Timeline / Data.gov — Climate Datasets
changed Source changed
A new raw object was archived. Both versions are preserved. 3833 line(s) added, 4294 line(s) removed.
Evidence
| Source | Data.gov — Climate Datasets |
|---|---|
| Agency | Data.gov |
| URL | https://api.gsa.gov/technology/datagov/v4/search?q=climate&sort=last_harvested_date&per_page=100&api_key=${DATAGOV_API_KEY} |
| Observed by | Civic Memory, directly, on 2026-09-23T00:19:26+00:00 |
| Content type | application/json |
| Current object |
1c677946382b1d03a6d5d6422b1c901c917a9598e2d9fb37ff437257fa621f9b
download raw
metadata
|
| Previous object |
7480bdbf5fcb43b2260241ae47c57065b36bb672bfa005866809d928024366cb
download raw
metadata
|
What changed derived
This diff is not evidence. It was produced by
civic-memory.diff_engine 1.1.0 at
2026-09-23T00:19:26+00:00 by normalizing the two archived objects above. The
objects are authoritative; this reading of them can be regenerated or deleted
without loss. 3833 line(s) added, 4294 line(s) removed.
--- previous +++ current @@ -1,3000 +1,2946 @@ { - "after": "WzE3ODkwODA2MjUxNTksMTcuMjA2ODEsNCwiZTgzNWJmZTEtNjI1NC00OGQ2LWIzNDctZGZkZTZiNzM4Y2I0Il0=", + "after": "WzE3OTAxMjIzMTUyNDMsMTEuMDUxMDkxLDEsImM3NGY1OTQ3LWI2OTQtNDEzMS04MDdiLTM3YmQxYjEyOWYxMCJd", "results": [ { - "_score": 8.184319, + "_score": 14.239145, "_sort": [ - 1789687939394, - 8.184319, - 0, - "03ab7385-aa1d-4350-ac6d-2ada50e233ef" + 1790122770073, + 14.239145, + 1, + "2bbdd079-e042-41f2-8f5d-71e5a055e550" ], "dcat": { + "@type": "dcat:Dataset", "accessLevel": "public", "bureauCode": [ - "010:12" + "026:00" ], "contactPoint": { "@type": "vcard:Contact", - "fn": "Kenny Eng", - "hasEmail": "mailto:keng@usgs.gov" - }, - "description": "This metadata record describes the following eight attributes: (1) the U.S. Geological Survey streamgage identification number, (2) aggregated level 2 ecoregion, (3) hydrologic metric abbreviation, (4) direct-human modification classification of watershed, (5) predicted hydrologic metric values for 1950 to 2014, (6) predicted hydrologic metric values for 1980 to 2014, (7) observed hydrologic metric values for 1980 to 2014, and (8) the direction of streamflow alteration (i.e., inflated, diminished, or indeterminant). Twelve hyrdologic metrics were calculated: low- and high-flow magnitude (LF_MAG(cfs/square km) and HF_MAG(cfs/square km)), low- and high-flow variability (LF_VAR(dimensionless) and HF_VAR(dimensionless)), low- and high-flow frequency (LF_FRE(number of pulses) and HF_FRE(number of pulses)), low- and high-flow duration (LF_DUR(days) and HF_DUR(days)), skewness (OT_SKW(dimensionless)), number of daily rises (OT_RIS(dimensionless)), low- and high-flow seasonality (LF_SEA(dimensionless) and HF_SEA(dimensionless)). The low- and high-flow magnitudes were calculated from the 1st and 99th percentile non-exceedence streamflows divided by the drainage area, respectively. The low- and high-flow variabilities were calculated from the coefficient of variation of the annual minimum and maximum streamflows, respectively. The low- and high-flow frequencies were calculated as the mean of the annual-time series of the number of pulses below the 10th and above the 90th percentile values, respectively. The low- and high-flow durations were calculated from the length of time (in days) that the streamflow was below the 10th percentile or above the 90th percentile, respectively. The skewness values were calculated as the third moment of the daily streamflow values. The number of daily rises values were calculated by the ratio of the number of days where the daily streamflow was greater than the previous day divided by the total number of days for the period. The low- and high-flow seasonality values were calculated based on frequency of occurrence in different seasons (for more details, please see Eng, K., Wolock, D.M., and Dettinger, M.D., 2016, Sensitivity of intermittent streams to climate variations in the USA: River Research and Applications, v. 32, no. 5, p. 885-895. [Also available at https://doi.org/10.1002/rra.2939.]). The observed daily-streamflow values are from U.S. Geological Survey National Water Information System (http://dx.doi.org/10.5066/F7P55KJN), and the estimated values were calculated by random forest statistical models. For LF_SEA and HF_SEA, the observed hydrologic metric is often subtracted by the predicted hydrologic metric. For the remaining hydrologic metrics, the observed hydrologic metric is often divided by the predicted hydrologic metric The data are in a tab-delimited text format.", + "fn": "Earthdata Forum", + "hasEmail": "mailto:earthdata-support@nasa.gov" + }, + "description": "The GPM Ground Validation (GV) Environment Canada (EC) Visibility Sensor FD12P C3VP dataset consists of visibility and precipitation data collected at the Environment Canada Canadian Climate station at the Centre for Atmospheric Research Experiments (CARE) site during the Canadian CloudSat/CALIPSO Validation Project (C3VP) field campaign. The campaign took place in southern Canada in support of multiple science missions, including the NASA GPM mission, in order to improve the modeling and remote sensing of winter precipitation. The GPM GV Visibility Sensor FD12P C3VP data are available from October 4, 2006 through March 31, 2007 in a Microsoft Excel comma-separated variable spreadsheet.", "distribution": [ { "@type": "dcat:Distribution", - "accessURL": "https://doi.org/10.5066/P9ULGVLI", - "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.5b8e87f1e4b0702d0e7ebc0a.xml", - "format": "XML", + "conformsTo": "http://www.isotc211.org/2005/gmi", + "description": "The metadata's original source.", + "downloadURL": "https://cmr.earthdata.nasa.gov/search/concepts/C1995871445-GHRC_DAAC.iso19115", + "format": "ISO", "mediaType": "text/xml", "title": "Original Metadata" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://ghrc.earthdata.nasa.gov/browseui/#pub/gpmvisecc3vp__1/docs/gpmvisecc3vp_dataset.pdf", + "format": "PDF", + "mediaType": "application/pdf" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://ghrc.nsstc.nasa.gov/home/about-ghrc/citing-ghrc-daac-data", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://radarmet.atmos.colostate.edu/c3vp/petersenetal_C3VP.pdf", + "format": "PDF", + "mediaType": "application/pdf" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://search.earthdata.nasa.gov/search/granules?p=C1995871445-GHRC_DAAC", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://www.manualslib.com/manual/538824/Vaisala-Fd12p.html", + "format": "HTML", + "mediaType": "text/html" } ], - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_5b8e87f1e4b0702d0e7ebc0a", - "keyword": [ - "USGS:5b8e87f1e4b0702d0e7ebc0a", - "streamflow" - ], - "modified": "2026-09-14T00:00:00Z", + "identifier": "10.5067/GPMGV/C3VP/VISSENSOR/DATA101", + "keyword": [ + "earth-science-air-quality-atmosphere-visibility", + "earth-science-precipitation-atmosphere-liquid-precipitation" + ], + "license": "https://www.usa.gov/government-works", + "modified": "2026-09-22", + "programCode": [ + "026:000" + ], "publisher": { "@type": "org:Organization", - "name": "U.S. Geological Survey" - }, - "spatial": "-125.33203124869, 24.566710428926, -66.09375000106, 49.410688528111", - "theme": [ - "geospatial" - ], - "title": "Hydrologic metric changes across the conterminous United