotte", + "slug": "storm-water-easements", + "spatial_centroid": { + "lat": 35.20648, + "lon": -80.87478 + }, + "spatial_shape": { + "coordinates": [ + [ + [ + -81.0357, + 35.0158 + ], + [ + -81.0357, + 35.4925 + ], + [ + -80.6334, + 35.4925 + ], + [ + -80.6334, + 35.0158 + ], + [ + -81.0357, + 35.0158 + ] + ] + ], + "type": "Polygon" + }, + "theme": [ + "geospatial" + ], + "title": "Storm Water Easements", + "type": "dataset" + }, + { + "_score": 9.54983, + "_sort": [ + 1790272168811, + 9.54983, + 0, + "e9db686b-bada-48b2-80a4-8eb0aa4f2173" + ], + "dcat": { + "@type": "dcat:Dataset", + "accessLevel": "public", + "contactPoint": { + "@type": "vcard:Contact", + "fn": "Charlotte NC", + "hasEmail": "mailto:gisadmins@ci.charlotte.nc.us" + }, + "description": "<div style='text-align:left;'><p><span style='color:rgb(55, 65, 81); font-family:Lato, Seravek, "Gill Sans Nova", Ubuntu, Roboto, Calibri, "DejaVu Sans", source-sans-pro, sans-serif;'><font size='3'>This dataset shows the storm water watersheds, these watersheds identify a creek or stream that storm water will flow into after a precipitation event. These watershed boundaries are located in Mecklenburg County, North Carolina.</font></span><br /></p></div>", + "distribution": [ + { + "@type": "dcat:Distribution", + "accessURL": "https://data.charlottenc.gov/api/download/v1/items/e9a63a5ffe8a4e109b8c1ade0d61030a/csv?layers=0", + "format": "CSV", + "mediaType": "text/csv", + "title": "CSV" + }, + { + "@type": "dcat:Distribution", + "accessURL": "https://data.charlottenc.gov/api/download/v1/items/e9a63a5ffe8a4e109b8c1ade0d61030a/filegdb?layers=0", + "format": "ZIP", + "mediaType": "application/zip", + "title": "File Geodatabase" + }, + { + "@type": "dcat:Distribution", + "accessURL": "https://data.charlottenc.gov/api/download/v1/items/e9a63a5ffe8a4e109b8c1ade0d61030a/geojson?layers=0", + "format": "GeoJSON", + "mediaType": "application/vnd.geo+json", + "title": "GeoJSON" + }, + { + "@type": "dcat:Distribution", + "accessURL": "https://data.charlottenc.gov/api/download/v1/items/e9a63a5ffe8a4e109b8c1ade0d61030a/kml?layers=0", + "format": "KML", + "mediaType": "application/vnd.google-earth.kml+xml", + "title": "KML" + }, + { + "@type": "dcat:Distribution", + "accessURL": "https://data.charlottenc.gov/api/download/v1/items/e9a63a5ffe8a4e109b8c1ade0d61030a/shapefile?layers=0", + "format": "ZIP", + "mediaType": "application/zip", + "title": "Shapefile" + }, + { + "@type": "dcat:Distribution", + "accessURL": "https://data.charlottenc.gov/datasets/charlotte::watershed-basins-2", + "format": "Web Page", + "mediaType": "text/html", + "title": "ArcGIS Hub Dataset" + }, + { + "@type": "dcat:Distribution", + "accessURL": "https://meckgis.mecklenburgcountync.gov/server/rest/services/StormWaterWatersheds/FeatureServer/0", + "format": "ArcGIS GeoServices REST API", + "mediaType": "application/json", + "title": "ArcGIS GeoService" + } + ], + "identifier": "https://www.arcgis.com/home/item.html?id=e9a63a5ffe8a4e109b8c1ade0d61030a&sublayer=0", + "issued": "2022-04-04T16:15:39.000Z", + "keyword": [ + "Charlotte", + "Environment", + "Mecklenburg County", + "North Carolina", + "Storm Water", + "Storm Water Services", + "Stormwater", + "USA", + "Watershed Basins" + ], + "landingPage": "https://data.charlottenc.gov/datasets/charlotte::watershed-basins-2", + "license": "https://creativecommons.org/licenses/by/4.0", + "modified": "2026-09-24T00:00:45.000Z", + "publisher": { + "name": "City of Charlotte" + }, + "spatial": "-81.0563,34.9991,-80.5561,35.5198", + "theme": [ + "geospatial" + ], + "title": "Watershed Basins" + }, + "description": "<div style='text-align:left;'><p><span style='color:rgb(55, 65, 81); font-family:Lato, Seravek, "Gill Sans Nova", Ubuntu, Roboto, Calibri, "DejaVu Sans", source-sans-pro, sans-serif;'><font size='3'>This dataset shows the storm water watersheds, these watersheds identify a creek or stream that storm water will flow into after a precipitation event. These watershed boundaries are located in Mecklenburg County, North Carolina.