States" - }, - "description": "This metadata record describes the following eight attributes: (1) the U.S. Geological Survey streamgage identification number, (2) aggregated level 2 ecoregion, (3) hydrologic metric abbreviation, (4) direct-human modification classification of watershed, (5) predicted hydrologic metric values for 1950 to 2014, (6) predicted hydrologic metric values for 1980 to 2014, (7) observed hydrologic metric values for 1980 to 2014, and (8) the direction of streamflow alteration (i.e., inflated, diminished, or indeterminant). Twelve hyrdologic metrics were calculated: low- and high-flow magnitude (LF_MAG(cfs/square km) and HF_MAG(cfs/square km)), low- and high-flow variability (LF_VAR(dimensionless) and HF_VAR(dimensionless)), low- and high-flow frequency (LF_FRE(number of pulses) and HF_FRE(number of pulses)), low- and high-flow duration (LF_DUR(days) and HF_DUR(days)), skewness (OT_SKW(dimensionless)), number of daily rises (OT_RIS(dimensionless)), low- and high-flow seasonality (LF_SEA(dimensionless) and HF_SEA(dimensionless)). The low- and high-flow magnitudes were calculated from the 1st and 99th percentile non-exceedence streamflows divided by the drainage area, respectively. The low- and high-flow variabilities were calculated from the coefficient of variation of the annual minimum and maximum streamflows, respectively. The low- and high-flow frequencies were calculated as the mean of the annual-time series of the number of pulses below the 10th and above the 90th percentile values, respectively. The low- and high-flow durations were calculated from the length of time (in days) that the streamflow was below the 10th percentile or above the 90th percentile, respectively. The skewness values were calculated as the third moment of the daily streamflow values. The number of daily rises values were calculated by the ratio of the number of days where the daily streamflow was greater than the previous day divided by the total number of days for the period. The low- and high-flow seasonality values were calculated based on frequency of occurrence in different seasons (for more details, please see Eng, K., Wolock, D.M., and Dettinger, M.D., 2016, Sensitivity of intermittent streams to climate variations in the USA: River Research and Applications, v. 32, no. 5, p. 885-895. [Also available at https://doi.org/10.1002/rra.2939.]). The observed daily-streamflow values are from U.S. Geological Survey National Water Information System (http://dx.doi.org/10.5066/F7P55KJN), and the estimated values were calculated by random forest statistical models. For LF_SEA and HF_SEA, the observed hydrologic metric is often subtracted by the predicted hydrologic metric. For the remaining hydrologic metrics, the observed hydrologic metric is often divided by the predicted hydrologic metric The data are in a tab-delimited text format.", + "name": "NASA/MSFC/GHRC" + }, + "spatial": "[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -79.791, \"NorthBoundingCoordinate\": 44.242, \"EastBoundingCoordinate\": -79.772, \"SouthBoundingCoordinate\": 44.222}]]", + "temporal": "2006-10-04/2007-03-31", + "theme": [ + "Earth Science" + ], + "title": "GPM Ground Validation Environment Canada (EC) Visibility Sensor FD12P C3VP V1" + }, + "description": "The GPM Ground Validation (GV) Environment Canada (EC) Visibility Sensor FD12P C3VP dataset consists of visibility and precipitation data collected at the Environment Canada Canadian Climate station at the Centre for Atmospheric Research Experiments (CARE) site during the Canadian CloudSat/CALIPSO Validation Project (C3VP) field campaign. The campaign took place in southern Canada in support of multiple science missions, including the NASA GPM mission, in order to improve the modeling and remote sensing of winter precipitation. The GPM GV Visibility Sensor FD12P C3VP data are available from October 4, 2006 through March 31, 2007 in a Microsoft Excel comma-separated variable spreadsheet.", "distribution_titles": [ - "Digital Data", "Original Metadata" ], - "harvest_record": "https://catalog.data.gov/harvest_record/38754b37-56c5-4f90-a18f-0049c4a0d19b", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/38754b37-56c5-4f90-a18f-0049c4a0d19b/raw", + "harvest_record": "https://catalog.data.gov/harvest_record/94dbc271-66f3-496f-90f7-539c9652b67e", + "harvest_record_raw": "https://catalog.data.gov/harvest_record/94dbc271-66f3-496f-90f7-539c9652b67e/raw", "has_download": true, "has_spatial": true, - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_5b8e87f1e4b0702d0e7ebc0a", - "keyword": [ - "USGS:5b8e87f1e4b0702d0e7ebc0a", - "streamflow" - ], - "last_harvested_date": "2026-09-17T23:32:19.394710", + "identifier": "10.5067/GPMGV/C3VP/VISSENSOR/DATA101", + "keyword": [ + "earth-science-air-quality-atmosphere-visibility", + "earth-science-precipitation-atmosphere-liquid-precipitation" + ], + "last_harvested_date": "2026-09-23T00:19:30.073523", "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", + "id": "f4ca4614-8901-409b-8553-2e994ad10023", + "logo": "https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png", + "name": "National Aeronautics and Space Administration", "organization_type": "Federal Government", - "slug": "doi" + "slug": "nasa" }, "parent_identifier": null, - "popularity": 0, - "publisher": "U.S. Geological Survey", - "slug": "hydrologic-metric-changes-across-the-conterminous-united-states-3a62a", - "spatial_centroid": { - "lat": 34.5043016686, - "lon": -101.63671874963799 - }, - "spatial_shape": { - "coordinates": [ - [ - [ - -125.33203124869, - 24.566710428926 - ], - [ - -125.33203124869, - 49.410688528111 - ], - [ - -66.09375000106, - 49.410688528111 - ], - [ - -66.09375000106, - 24.566710428926 - ], - [ - -125.33203124869, - 24.566710428926 - ] - ] - ], - "type": "Polygon" - }, - "theme": [ - "geospatial" - ], - "title": "Hydrologic metric changes across the conterminous United States", + "popularity": 1, + "publisher": "NASA/MSFC/GHRC", + "slug": "gpm-ground-validation-environment-canada-ec-visibility-sensor-fd12p-c3vp-v1", + "spatial_centroid": null, + "spatial_shape": null, + "theme": [ + "Earth Science" + ], + "title": "GPM Ground Validation Environment Canada (EC) Visibility Sensor FD12P C3VP V1", "type": "dataset" }, { - "_score": 38.496094, + "_score": 19.831852, "_sort": [ - 1789687665593, - 38.496094, + 1790122727629, + 19.831852, 1, - "b46cca48-f5fe-4fc1-834d-8a9cfcd364e1" + "e1f92163-622e-43e9-a5bb-664a419a4589" ], "dcat": { + "@type": "dcat:Dataset", "accessLevel": "public", "bureauCode": [ - "010:12" + "026:00" ], "contactPoint": { "@type": "vcard:Contact", - "fn": "Michael E. Wieczorek", - "hasEmail": "mailto:mewieczo@usgs.gov" - }, - "description": "This tabular data set represents 30 year (1971 - 2000) mean annual precipitation in millimeters compiled for two spatial components of the NHDPlus version 2 data suite (NHDPlusv2) for the conterminous United States; 1) individual reach catchments and 2) reach catchments accumulated upstream through the river network. This dataset can be linked to the NHDPlus version 2 data suite by the unique identifier COMID. The source data for 30 year (1971 - 2000) mean annual precipitation data was produced by the PRISM Group at Oregon State University (PRISM, 2008). Units are millimeters. Reach catchment information characterizes data at