</font></span><br /></p></div>", + "distribution_titles": [ + "CSV", + "File Geodatabase", + "GeoJSON", + "KML", + "Shapefile", + "ArcGIS Hub Dataset", + "ArcGIS GeoService" + ], + "harvest_record": "https://catalog.data.gov/harvest_record/52c0de0e-38ef-4a43-bc94-dc142eca6ade", + "harvest_record_raw": "https://catalog.data.gov/harvest_record/52c0de0e-38ef-4a43-bc94-dc142eca6ade/raw", + "has_download": false, + "has_spatial": true, + "identifier": "https://www.arcgis.com/home/item.html?id=e9a63a5ffe8a4e109b8c1ade0d61030a&sublayer=0", + "keyword": [ + "Charlotte", + "Environment", + "Mecklenburg County", + "North Carolina", + "Storm Water", + "Storm Water Services", + "Stormwater", + "USA", + "Watershed Basins" + ], + "last_harvested_date": "2026-09-24T17:49:28.811378", + "organization": { + "aliases": [ + "north carolina" + ], + "code_repo_exempt": false, + "code_repo_url": null, + "description": null, + "id": "771e022a-4a81-4cce-ac79-f6e04bdf76d3", + "logo": "", + "name": "City of Charlotte", + "organization_type": "City Government", + "slug": "charlotte-nc" + }, + "parent_identifier": null, + "popularity": 0, + "publisher": "City of Charlotte", + "slug": "watershed-basins", + "spatial_centroid": { + "lat": 35.20738, + "lon": -80.85622 + }, + "spatial_shape": { + "coordinates": [ + [ + [ + -81.0563, + 34.9991 + ], + [ + -81.0563, + 35.5198 + ], + [ + -80.5561, + 35.5198 + ], + [ + -80.5561, + 34.9991 + ], + [ + -81.0563, + 34.9991 + ] + ] + ], + "type": "Polygon" + }, + "theme": [ + "geospatial" + ], + "title": "Watershed Basins", + "type": "dataset" + }, + { + "_score": 10.417429, "_sort": [ 1790212848966, - 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In this data release the following data are provided for 602 morphologically identified and genotyped Lake Superior ciscoes: sample location including state and country, ecoregion, collection date, geographic coordinates, sampling gear, collector; morphological and genetic species identifications; morphological conformation scores; Q-scores; measurement data for 38 morphometric characters and counts; USGS specimen number; MEL_ID (Molecular Ecology Lab Identifier); and National Center for Biotechnology Information (NCBI) accession numbers for genetic data.", - "distribution": [ - { - "@type": "dcat:Distribution", - "accessURL": "https://doi.org/10.5066/P1R4SNN5", - "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.6a07284eb66b01b8f8e903c3.xml", - "format": "XML", - "mediaType": "text/xml", - "title": "Original Metadata" - } - ], - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_6a07284eb66b01b8f8e903c3", - "keyword": [ - "Coregonine", - "Coregonus", - "Coregonus artedi", - "Coregonus clupeaformis", - "Coregonus hoyi", - "Coregonus kiyi", - "Coregonus nigripinnis", - "Coregonus reighardi", - "Coregonus zenithicus", - "DNA sequencing", - "Great Lakes", - "Lake Superior", - "Natural Resource Management", - "USGS:6a07284eb66b01b8f8e903c3", - "animals", - "aquatic biology", - "biodiversity", - "biota", - "environment", - "fish", - "freshwater ecosystems", - "genetic diversity", - "genetics", - "genotype", - "ichthyology", - "inlandWaters", - "meristics", - "morphology (biological)", - "native species", - "species diversity" - ], - "modified": "2026-09-21T00:00:00Z", - "publisher": { - "@type": "org:Organization", - "name": "U.S. Geological Survey" - }, - "spatial": "-92.6807, 46.3166, -84.1553, 49.1530", - "theme": [ - "geospatial" - ], - "title": "Morphological and genetic data for the Lake Superior cisco complex, 2006-2021" - }, - "description": "Contained in this data release are the core data elements of our study of the contemporary diversity of the cisco complex of Lake Superior as described by Koelz (1929): Coregonus artedi, C. hoyi, C. kiyi, C. zenithicus, C. reighardi, and C. nigripinnis (Gorman et al. 2026). Fish were collected over a broad range of habitats and geographic regions of Lake Superior during 2003-2021. Most collections were conducted by the U.S. Geological Survey and the Department of Fisheries and Oceans Canada and supplemented by collections from The Nature Conservancy and state and tribal partners. A subset of 602 fish collected from years 2006-2021 were identified morphologically, genotyped, and measured morphometrically. In this data release the following data are provided for 602 morphologically identified and genotyped Lake Superior ciscoes: sample location including state and country, ecoregion, collection date, geographic coordinates, sampling gear, collector; morphological and genetic species identifications; morphological conformation scores; Q-scores; measurement data for 38 morphometric characters and counts; USGS specimen number; MEL_ID (Molecular Ecology Lab Identifier); and National Center for Biotechnology Information (NCBI) accession numbers for genetic data.", - "distribution_titles": [ - "Digital Data", - "Original Metadata" - ], - "harvest_record": "https://catalog.data.gov/harvest_record/c4479b43-3559-46b7-a105-75b903b41af6", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/c4479b43-3559-46b7-a105-75b903b41af6/raw", - "has_download": true, - "has_spatial": true, - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_6a07284eb66b01b8f8e903c3", - "keyword": [ - "Coregonine", - "Coregonus", - "Coregonus artedi", - "Coregonus clupeaformis", - "Coregonus hoyi", - "Coregonus kiyi", - "Coregonus nigripinnis", - "Coregonus reighardi", - "Coregonus zenithicus", - "DNA sequencing", - "Great Lakes", - "Lake Superior", - "Natural Resource Management", - "USGS:6a07284eb66b01b8f8e903c3", - "animals", - "aquatic biology", - "biodiversity", - "biota", - "environment", - "fish", - "freshwater ecosystems", - "genetic diversity", - "genetics", - "genotype", - "ichthyology", - "inlandWaters", - "meristics", - "morphology (biological)", - "native species", - "species diversity" - ], - "last_harvested_date": "2026-09-24T00:17:46.621962", - "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": "morphological-and-genetic-data-for-the-lake-superior-cisco-complex-2006-2021", - "spatial_centroid": { - "lat": 47.45116, - "lon": -89.27054000000001 - }, - "spatial_shape": { - "coordinates": [ - [ - [ - -92.6807, - 46.3166 - ], - [ - -92.6807, - 49.153 - ], - [ - -84.1553, - 49.153 - ], - [ - -84.1553, - 46.3166 - ], - [ - -92.6807, - 46.3166 - ] - ] - ], - "type": "Polygon" - }, - "theme": [ - "geospatial" - ], - "title": "Morphological and genetic data for the Lake Superior cisco complex, 2006-2021", - "type": "dataset" - }, - { - "_score": 6.859107, - "_sort": [ - 1790208840919, - 6.859107, - 0, - "8a65f856-9b15-49df-897c-e34a07e872bd" - ], - "dcat": { - "accessLevel": "public", - "bureauCode": [ - "010:12" - ], - "contactPoint": { - "@type": "vcard:Contact", - "fn": "Lyndsay B. Ball", - "hasEmail": "mailto:lbball@usgs.gov" - }, - "description": "Hydrologic and geophysical data were collected in 2023-2025 near the Perigo Mine in Gilpin County, Colorado. Two boreholes (P9 and P10) were drilled in the fall of 2023. The drill site is located on a forested mountain hillslope near abandoned mining infrastructure at an elevation of about 2,970 meters. The boreholes were continuously cored using a wireline HQ-sized coring system through Quaternary soil, colluvium, and Precambrian-aged gneiss bedrock. In-situ injection-based hydraulic tests were performed during drilling while advancing using a single-packer apparatus in tandem with an in-line flow meter and interval pressure monitoring. Borehole geophysical logging was performed in the open holes. Each borehole was completed as four vertically discrete nested monitoring wells (P9A-D and P10A-D). Pressure transducers have been deployed in these wells along with pre-existing monitoring wells (P5 and P8) to monitor groundwater levels and temperature. Additionally, shallow soil moisture and temperature monitoring data were collected at 15 locations across the hillslope to better understand infiltration dynamics.\nThis data release includes borehole location and well completion information from P9 and P10. The hydraulic test data directory contains in-situ packer test data collected during drilling and laboratory permeability/porosity results from selected core samples. The geophysical log directory contains borehole geophysical logs collected prior to well completion. The hydrologic monitoring data directory contains groundwater level and temperature data for fall 2023 to summer 2025. The soil moisture and temperature data directory contains shallow monitoring data for fall 2023-fall 2024.", - "distribution": [ - { - "@type": "dcat:Distribution", - "accessURL": "https://doi.org/10.5066/P149XR6J", - "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.68b0dbb8d4be02739177e93f.xml", - "format": "XML", - "mediaType": "text/xml", - "title": "Original Metadata" - } - ], - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_68b0dbb8d4be02739177e93f", - "keyword": [ - "Colorado", - "Colorado Division of Reclamation, Mining, and Safety", - "DRMS", - "Dakota Hill", - "GGGSC", - "Gamble Gulch", - "Geology, Geophysics, and Geochemistry Science Center", - "Gilpin", - "MRP", - "Mineral Resources Program", - "Perigo (historical)", - "Roosevelt