the local scale. Reach catchments accumulated upstream through the river network characterizes cumulative upstream conditions. Network-accumulated values are computed using two methods, 1) divergence-routed and 2) total cumulative drainage area. Both approaches use a modified routing database to navigate the NHDPlus reach network to aggregate (accumulate) the metrics derived from the reach catchment scale. (Schwarz and Wieczorek, 2018).", + "fn": "Earthdata Forum", + "hasEmail": "mailto:earthdata-support@nasa.gov" + }, + "description": "This dataset provides gridded estimates of soil CO2 flux (g C m-2 d-1) for the winter non-growing season (NGS) across pan-Arctic and Boreal permafrost regions (>49 Deg N), at 25 km spatial resolution. The data are the daily average flux over a monthly period for two climate periods: the baseline climate period represents 2003-2018 and the future climate scenarios period represents 2018-2100 under Representative Concentration Pathways (RCP) 4.5 and 8.5. The data were produced by applying a Boosted Regression Tree machine learning approach to create gridded estimates of emissions based on in situ observations of NGS fluxes provided in a related dataset. The resulting monthly average flux data records can be used to calculate annual NGS soil CO2 flux budgets from 2003-2100.", "distribution": [ { "@type": "dcat:Distribution", - "accessURL": "https://doi.org/10.5066/F7765D7V", - "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.573b70a7e4b0dae0d5e3ae85.xml", - "format": "XML", + "conformsTo": "http://www.isotc211.org/2005/gmi", + "description": "The metadata's original source.", + "downloadURL": "https://cmr.earthdata.nasa.gov/search/concepts/C2143812328-ORNL_CLOUD.iso19115", + "format": "ISO", "mediaType": "text/xml", "title": "Original Metadata" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://above.nasa.gov", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://daac.ornl.gov/ABOVE/guides/Soil_Carbon_Flux_Maps_Fig1.png", + "format": "PNG", + "mediaType": "image/png" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://data.ornldaac.earthdata.nasa.gov/protected/bundle/Soil_Carbon_Flux_Maps_1683.zip", + "format": "ZIP", + "mediaType": "application/zip" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://data.ornldaac.earthdata.nasa.gov/public/above/Soil_Carbon_Flux_Maps/comp/Soil_Carbon_Flux_Maps.pdf", + "format": "PDF", + "mediaType": "application/pdf" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://doi.org/10.3334/ORNLDAAC/1683", + "format": "HTML", + "mediaType": "text/html" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://opendap.earthdata.nasa.gov/", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://search.earthdata.nasa.gov/search/granules?p=C2143812328-ORNL_CLOUD", + "format": "BIN", + "mediaType": "application/octet-stream" } ], - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_573b70a7e4b0dae0d5e3ae85", - "keyword": [ - "Catchment", - "Climate", - "Inlandwaters", - "NAWQA", - "NHDPlus", - "PRISM", - "SPARROW", - "USGS:573b70a7e4b0dae0d5e3ae85", - "mean annual precipitation" - ], - "modified": "2026-08-27T00:00:00Z", + "identifier": "10.3334/ORNLDAAC/1683", + "keyword": [ + "earth-science-atmospheric-chemistry-atmosphere-carbon-and-hydrocarbon-compounds", + "earth-science-frozen-ground-land-surface-permafrost", + "earth-science-soils-land-surface-carbon", + "earth-science-soils-land-surface-soil-respiration" + ], + "license": "https://www.usa.gov/government-works", + "modified": "2026-09-22", + "programCode": [ + "026:000" + ], "publisher": { "@type": "org:Organization", - "name": "U.S. Geological Survey" - }, - "spatial": "-127.910792, 23.243486, -65.327751, 51.657387", - "theme": [ - "geospatial" - ], - "title": "Select Climate Attributes: 30 Year (1971 - 2000) Mean Annual Precipitation" - }, - "description": "This tabular data set represents 30 year (1971 - 2000) mean annual precipitation in millimeters compiled for two spatial components of the NHDPlus version 2 data suite (NHDPlusv2) for the conterminous United States; 1) individual reach catchments and 2) reach catchments accumulated upstream through the river network. This dataset can be linked to the NHDPlus version 2 data suite by the unique identifier COMID. The source data for 30 year (1971 - 2000) mean annual precipitation data was produced by the PRISM Group at Oregon State University (PRISM, 2008). Units are millimeters. Reach catchment information characterizes data at the local scale. Reach catchments accumulated upstream through the river network characterizes cumulative upstream conditions. Network-accumulated values are computed using two methods, 1) divergence-routed and 2) total cumulative drainage area. Both approaches use a modified routing database to navigate the NHDPlus reach network to aggregate (accumulate) the metrics derived from the reach catchment scale. (Schwarz and Wieczorek, 2018).", + "name": "ORNL_DAAC" + }, + "spatial": "[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -180.0, \"NorthBoundingCoordinate\": 89.979, \"EastBoundingCoordinate\": 179.896, \"SouthBoundingCoordinate\": -84.6916}]]", + "temporal": "1993-01-01/2100-11-30", + "theme": [ + "Earth Science" + ], + "title": "Gridded Winter Soil CO2 Flux Estimates for pan-Arctic and Boreal Regions, 2003-2100" + }, + "description": "This dataset provides gridded estimates of soil CO2 flux (g C m-2 d-1) for the winter non-growing season (NGS) across pan-Arctic and Boreal permafrost regions (>49 Deg N), at 25 km spatial resolution. The data are the daily average flux over a monthly period for two climate periods: the baseline climate period represents 2003-2018 and the future climate scenarios period represents 2018-2100 under Representative Concentration Pathways (RCP) 4.5 and 8.5. The data were produced by applying a Boosted Regression Tree machine learning approach to create gridded estimates of emissions based on in situ observations of NGS fluxes provided in a related dataset. The resulting monthly average flux data records can be used to calculate annual NGS soil CO2 flux budgets from 2003-2100.", "distribution_titles": [ - "Digital Data", "Original Metadata" ], - "harvest_record": "https://catalog.data.gov/harvest_record/10a20f3a-fe46-44c8-91aa-375da73ebd4d", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/10a20f3a-fe46-44c8-91aa-375da73ebd4d/raw", + "harvest_record": "https://catalog.data.gov/harvest_record/5ed8598b-70c2-4e85-abff-88258138a756", + "harvest_record_raw": "https://catalog.data.gov/harvest_record/5ed8598b-70c2-4e85-abff-88258138a756/raw", "has_download": true, "has_spatial": true, - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_573b70a7e4b0dae0d5e3ae85", - "keyword": [ - "Catchment", - "Climate", - "Inlandwaters", - "NAWQA", - "NHDPlus", - "PRISM", - "SPARROW", - "USGS:573b70a7e4b0dae0d5e3ae85", - "mean annual precipitation" - ], - "last_harvested_date": "2026-09-17T23:27:45.593906", + "identifier": "10.3334/ORNLDAAC/1683", + "keyword": [ + "earth-science-atmospheric-chemistry-atmosphere-carbon-and-hydrocarbon-compounds", + "earth-science-frozen-ground-land-surface-permafrost", + "earth-science-soils-land-surface-carbon", + "earth-science-soils-land-surface-soil-respiration" + ], + "last_harvested_date": "2026-09-23T00:18:47.629389", "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", + "id": "f4ca4614-8901-409b-8553-2e994ad10023", + "logo": "https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png", + "name": "National