National Forest", - "U.S. Geological Survey", - "USGS", - "USGS:68b0dbb8d4be02739177e93f", - "University of Wyoming", - "borehole logging", - "core analysis", - "drilling and coring", - "environment", - "geoscientificInformation", - "groundwater", - "groundwater level", - "hydrogeology", - "permeability", - "porosity" - ], - "modified": "2026-09-16T00:00:00Z", - "publisher": { - "@type": "org:Organization", - "name": "U.S. Geological Survey" - }, - "spatial": "-105.534507, 39.878868, -105.528252, 39.881091", - "theme": [ - "geospatial" - ], - "title": "Hydrologic and borehole geophysical data from the Perigo Mine site, Gilpin County Colorado" - }, - "description": "Hydrologic and geophysical data were collected in 2023-2025 near the Perigo Mine in Gilpin County, Colorado. Two boreholes (P9 and P10) were drilled in the fall of 2023. The drill site is located on a forested mountain hillslope near abandoned mining infrastructure at an elevation of about 2,970 meters. The boreholes were continuously cored using a wireline HQ-sized coring system through Quaternary soil, colluvium, and Precambrian-aged gneiss bedrock. In-situ injection-based hydraulic tests were performed during drilling while advancing using a single-packer apparatus in tandem with an in-line flow meter and interval pressure monitoring. Borehole geophysical logging was performed in the open holes. Each borehole was completed as four vertically discrete nested monitoring wells (P9A-D and P10A-D). Pressure transducers have been deployed in these wells along with pre-existing monitoring wells (P5 and P8) to monitor groundwater levels and temperature. Additionally, shallow soil moisture and temperature monitoring data were collected at 15 locations across the hillslope to better understand infiltration dynamics.\nThis data release includes borehole location and well completion information from P9 and P10. The hydraulic test data directory contains in-situ packer test data collected during drilling and laboratory permeability/porosity results from selected core samples. The geophysical log directory contains borehole geophysical logs collected prior to well completion. The hydrologic monitoring data directory contains groundwater level and temperature data for fall 2023 to summer 2025. The soil moisture and temperature data directory contains shallow monitoring data for fall 2023-fall 2024.", - "distribution_titles": [ - "Digital Data", - "Original Metadata" - ], - "harvest_record": "https://catalog.data.gov/harvest_record/449f5688-3b72-47d0-843b-edea92d34602", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/449f5688-3b72-47d0-843b-edea92d34602/raw", - "has_download": true, - "has_spatial": true, - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_68b0dbb8d4be02739177e93f", - "keyword": [ - "Colorado", - "Colorado Division of Reclamation, Mining, and Safety", - "DRMS", - "Dakota Hill", - "GGGSC", - "Gamble Gulch", - "Geology, Geophysics, and Geochemistry Science Center", - "Gilpin", - "MRP", - "Mineral Resources Program", - "Perigo (historical)", - "Roosevelt National Forest", - "U.S. Geological Survey", - "USGS", - "USGS:68b0dbb8d4be02739177e93f", - "University of Wyoming", - "borehole logging", - "core analysis", - "drilling and coring", - "environment", - "geoscientificInformation", - "groundwater", - "groundwater level", - "hydrogeology", - "permeability", - "porosity" - ], - "last_harvested_date": "2026-09-24T00:14:00.919002", - "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": "hydrologic-and-borehole-geophysical-data-from-the-perigo-mine-site-gilpin-county-colorado", - "spatial_centroid": { - "lat": 39.87975719999999, - "lon": -105.532005 - }, - "spatial_shape": { - "coordinates": [ - [ - [ - -105.534507, - 39.878868 - ], - [ - -105.534507, - 39.881091 - ], - [ - -105.528252, - 39.881091 - ], - [ - -105.528252, - 39.878868 - ], - [ - -105.534507, - 39.878868 - ] - ] - ], - "type": "Polygon" - }, - "theme": [ - "geospatial" - ], - "title": "Hydrologic and borehole geophysical data from the Perigo Mine site, Gilpin County Colorado", - "type": "dataset" - }, - { - "_score": 10.170767, - "_sort": [ - 1790208742942, - 10.170767, - 0, - "28566861-8d65-4d5d-8e73-8355b983184e" - ], - "dcat": { - "accessLevel": "public", - "bureauCode": [ - "010:12" - ], - "contactPoint": { - "@type": "vcard:Contact", - "fn": "Erica Stuber", - "hasEmail": "mailto:erica.stuber@usu.edu" - }, - "description": "This raster dataset provides estimated ecosystem condition scores, representing the difference between current conditions and reference/baseline conditions, for Utah, USA for the year 2024. The data are analogous to LANDFIRE's Vegetation Departure Scores (which are calculated using LANDFIRE Succession-Class raster data, and LANDFIRE Biophysical Settings raster data), but we used custom processing of the underlying LANDFIRE data to generate scores at higher resolution.