Aeronautics and Space Administration", "organization_type": "Federal Government", - "slug": "doi" + "slug": "nasa" }, "parent_identifier": null, "popularity": 1, - "publisher": "U.S. Geological Survey", - "slug": "attributes-for-nhdplus-version-2-1-catchments-and-modified-routing-of-upstream-watersheds-", - "spatial_centroid": { - "lat": 34.6090464, - "lon": -102.8775756 - }, - "spatial_shape": { - "coordinates": [ - [ - [ - -127.910792, - 23.243486 - ], - [ - -127.910792, - 51.657387 - ], - [ - -65.327751, - 51.657387 - ], - [ - -65.327751, - 23.243486 - ], - [ - -127.910792, - 23.243486 - ] - ] - ], - "type": "Polygon" - }, - "theme": [ - "geospatial" - ], - "title": "Select Climate Attributes: 30 Year (1971 - 2000) Mean Annual Precipitation", + "publisher": "ORNL_DAAC", + "slug": "gridded-winter-soil-co2-flux-estimates-for-pan-arctic-and-boreal-regions-2003-2100", + "spatial_centroid": null, + "spatial_shape": null, + "theme": [ + "Earth Science" + ], + "title": "Gridded Winter Soil CO2 Flux Estimates for pan-Arctic and Boreal Regions, 2003-2100", "type": "dataset" }, { - "_score": 8.165314, + "_score": 30.583317, "_sort": [ - 1789606216655, - 8.165314, - 3, - "6fb3691a-55bc-462e-82ed-7db02769e05c" + 1790122723239, + 30.583317, + 1, + "451d38a9-2695-4448-9567-faf5f4d04cff" ], "dcat": { + "@type": "dcat:Dataset", "accessLevel": "public", "bureauCode": [ - "010:12" + "026:00" ], "contactPoint": { "@type": "vcard:Contact", - "fn": "Michael E. Wieczorek", - "hasEmail": "mailto:mewieczo@usgs.gov" - }, - "description": "This data set represents the area of Hydrologic Landscape Regions (HLR) compiled for every catchment \nof NHDPlus for the conterminous United States. The source data set is a 100-meter version of Hydrologic \nLandscape Regions of the United States (Wolock, 2003). HLR groups watersheds on the basis of similarities \nin land-surface form, geologic texture, and climate characteristics.\n\t\t\nThe NHDPlus Version 1.1 is an integrated suite of application-ready geospatial datasets that incorporates \nmany of the best features of the National Hydrography Dataset (NHD) and the National Elevation Dataset \n(NED). The NHDPlus includes a stream network (based on the 1:100,00-scale NHD), improved networking, \nnaming, and value-added attributes (VAAs). NHDPlus also includes elevation-derived catchments \n(drainage areas) produced using a drainage enforcement technique first widely used in New England, \nand thus referred to as \"the New England Method.\" This technique involves \"burning in\" the 1:100,000-scale \nNHD and when available building \"walls\" using the National Watershed Boundary Dataset (WBD). The \nresulting modified digital elevation model (HydroDEM) is used to produce hydrologic derivatives that agree \nwith the NHD and WBD. Over the past two years, an interdisciplinary team from the U.S. Geological Survey \n(USGS), and the U.S. Environmental Protection Agency (USEPA), and contractors, found that this method \nproduces the best quality NHD catchments using an automated process (USEPA, 2007). The NHDPlus \ndataset is organized by 18 Production Units that cover the conterminous United States.\n\t\t\nThe NHDPlus version 1.1 data are grouped by the U.S. Geologic Survey's Major River Basins (MRBs, \nCrawford and others, 2006). MRB1, covering the New England and Mid-Atlantic River basins, contains \nNHDPlus Production Units 1 and 2. MRB2, covering the South Atlantic-Gulf and Tennessee River basins, \ncontains NHDPlus Production Units 3 and 6. MRB3, covering the Great Lakes, Ohio, Upper Mississippi, \nand Souris-Red-Rainy River basins, contains NHDPlus Production Units 4, 5, 7 and 9. MRB4, covering \nthe Missouri River basins, contains NHDPlus Production Units 10-lower and 10-upper. MRB5, covering \nthe Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins, contains NHDPlus Production \nUnits 8, 11 and 12. MRB6, covering the Rio Grande, Colorado and Great Basin River basins, contains \nNHDPlus Production Units 13, 14, 15 and 16. MRB7, covering the Pacific Northwest River basins, \ncontains NHDPlus Production Unit 17. MRB8, covering California River basins, contains NHDPlus \nProduction Unit 18.", - "distribution": [ - { - "@type": "dcat:Distribution", - "accessURL": "https://doi.org/10.5066/P9142BM0", - "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.93b2f75c-33bc-4cae-b48e-41b6f85d2e39.xml", - "format": "XML", - "mediaType": "text/xml", - "title": "Original Metadata" - } - ], - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_93b2f75c-33bc-4cae-b48e-41b6f85d2e39", - "keyword": [ - "CALI", - "COGB", - "California", - "Catchment", - "Conterminous United States", - "GLMR", - "Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy", - "Hydrologic landscape regions", - "Inlandwaters", - "LMTG", - "Lower Mississippi, Arkansas-White-Red, and Texas-Gulf", - "MORI", - "MRB", - "MRB1", - "MRB2", - "MRB3", - "MRB4", - "MRB5", - "MRB6", - "MRB7", - "MRB8", - "Major River Basin", - "Missouri", - "NAWQA", - "NEMA", - "NHDPlus", - "New England and Mid-Atlantic", - "PANW", - "Pacific Northwest", - "Rio Grande, Colorado, and Great Basin", - "SAGT", - "SPARROW", - "South Atlantic-Gulf and Tennessee", - "USGS:93b2f75c-33bc-4cae-b48e-41b6f85d2e39", - "environment", - "geoscientificInformation", - "inlandWaters" - ], - "modified": "2020-11-17T00:00:00Z", + "fn": "Planetary Data System", + "hasEmail": "mailto:pds-operator@jpl.nasa.gov" + }, + "description": "Unknown", + "identifier": "urn:nasa:pds:context_pds3:data_set:data_set.mro-m-mcs-5-ddr-v1.0;urn:nasa:pds:context_pds3:data_set:data_set.mro-m-mcs-5-ddr-v1.0::1.0", + "keyword": [ + "__" + ], + "license": "https://www.usa.gov/government-works", + "modified": "2026-09-22", + "programCode": [ + "026:000" + ], "publisher": { "@type": "org:Organization", - "name": "U.S. Geological Survey" - }, - "spatial": "-127.910792, 23.243486, -65.327751, 51.657387", - "theme": [ - "geospatial" - ], - "title": "Attributes for NHDPlus Catchments (Version 1.1) for the Conterminous United States: Hydrologic Landscape Regions" - }, - "description": "This data set represents the area of Hydrologic Landscape Regions (HLR) compiled for every catchment \nof NHDPlus for the conterminous United States. The source data set is a 100-meter version of Hydrologic \nLandscape Regions of the United States (Wolock, 2003). HLR groups watersheds on the basis of similarities \nin land-surface form, geologic texture, and climate characteristics.\n\t\t\nThe NHDPlus Version 1.1 is an integrated suite of application-ready geospatial datasets that incorporates \nmany of the best features of the National Hydrography Dataset (NHD) and the National Elevation Dataset \n(NED). The NHDPlus includes a stream network (based on the 1:100,00-scale NHD), improved networking, \nnaming, and value-added attributes (VAAs). NHDPlus also includes elevation-derived catchments \n(drainage areas) produced using a drainage enforcement technique first widely used in New England, \nand thus referred to as \"the New England Method.\" This technique involves \"burning in\" the 1:100,000-scale \nNHD and when available building \"walls\" using the National Watershed Boundary Dataset (WBD). The \nresulting modified digital elevation model (HydroDEM) is used to produce hydrologic derivatives that agree \nwith the NHD and WBD. Over the past two years, an interdisciplinary team from the U.S. Geological Survey \n(USGS), and the U.S. Environmental Protection Agency (USEPA), and contractors, found that this method \nproduces the best quality NHD catchments using an automated process (USEPA, 2007). The NHDPlus \ndataset is organized by 18 Production Units that cover the conterminous United States.\n\t\t\nThe NHDPlus version 1.1 data are grouped by the U.S. Geologic Survey's Major River Basins (MRBs, \nCrawford and others, 2006). MRB1, covering the New England and Mid-Atlantic River basins, contains \nNHDPlus Production Units 1 and 2. MRB2, covering the South Atlantic-Gulf and Tennessee River basins, \ncontains NHDPlus Production Units 3 and 6. MRB3, covering the Great Lakes, Ohio, Upper Mississippi, \nand Souris-Red-Rainy River basins, contains NHDPlus Production Units 4, 5, 7 and 9. MRB4, covering \nthe Missouri River basins, contains NHDPlus Production Units 10-lower and 10-upper. MRB5, covering \nthe Lower Mississippi, Arkansas-White-Red, and Texas-Gulf River basins, contains NHDPlus Production \nUnits 8, 11 and 12. MRB6, covering the Rio Grande, Colorado and Great Basin River basins, contains \nNHDPlus Production Units 13, 14, 15 and 16. MRB7, covering the Pacific Northwest River basins, \ncontains NHDPlus Production Unit 17. MRB8, covering California River basins, contains NHDPlus \nProduction Unit 18.", - "distribution_titles": [ - "Digital Data", - "Original Metadata" - ], - "harvest_record": "https://catalog.data.gov/harvest_record/86e57537-d748-4d55-be87-50f70428f7bf", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/86e57537-d748-4d55-be87-50f70428f7bf/raw", - "has_download": true, - "has_spatial": true, - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_93b2f75c-33bc-4cae-b48e-41b6f85d2e39", - "keyword": [ - "CALI", - "COGB", - "California", - "Catchment", - "Conterminous United States", - "GLMR", - "Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy", - "Hydrologic landscape regions", - "Inlandwaters", - "LMTG", - "Lower Mississippi, Arkansas-White-Red, and Texas-Gulf", - "MORI", - "MRB", - "MRB1", - "MRB2", - "MRB3", - "MRB4", - "MRB5", - "MRB6", - "MRB7", - "MRB8", - "Major River Basin", - "Missouri", - "NAWQA", - "NEMA", - "NHDPlus", - "New England and Mid-Atlantic", - "PANW", - "Pacific Northwest", - "Rio Grande, Colorado, and Great Basin", - "SAGT", - "SPARROW", - "South Atlantic-Gulf and Tennessee", - "USGS:93b2f75c-33bc-4cae-b48e-41b6f85d2e39", - "environment", - "geoscientificInformation", - "inlandWaters" - ], - "last_harvested_date": "2026-09-17T00:50:16.655685", + "name": "Planetary Atmospheres" + }, + "theme": [ + "Planetary Science" + ], + "title": "MRO MARS CLIMATE SOUNDER LEVEL 5 DDR V1.0" + }, + "description": "Unknown", + "distribution_titles": [], + "harvest_record": "https://catalog.data.gov/harvest_record/f9a5a381-0652-4087-8ea9-96d7621f35a9", + "harvest_record_raw": "https://catalog.data.gov/harvest_record/f9a5a381-0652-4087-8ea9-96d7621f35a9/raw", + "has_download": false, + "has_spatial": false, + "identifier": "urn:nasa:pds:context_pds3:data_set:data_set.mro-m-mcs-5-ddr-v1.0;urn:nasa:pds:context_pds3:data_set:data_set.mro-m-mcs-5-ddr-v1.0::1.0", + "keyword": [ + "__" + ], + "last_harvested_date": "2026-09-23T00:18:43.239278", "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", + "id": "f4ca4614-8901-409b-8553-2e994ad10023", + "logo": "https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png", + "name": "National Aeronautics and Space Administration", "organization_type": "Federal Government", - "slug": "doi" + "slug": "nasa" }, "parent_identifier": null, - "popularity": 3, - "publisher": "U.S. Geological Survey", - "slug": "attributes-for-nhdplus-catchments-version-1-1-for-the-conterminous-united-states-hydrologi", - "spatial_centroid": { - "lat": 34.6090464, - "lon": -102.8775756 - }, - "spatial_shape": { - "coordinates": [ - [ - [ - -127.910792, - 23.243486 - ], - [ - -127.910792, - 51.657387 - ], - [ - -65.327751, - 51.657387 - ], - [ - -65.327751, - 23.243486 - ], - [ - -127.910792, - 23.243486 - ] - ] - ], - "type": "Polygon" - }, - "theme": [ - "geospatial" - ], - "title": "Attributes for NHDPlus Catchments (Version 1.1) for the Conterminous United States: Hydrologic Landscape Regions", + "popularity": 1, + "publisher": "Planetary Atmospheres", + "slug": "mro-mars-climate-sounder-level-5-ddr-v1-0-21a2a", + "spatial_centroid": null, + "spatial_shape": null, + "theme": [ + "Planetary Science" + ], + "title": "MRO MARS CLIMATE SOUNDER LEVEL 5 DDR V1.0", "type": "dataset" }, { - "_score": 19.094769, + "_score": 11.625898, "_sort": [ - 1789605581640, - 19.094769, + 1790122669646, + 11.625898, 1, - "e2714ff8-adf8-4a22-a8eb-601f30c5f482" + "add6a17b-671f-46db-b02c-d31535d917b5" ], "dcat": { + "@type": "dcat:Dataset", "accessLevel": "public", "bureauCode": [ - "010:12" + "026:00" ], "contactPoint": { "@type": "vcard:Contact", - "fn": "Virginia and West Virginia Water Science Center", - "hasEmail": "mailto:dlmoyer@usgs.gov" - }, - "description": "1D transient numerical simulations with a modified version of the SUTRA model \n(preliminary code) that accounts for variably-saturated freeze-thaw dynamics \n(e.g. McKenzie and Voss, 2013) to predict annual alluvial aquifer temperature \ndynamics using coupled fluid and heat transport physics. The model simulations \nwere run with a modified version of SUTRA_ICE (unreleased) that accomadates \na time-variable sinusiodal upper temperature boundary. This data release also \nincludes the source code and Argus One GUI files used to build the models, \nthough this proprietary software is not needed to run the models as described \nin the upper-level \"readme\" file.", + "fn": "Earthdata Forum", + "hasEmail": "mailto:earthdata-support@nasa.gov" + }, + "description": "The ISCCP_B3_NAT data is the International Satellite Cloud Climatology Project (ISCCP) Stage B3 Reduced Radiances in Native Format data product. This is the original radiance data, sampled to 30 Km and 3-hour spacing. Data collection for this product is complete and was collected using several instruments on multiple platforms, please see the instrument and platform list of this record for a comprehensive list. The normalization of all radiances to a standard calibration made these data a globally uniform set of measurements that can be used for detailed cloud process studies.