\nLANDFIRE Succession Class (S-Class) maps at 30 m resolution were summarized within 300 m analysis cells. Each 300 m cell contains the proportional cover of seven vegetation classes: A (early development), B (mid-development closed), C (mid-development open), D (late-development open), E (late-development closed), UN (uncharacteristic native), and UE (uncharacteristic exotic). S-classes for each ecosystem type consider the type, cover, and height of vegetation, and whether the vegetation is characteristic of ecosystem type. The dominant LANDFIRE Biophysical Setting in each 300 m cell was used to identify reference-condition expectations. \nThe Ecosystem Condition score raster provides a single, integrated departure score ranging from 0 to 100, where larger values indicate greater departure from reference conditions. The score is based on the same ecological departure framework used by the LANDFIRE Vegetation Departure product and the Fire Regime Condition Class (FRCC) methodology.\nTo calculate the score, vegetation conditions within each 300 m grid cell are first summarized across seven LANDFIRE Succession Classes (S-Classes): A, B, C, D, E, UN, and UE. Current proportions of each S-Class are compared with the proportions expected under reference conditions for the corresponding ecosystem type. Individual S-Class departures are then combined into a single aggregate Ecosystem Condition score that represents the overall degree of departure from the ecosystem's expected reference condition.\nECO Score:\n100 - sum(Ci - Ri)\nWhere Ci = The current percentage of the 300m resolution landscape in successional/structural class i. And Ri = The historical reference percentage of the landscape in successional/structural class i.", - "distribution": [ - { - "@type": "dcat:Distribution", - "accessURL": "https://doi.org/10.5066/P13EXQGF", - "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.6a96d08b1ba49b45440e95de.xml", - "format": "XML", - "mediaType": "text/xml", - "title": "Original Metadata" - } - ], - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_6a96d08b1ba49b45440e95de", - "keyword": [ - "USGS:6a96d08b1ba49b45440e95de", - "biota", - "ecosystem monitoring", - "ecosystem restoration", - "environment", - "terrestrial ecosystems" - ], - "modified": "2026-09-15T00:00:00Z", - "publisher": { - "@type": "org:Organization", - "name": "U.S. Geological Survey" - }, - "spatial": "-114.0400, 36.9900, -109.0400, 42.0000", - "theme": [ - "geospatial" - ], - "title": "2024 geospatial Ecosystem Condition (ECO) Score layer for Utah, USA" - }, - "description": "This raster dataset provides estimated ecosystem condition scores, representing the difference between current conditions and reference/baseline conditions, for Utah, USA for the year 2024. The data are analogous to LANDFIRE's Vegetation Departure Scores (which are calculated using LANDFIRE Succession-Class raster data, and LANDFIRE Biophysical Settings raster data), but we used custom processing of the underlying LANDFIRE data to generate scores at higher resolution.\nLANDFIRE Succession Class (S-Class) maps at 30 m resolution were summarized within 300 m analysis cells. Each 300 m cell contains the proportional cover of seven vegetation classes: A (early development), B (mid-development closed), C (mid-development open), D (late-development open), E (late-development closed), UN (uncharacteristic native), and UE (uncharacteristic exotic). S-classes for each ecosystem type consider the type, cover, and height of vegetation, and whether the vegetation is characteristic of ecosystem type. The dominant LANDFIRE Biophysical Setting in each 300 m cell was used to identify reference-condition expectations. \nThe Ecosystem Condition score raster provides a single, integrated departure score ranging from 0 to 100, where larger values indicate greater departure from reference conditions. The score is based on the same ecological departure framework used by the LANDFIRE Vegetation Departure product and the Fire Regime Condition Class (FRCC) methodology.