\r\n\r\nISCCP was the first project of the World Climate Research Program (WCRP) and was established in 1982 (WMO-35 1982, Schiffer and Rossow 1983) to: produce a global, reduced resolution, calibrated and normalized radiance data set containing basic information on the properties of the atmosphere from which cloud parameters can be derived; stimulate and coordinate basic research on techniques for inferring the physical properties of clouds from the condensed radiance data set and to apply the resulting algorithms to derive and validate a global cloud climatology for improving the parameterization of clouds in climate models; and promote research using ISCCP data that contributes to improved understanding of the Earth's radiation budget and hydrological cycle. \r\n\r\nSince 1983 an international group of institutions has collected and analyzed satellite radiance measurements from up to five geostationary and two polar orbiting satellites to infer the global distribution of cloud properties and their diurnal, seasonal and inter-annual variations. The primary focus of the first phase of the project (1983-1995) was the elucidation of the role of clouds in the radiation budget (top of the atmosphere and surface). In the second phase of the project (1995 onwards) the analysis also concerns improving understanding of clouds in the global hydrological cycle. \r\n\r\nISCCP analysis combined satellite-measured radiances (Stage B3 data, Schiffer and Rossow 1985), Rossow et al. 1987) with the TOVS atmospheric temperature-humidity and ice/snow correlative data sets to obtain information about clouds and the surface. The analysis method first determined the presence of absence of clouds in each individual image pixel and retrieves the radiometric properties of the cloud for each cloudy pixel and of the surface for each clear pixel. The pixel analysis is performed separately for each satellite radiance data set and the results reported in the Stage DX data product, which has a nominal resolution of 30 km and 3 hours. The Stage D1 product is produced by summarizing the pixel-level results every 3 hours on an equal-area map with 280 km resolution and merging the results from separate satellites with the atmospheric and ice/snow data sets to produce global coverage at each time. The Stage D2 data product is produced by averaging the Stage D1 data over each month, first at each of the eight three hour time intervals and then over all time intervals.", "distribution": [ { "@type": "dcat:Distribution", - "accessURL": "https://doi.org/10.5066/F7F47M8Q", - "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.8ec2db4f-7c68-42da-8beb-0c4a7cb2d060.xml", - "format": "XML", + "conformsTo": "http://www.isotc211.org/2005/gmi", + "description": "The metadata's original source.", + "downloadURL": "https://cmr.earthdata.nasa.gov/search/concepts/C3880704215-LARC_CLOUD.iso19115", + "format": "ISO", "mediaType": "text/xml", "title": "Original Metadata" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://asdc.larc.nasa.gov/citing-data", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://asdc.larc.nasa.gov/documents/isccp/guide/abstract_ISCCP_Stage_B3.pdf", + "format": "PDF", + "mediaType": "application/pdf" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://asdc.larc.nasa.gov/documents/isccp/guide/isccp_project.pdf", + "format": "PDF", + "mediaType": "application/pdf" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://asdc.larc.nasa.gov/documents/isccp/isccp_b3_details.pdf", + "format": "PDF", + "mediaType": "application/pdf" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://asdc.larc.nasa.gov/documents/isccp/read_software/isccp_b3_kind.f", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://asdc.larc.nasa.gov/documents/isccp/read_software/isccp_b3_module.f", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://asdc.larc.nasa.gov/documents/isccp/read_software/isccp_b3_read.f", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://asdc.larc.nasa.gov/documents/isccp/read_software/isccp_b3_read_linux.f", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://asdc.larc.nasa.gov/documents/isccp/readme/readme_isccp_b3_nat.txt", + "format": "TXT", + "mediaType": "text/plain" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://asdc.larc.nasa.gov/project/ISCCP", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://climatedataguide.ucar.edu/", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://cmr.earthdata.nasa.gov/virtual-directory/collections/C3880704215-LARC_CLOUD", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://doi.org/10.5067/ISCCP/B3_NAT", + "format": "HTML", + "mediaType": "text/html" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://earthdata.nasa.gov/esds/competitive-programs/measures/data-analysis-for-isccp", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://earthobservatory.nasa.gov/features/ShadowsDoubt", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://earthobservatory.nasa.gov/features/StarsCloudsCrops", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://isccp.giss.nasa.gov/", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://isccp.giss.nasa.gov/docs/documents.html", + "format": "HTML", + "mediaType": "text/html" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://isccp.giss.nasa.gov/errors.html", + "format": "HTML", + "mediaType": "text/html" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://isccp.giss.nasa.gov/newalg.html", + "format": "HTML", + "mediaType": "text/html" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://isccp.giss.nasa.gov/products/products.html", + "format": "HTML", + "mediaType": "text/html" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://science.nasa.gov/mission/aura/science-and-data/", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://search.earthdata.nasa.gov/search/granules?p=C3880704215-LARC_CLOUD", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://www.earthdata.nasa.gov/learn/sensing-our-planet/but-the-winds-but-the-spaces", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://www.giss.nasa.gov/tools/panoply/", + "format": "BIN", + "mediaType": "application/octet-stream" } ], - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_8ec2db4f-7c68-42da-8beb-0c4a7cb2d060", - "keyword": [ - "Groundwater", - "InlandWaters", - "SUTRA", - "SUTRA-ice", - "Shenandoah National Park", - "Surface Water", - "Thermal", - "USGS:8ec2db4f-7c68-42da-8beb-0c4a7cb2d060", - "Virginia", - "environment", - "geoscientificInformation", - "inlandWaters", - "refugia" - ], - "modified": "2020-11-17T00:00:00Z", + "identifier": "10.5067/ISCCP/B3_NAT", + "keyword": [ + "earth-science-infrared-wavelengths-spectral-engineering-infrared-imagery", + "earth-science-infrared-wavelengths-spectral-engineering-infrared-radiance", + "earth-science-visible-wavelengths-spectral-engineering-visible-imagery", + "earth-science-visible-wavelengths-spectral-engineering-visible-radiance" + ], + "license": "https://www.usa.gov/government-works", + "modified": "2026-09-22", + "programCode": [ + "026:000" + ], "publisher": { "@type": "org:Organization", - "name": "U.S. Geological Survey" - }, - "spatial": "-78.378933, 38.53969, -78.347222, 38.58403", - "theme": [ - "geospatial" - ], - "title": "Modeled temperature data developed for study of shallow mountain bedrock limits seepage-based headwater climate refugia, Shenandoah National Park, Virginia: U.S. Geological Survey data release" - }, - "description": "1D transient numerical simulations with a modified version of the SUTRA model \n(preliminary code) that accounts for variably-saturated freeze-thaw dynamics \n(e.g. McKenzie and Voss, 2013) to predict annual alluvial aquifer temperature \ndynamics using coupled fluid and heat transport physics. The model simulations \nwere run with a modified version of SUTRA_ICE (unreleased) that accomadates \na time-variable sinusiodal upper temperature boundary. This data release also \nincludes the source code and Argus One GUI files used to build the models, \nthough this proprietary software is not needed to run the models as described \nin the upper-level \"readme\" file.", + "name": "NASA/LARC/SD/ASDC" + }, + "spatial": "[\"CARTESIAN\", [{\"Boundary\": {\"Points\": [{\"Latitude\": -90, \"Longitude\": -180}, {\"Latitude\": -90, \"Longitude\": 180}, {\"Latitude\": 90, \"Longitude\": 180}, {\"Latitude\": 90, \"Longitude\": -180}, {\"Latitude\": -90, \"Longitude\": -180}]}}]]", + "temporal": "1983-07-01/2009-12-31", + "theme": [ + "Earth Science" + ], + "title": "International Satellite Cloud Climatology Project (ISCCP) Stage B3 Reduced Radiances in Native Format" + }, + "description": "The ISCCP_B3_NAT data is the International Satellite Cloud Climatology Project (ISCCP) Stage B3 Reduced Radiances in Native Format data product. This is the original radiance data, sampled to 30 Km and 3-hour spacing. Data collection for this product is complete and was collected using several instruments on multiple platforms, please see the instrument and platform list of this record for a comprehensive list. The normalization of all radiances to a standard calibration made these data a globally uniform set of measurements that can be used for detailed cloud process studies.\r\n\r\nISCCP was the first project of the World Climate Research Program (WCRP) and was established in 1982 (WMO-35 1982, Schiffer and Rossow 1983) to: produce a global, reduced resolution, calibrated and normalized radiance data set containing basic information on the properties of the atmosphere from which cloud parameters can be derived; stimulate and coordinate basic research on techniques for inferring the physical properties of clouds from the condensed radiance data set and to apply the resulting algorithms to derive and validate a global cloud climatology for improving the parameterization of clouds in climate models; and promote research using ISCCP data that contributes to improved understanding of the Earth's radiation budget and hydrological cycle. \r\n\r\nSince 1983 an international group of institutions has collected and analyzed satellite radiance measurements from up to five geostationary and two polar orbiting satellites to infer the global distribution of cloud properties and their diurnal, seasonal and inter-annual variations. The primary focus of the first phase of the project (1983-1995) was the elucidation of the role of clouds in the radiation budget (top of the atmosphere and surface). In the second phase of the project (1995 onwards) the analysis also concerns improving understanding of clouds in the global hydrological cycle. \r\n\r\nISCCP analysis combined satellite-measured radiances (Stage B3 data, Schiffer and Rossow 1985), Rossow et al. 1987) with the TOVS atmospheric temperature-humidity and ice/snow correlative data sets to obtain information about clouds and the surface. The analysis method first determined the presence of absence of clouds in each individual image pixel and retrieves the radiometric properties of the cloud for each cloudy pixel and of the surface for each clear pixel. The pixel analysis is performed separately for each satellite radiance data set and the results reported in the Stage DX data product, which has a nominal resolution of 30 km and 3 hours. The Stage D1 product is produced by summarizing the pixel-level results every 3 hours on an equal-area map with 280 km resolution and merging the results from separate satellites with the atmospheric and ice/snow data sets to produce global coverage at each time. The Stage D2 data product is produced by averaging the Stage D1 data over each month, first at each of the eight three hour time intervals and then over all time intervals.", "distribution_titles": [ - "Digital Data", "Original Metadata" ], - "harvest_record": "https://catalog.data.gov/harvest_record/4b875650-0e8e-4c74-8d55-9e76854fc4d2", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/4b875650-0e8e-4c74-8d55-9e76854fc4d2/raw", + "harvest_record": "https://catalog.data.gov/harvest_record/6d67fc18-0c4c-4b15-90ec-a4b6e2d75df0", + "harvest_record_raw": "https://catalog.data.gov/harvest_record/6d67fc18-0c4c-4b15-90ec-a4b6e2d75df0/raw", "has_download": true, "has_spatial": true, - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_8ec2db4f-7c68-42da-8beb-0c4a7cb2d060", - "keyword": [ - "Groundwater", - "InlandWaters", - "SUTRA", - "SUTRA-ice", - "Shenandoah National Park", - "Surface Water", - "Thermal", - "USGS:8ec2db4f-7c68-42da-8beb-0c4a7cb2d060", - "Virginia", - "environment", - "geoscientificInformation", - "inlandWaters", - "refugia" - ], - "last_harvested_date": "2026-09-17T00:39:41.640959", + "identifier": "10.5067/ISCCP/B3_NAT", + "keyword": [ + "earth-science-infrared-wavelengths-spectral-engineering-infrared-imagery", + "earth-science-infrared-wavelengths-spectral-engineering-infrared-radiance", + "earth-science-visible-wavelengths-spectral-engineering-visible-imagery", + "earth-science-visible-wavelengths-spectral-engineering-visible-radiance" + ], + "last_harvested_date": "2026-09-23T00:17:49.646828", "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", + "id": "f4ca4614-8901-409b-8553-2e994ad10023", + "logo": "https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png", + "name": "National Aeronautics and Space Administration", "organization_type": "Federal Government", - "slug": "doi" + "slug": "nasa" }, "parent_identifier": null, "popularity": 1, - "publisher": "U.S. Geological Survey", - "slug": "modeled-temperature-data-developed-for-study-of-shallow-mountain-bedrock-limits-seepage-ba", - "spatial_centroid": { - "lat": 38.557426, - "lon": -78.3662486 - }, - "spatial_shape": { - "coordinates": [ - [ - [ - -78.378933, - 38.53969 - ], - [ - -78.378933, - 38.58403 - ], - [ - -78.347222, - 38.58403 - ], - [ - -78.347222, - 38.53969 - ], - [ - -78.378933, - 38.53969 - ] - ] - ], - "type": "Polygon" - }, - "theme": [ - "geospatial" - ], - "title": "Modeled temperature data developed for study of shallow mountain bedrock limits seepage-based headwater climate refugia, Shenandoah National Park, Virginia: U.S. Geological Survey data release", + "publisher": "NASA/LARC/SD/ASDC", + "slug": "international-satellite-cloud-climatology-project-isccp-stage-b3-reduced-radiances-in-nati", + "spatial_centroid": null, + "spatial_shape": null, + "theme": [ + "Earth Science" + ], + "title": "International Satellite Cloud Climatology Project (ISCCP) Stage B3 Reduced Radiances in Native Format", "type": "dataset" }, { - "_score": 24.224026, + "_score": 12.258453, "_sort": [ - 1789605360724, - 24.224026, + 1790122669244, + 12.258453, 1, - "cc1e5a35-411e-412b-ae24-a35459c2a5ee" + "3af28914-9d66-4c1e-95ac-1657ee8803be" ], "dcat": { + "@type": "dcat:Dataset", "accessLevel": "public", "bureauCode": [ - "010:12" + "026:00" ], "contactPoint": { "@type": "vcard:Contact", - "fn": "Fred D Tillman", - "hasEmail": "mailto:ftillman@usgs.gov" - }, - "description": "hsg_UCRB_Maurer_resolution.asc is an Esri ASCII grid representing the hydrologic soil group \n(HSG) for the Upper Colorado River Basin. The HSG for an area is determined by the least \nwater-transmitting layer in the soil column. The Natural Resources Conservation Service \n(NRCS) classifies four HSGs from Group A (high infiltration capacity and low overland flow \npotential) to Group D (low infiltration capacity and high overland flow potential). In Soil-Water \nBalance recharge simulations, a lookup table incorporates HSG and land-cover information \nfor each grid cell to define unique runoff curve numbers, vegetation rooting depths, interception \nvalues, and maximum daily recharge values.", + "fn": "Earthdata Forum", + "hasEmail": "mailto:earthdata-support@nasa.gov" + }, + "description": "The ISCCP_D2 data set contains monthly, 280 KM equal-area grid data from various polar and geostationary satellites. Climatological Summary Product contents contain monthly average of D1 quantities including mean diurnal cycle, distribution and properties of total cloudiness and cloud types.