\nTo calculate the score, vegetation conditions within each 300 m grid cell are first summarized across seven LANDFIRE Succession Classes (S-Classes): A, B, C, D, E, UN, and UE. Current proportions of each S-Class are compared with the proportions expected under reference conditions for the corresponding ecosystem type. Individual S-Class departures are then combined into a single aggregate Ecosystem Condition score that represents the overall degree of departure from the ecosystem's expected reference condition.\nECO Score:\n100 - sum(Ci - Ri)\nWhere Ci = The current percentage of the 300m resolution landscape in successional/structural class i. And Ri = The historical reference percentage of the landscape in successional/structural class i.", - "distribution_titles": [ - "Digital Data", - "Original Metadata" - ], - "harvest_record": "https://catalog.data.gov/harvest_record/aca9470d-7b60-4b90-80e8-44c389e9d5dd", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/aca9470d-7b60-4b90-80e8-44c389e9d5dd/raw", - "has_download": true, - "has_spatial": true, - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_6a96d08b1ba49b45440e95de", - "keyword": [ - "USGS:6a96d08b1ba49b45440e95de", - "biota", - "ecosystem monitoring", - "ecosystem restoration", - "environment", - "terrestrial ecosystems" - ], - "last_harvested_date": "2026-09-24T00:12:22.942895", - "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": "2024-geospatial-ecosystem-condition-eco-score-layer-for-utah-usa", - "spatial_centroid": { - "lat": 38.994, - "lon": -112.04 - }, - "spatial_shape": { - "coordinates": [ - [ - [ - -114.04, - 36.99 - ], - [ - -114.04, - 42.0 - ], - [ - -109.04, - 42.0 - ], - [ - -109.04, - 36.99 - ], - [ - -114.04, - 36.99 - ] - ] - ], - "type": "Polygon" - }, - "theme": [ - "geospatial" - ], - "title": "2024 geospatial Ecosystem Condition (ECO) Score layer for Utah, USA", - "type": "dataset" - }, - { - "_score": 8.10714, - "_sort": [ - 1790208540856, - 8.10714, - 2, - "6cae55a6-1ac9-453a-9715-a3c3302922ac" - ], - "dcat": { - "accessLevel": "public", - "bureauCode": [ - "010:12" - ], - "contactPoint": { - "@type": "vcard:Contact", - "fn": "Jordan S. Read", - "hasEmail": "mailto:jread@usgs.gov" - }, - "description": "Climate change has been shown to influence lake temperatures globally. To better understand the diversity of lake responses to climate change and give managers tools to manage individual lakes, we modelled daily water temperature profiles for 10,774 lakes in Michigan, Minnesota and Wisconsin for contemporary (1979-2015) and future (2020-2040 and 2080-2100) time periods with climate models based on the Representative Concentration Pathway 8.5, the worst-case emission scenario. From simulated temperatures, we derived commonly used, ecologically relevant annual metrics of thermal conditions for each lake. We included all available supporting metadata including satellite and in-situ observations of water clarity, maximum observed lake depth, land-cover based estimates of surrounding canopy height and observed water temperature profiles (used here for validation). This unique dataset offers landscape-level insight into the future impact of climate change on lakes. This data set contains the following parameters: ice_duration_days, ice_on_date, ice_off_date, winter_dur_0-4, coef_var_30-60, coef_var_0-30, stratification_onset_yday, stratification_duration, sthermo_depth_mean, peak_temp, gdd_wtr_0c, gdd_wtr_5c, gdd_wtr_10c, bottom_temp_at_strat, schmidt_daily_annual_sum, mean_surf_jas, max_surf_jas, mean_bot_jas, max_bot_jas, mean_surf_jan, max_surf_jan, mean_bot_jan, max_bot_jan, mean_surf_feb, max_surf_feb, mean_bot_feb, max_bot_feb, mean_surf_mar, max_surf_mar, mean_bot_mar, max_bot_mar, mean_surf_apr, max_surf_apr, mean_bot_apr, max_bot_apr, mean_surf_may, max_surf_may, mean_bot_may, max_bot_may, mean_surf_jun, max_surf_jun, mean_bot_jun, max_bot_jun, mean_surf_jul, max_surf_jul, mean_bot_jul, max_bot_jul, mean_surf_aug, max_surf_aug, mean_bot_aug, max_bot_aug, mean_surf_sep, max_surf_sep, mean_bot_sep, max_bot_sep, mean_surf_oct, max_surf_oct, mean_bot_oct, max_bot_oct, mean_surf_nov, max_surf_nov, mean_bot_nov, max_bot_nov, mean_surf_dec, max_surf_dec, mean_bot_dec, max_bot_dec, which are defined below.", - "distribution": [ - { - "@type": "dcat:Distribution", - "accessURL": "https://doi.org/10.5066/F7DV1H10", - "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.57d9e887e4b090824ffb1098.xml", - "format": "XML", - "mediaType": "text/xml", - "title": "Original Metadata" - } - ], - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_57d9e887e4b090824ffb1098", - "keyword": [ - "IA", - "IL", - "IN", - "Illinois", - "Indiana", - "Iowa", - "MI", - "MN", - "Michigan", - "Minnesota", - "SD", - "South Dakota", - "US", - "USGS:57d9e887e4b090824ffb1098", - "United States", - "WI", - "Wisconsin", - "biota", - "climate change", - "environment", - "inlandWaters", - "modeling", - "reservoirs", - "temperate lakes", - "thermal profiles", - "water" - ], - "modified": "2026-09-17T00:00:00Z", - "publisher": { - "@type": "org:Organization", - "name": "U.S. Geological Survey" - }, - "spatial": "-96.8589114267623, 48.7289513243629, -83.0573307815185, 41.7553570685206", - "theme": [ - "geospatial" - ], - "title": "Thermal metrics: A large-scale database of modeled contemporary and future water temperature data for 10,774 Michigan, Minnesota and Wisconsin Lakes" - }, - "description": "Climate change has been shown to influence lake temperatures globally. To better understand the diversity of lake responses to climate change and give managers tools to manage individual lakes, we modelled daily water temperature profiles for 10,774 lakes in Michigan, Minnesota and Wisconsin for contemporary (1979-2015) and future (2020-2040 and 2080-2100) time periods with climate models based on the Representative Concentration Pathway 8.5, the worst-case emission scenario. From simulated temperatures, we derived commonly used, ecologically relevant annual metrics of thermal conditions for each lake. We included all available supporting metadata including satellite and in-situ observations of water clarity, maximum observed lake depth, land-cover based estimates of surrounding canopy height and observed water temperature profiles (used here for validation). This unique dataset offers landscape-level insight into the future impact of climate change on lakes. This data set contains the following parameters: ice_duration_days, ice_on_date, ice_off_date, winter_dur_0-4, coef_var_30-60, coef_var_0-30, stratification_onset_yday, stratification_duration, sthermo_depth_mean, peak_temp, gdd_wtr_0c, gdd_wtr_5c, gdd_wtr_10c, bottom_temp_at_strat, schmidt_daily_annual_sum, mean_surf_jas, max_surf_jas, mean_bot_jas, max_bot_jas, mean_surf_jan, max_surf_jan, mean_bot_jan, max_bot_jan, mean_surf_feb, max_surf_feb, mean_bot_feb, max_bot_feb, mean_surf_mar, max_surf_mar, mean_bot_mar, max_bot_mar, mean_surf_apr, max_surf_apr, mean_bot_apr, max_bot_apr, mean_surf_may, max_surf_may, mean_bot_may, max_bot_may, mean_surf_jun, max_surf_jun, mean_bot_jun, max_bot_jun, mean_surf_jul, max_surf_jul, mean_bot_jul, max_bot_jul, mean_surf_aug, max_surf_aug, mean_bot_aug, max_bot_aug, mean_surf_sep, max_surf_sep, mean_bot_sep, max_bot_sep, mean_surf_oct, max_surf_oct, mean_bot_oct, max_bot_oct, mean_surf_nov, max_surf_nov, mean_bot_nov, max_bot_nov, mean_surf_dec, max_surf_dec, mean_bot_dec, max_bot_dec, which are defined below.", - "distribution_titles": [ - "Digital Data", - "Original Metadata" - ], - "harvest_record": "https://catalog.data.gov/harvest_record/02b3a9d3-7b46-4655-8355-28c542440478", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/02b3a9d3-7b46-4655-8355-28c542440478/raw", - "has_download": true, - "has_spatial": true, - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_57d9e887e4b090824ffb1098", - "keyword": [ - "IA", - "IL", - "IN", - "Illinois", - "Indiana", - "Iowa", - "MI", - "MN", - "Michigan", - "Minnesota", - "SD", - "South Dakota", - "US", - "USGS:57d9e887e4b090824ffb1098", - "United States", - "WI", - "Wisconsin", - "biota", - "climate change", - "environment", - "inlandWaters", - "modeling", - "reservoirs", - "temperate lakes", - "thermal profiles", - "water" - ], - "last_harvested_date": "2026-09-24T00:09:00.856238", - "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": "thermal-metrics-a-large-scale-database-of-modeled-contemporary-and-future-water-temperatur", - "spatial_centroid": { - "lat": 45.939513622025984, - "lon": -91.33827916866478 - }, - "spatial_shape": { - "coordinates": [ - [ - [ - -96.8589114267623, - 48.7289513243629 - ], - [ - -96.8589114267623, - 41.7553570685206 - ], - [ - -83.0573307815185, - 41.7553570685206 - ], - [ - -83.0573307815185, - 48.7289513243629 - ], - [ - -96.8589114267623, - 48.7289513243629 - ] - ] - ], - "type": "Polygon" - }, - "theme": [ - "geospatial" - ], - "title": "Thermal metrics: A large-scale database of modeled contemporary and future water temperature data for 10,774 Michigan, Minnesota and Wisconsin Lakes", - "type": "dataset" - }, - { - "_score": 8.817127, - "_sort": [ - 1790208342798, - 8.817127, - 2, - "402468fa-0df4-412e-9eca-b7f2a0189236" - ], - "dcat": { - "accessLevel": "public", - "bureauCode": [ - "010:12" - ], - "contactPoint": { - "@type": "vcard:Contact", - "fn": "April Taylor", - "hasEmail": "mailto:casc-data@usgs.gov" - }, - "description": "THE CHICKASAW NATION HOSTED THIS RESEARCH SYMPOSIUM ON MARCH 22-24, 2022, HELD AT THE CHICKASAW RETREAT AND CONFERENCE CENTER IN SULPHUR, OK.\nAfter the Climate Workshop for The Chickasaw Nation in 2019, the Tribal managers discussed the need to include culture in conservation efforts and decided to seek a grant for culturally significant plants. This event was organized and led by the Chickasaw Nation and was funded by the U.S. Geological Survey through the South Central Climate Adaptation Science Center.\nThere were 106 attendees with 75 Native representatives from 21 different tribes. There were 11 student attendees. Attendees came from all across the United States including Maine, New York, Michigan, Montana, California, Alabama, and North Carolina. One of the speakers even presented via livestream from Hawaii.\nThe event brought tribes and researchers together on equal levels to learn about what they are doing related to plants and climate change and discuss collaboration opportunities. This dataset contains evaluation responses from participants who attended the research symposium. 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"Animals/Invertebrates", - "Animals/Vertebrates", - "Bioenergetics", - "Biomass", - "Biota", - "Calorimetry", - "Capelin", - "Coastal ecosystems", - "Conductivity", - "Cook Inlet", - "Environment", - "Euphausiids", - "Fish", - "Fisheries", - "Fishery technology", - "Food fishes", - "Food web", - "Forage fish", - "Gulf of Alaska", - "Inorganic Nutrients", - "Macrozooplankton", - "Marine ecosystems", - "Marine fishery resources", - "Oceans", - "Pacific Sand Lance", - "Pelagic habitat", - "Photosynthetically active radiation", - "Plankton", - "Salinity", - "Sandlance", - "Temperature", - "Turbidity", - "USGS:6a173389b66b0148116fbedb", - "Zooplankton" - ], - "last_harvested_date": "2026-09-24T00:04:59.067568", - "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", - 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The dataset has three comma separated values (.csv) file exported from a Microsoft Access relational database. The data consist of: 1) size and disease state of sea stars, 2) counts of sea stars, and 3) taxonomic classification of sea stars.", - "distribution": [ - { - "@type": "dcat:Distribution", - "accessURL": "https://doi.org/10.5066/F7513WCB", - "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.ASC486.xml", - "format": "XML", - "mediaType": "text/xml", - "title": "Original Metadata" - } - ], - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_ASC486", - "keyword": [ - "Alaska", - "Alaska Peninsula", - "Animals/Invertebrates", - "Aquatic ecosystems", - "Biospheric indicators", - "Biota", - "Community ecology", - "Echinoderms", - "Ecosystem monitoring", - "Environment", - "Gulf of Alaska", - "Intertidal environments", - "Intertidal zone", - "Katmai National Park and Preserve", - "Kenai Fjords National Park", - "Marine ecosystems", - "Marine invertebrates", - "Nearshore ecology", - "Prince William Sound", - "Sea star", - "USGS:ASC486" - ], - "modified": "2026-09-14T00:00:00Z", - "publisher": { - "@type": "org:Organization", - "name": "U.S. Geological Survey" - }, - "spatial": "-156.643, 57.938, -145.415, 61.122", - "theme": [ - "geospatial" - ], - "title": "Rocky Intertidal Sea Star Size, Count, and Disease Data from Prince William Sound, Katmai National Park and Preserve, and Kenai Fjords National Park" - }, - "description": "This is a child item of the USGS Data Release: https://doi.org/10.5066/F7513WCB.\n\t These data are part of the Gulf Watch Alaska (GWA) long-term monitoring program, nearshore monitoring component. 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