\r\n\r\nThe International Satellite Cloud Climatology Project (ISCCP), the first project of the World Climate Research Program (WCRP), was established in 1982 (WMO-35 1982, Schiffer and Rossow 1983): \r\n- To produce a global, reduced resolution, calibrated and normalized radiance data set containing basic information on the properties of the atmosphere from which cloud parameters can be derived. \r\n- To stimulate and coordinate basic research on techniques for inferring the physical properties of clouds from the condensed radiance data set and to apply the resulting algorithms to derive and validate a global cloud climatology for improving the parameterization of clouds in climate models. \r\n- To promote research using ISCCP data that contributes to improved understanding of the Earth's radiation budget and hydrological cycle. \r\n\r\nSince 1983 an international group of institutions has collected and analyzed satellite radiance measurements from up to five geostationary and two polar orbiting satellites to infer the global distribution of cloud properties and their diurnal, seasonal and interannual variations. The primary focus of the first phase of the project (1983-1995) was the elucidation of the role of clouds in the radiation budget (top of the atmosphere and surface). In the second phase of the project (1995 onwards) the analysis also concerns improving understanding of clouds in the global hydrological cycle. \r\n\r\nThe ISCCP analysis combines satellite-measured radiances (Stage B3 data, Schiffer and Rossow 1985), Rossow et al. 1987) with the TOVS atmospheric temperature-humidity and ice/snow correlative data sets to obtain information about clouds and the surface. The analysis method first determines the presence of absence of clouds in each individual image pixel and retrieves the radiometric properties of the cloud for each cloudy pixel and of the surface for each clear pixel. The pixel analysis is performed separately for each satellite radiance data set and the results reported in the Stage DX data product, which has a nominal resolution of 30 km and 3 hours. The Stage D1 product is produced by summarizing the pixel-level results every 3 hours on an equal-area map with 280 km resolution and merging the results from separate satellites with the atmospheric and ice/snow data sets to produce global coverage at each time. The Stage D2 data product is produced by averaging the Stage D1 data over each month, first at each of the eight three hour time intervals and then over all time intervals.", "distribution": [ { "@type": "dcat:Distribution", - "accessURL": "https://doi.org/10.5066/P9CRMCYQ", - "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.54f57f83-ee11-44ce-82d7-bb5f1e06e86f.xml", - "format": "XML", + "conformsTo": "http://www.isotc211.org/2005/gmi", + "description": "The metadata's original source.", + "downloadURL": "https://cmr.earthdata.nasa.gov/search/concepts/C3880704243-LARC_CLOUD.iso19115", + "format": "ISO", "mediaType": "text/xml", "title": "Original Metadata" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://asdc.larc.nasa.gov/citing-data", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://asdc.larc.nasa.gov/documents/isccp/guide/base_isccp_d1_d2_dataset.pdf", + "format": "PDF", + "mediaType": "application/pdf" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://asdc.larc.nasa.gov/documents/isccp/guide/isccp_project.pdf", + "format": "PDF", + "mediaType": "application/pdf" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://asdc.larc.nasa.gov/documents/isccp/read_software/isccp_d2_read.c", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://asdc.larc.nasa.gov/documents/isccp/read_software/isccp_d2_read.f", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://asdc.larc.nasa.gov/documents/isccp/readme/readme_isccp_d2.txt", + "format": "TXT", + "mediaType": "text/plain" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://asdc.larc.nasa.gov/project/ISCCP", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://climatedataguide.ucar.edu/", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://cmr.earthdata.nasa.gov/virtual-directory/collections/C3880704243-LARC_CLOUD", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://doi.org/10.5067/ISCCP/D2", + "format": "HTML", + "mediaType": "text/html" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://earthdata.nasa.gov/esds/competitive-programs/measures/data-analysis-for-isccp", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://earthobservatory.nasa.gov/features/ShadowsDoubt", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://earthobservatory.nasa.gov/features/StarsCloudsCrops", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://isccp.giss.nasa.gov/", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://isccp.giss.nasa.gov/docs/documents.html", + "format": "HTML", + "mediaType": "text/html" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://isccp.giss.nasa.gov/errors.html", + "format": "HTML", + "mediaType": "text/html" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://isccp.giss.nasa.gov/newalg.html", + "format": "HTML", + "mediaType": "text/html" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://isccp.giss.nasa.gov/products/products.html", + "format": "HTML", + "mediaType": "text/html" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://science.nasa.gov/mission/aura/science-and-data/", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://search.earthdata.nasa.gov/search/granules?p=C3880704243-LARC_CLOUD", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://www.earthdata.nasa.gov/learn/sensing-our-planet/but-the-winds-but-the-spaces", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://www.giss.nasa.gov/tools/panoply/", + "format": "BIN", + "mediaType": "application/octet-stream" } ], - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_54f57f83-ee11-44ce-82d7-bb5f1e06e86f", - "keyword": [ - "Arizona", - "California", - "Colorado", - "Nevada", - "New Mexico", - "USGS:54f57f83-ee11-44ce-82d7-bb5f1e06e86f", - "Upper Colorado River Basin", - "Utah", - "Wyoming", - "environment", - "geoscientificInformation", - "groundwater", - "groundwater recharge", - "hydrologic soil group", - "inlandWaters" - ], - "modified": "2020-11-17T00:00:00Z", + "identifier": "10.5067/ISCCP/D2", + "keyword": [ + "earth-science-atmospheric-chemistry-atmosphere-oxygen-compounds", + "earth-science-atmospheric-chemistry-atmosphere-trace-gases-trace-species", + "earth-science-atmospheric-pressure-atmosphere-atmospheric-pressure-measurements", + "earth-science-atmospheric-pressure-atmosphere-surface-pressure", + "earth-science-atmospheric-radiation-atmosphere-optical-depth-thickness", + "earth-science-atmospheric-radiation-atmosphere-reflectance", + "earth-science-atmospheric-temperature-atmosphere-surface-temperature", + "earth-science-atmospheric-water-vapor-atmosphere-water-vapor-indicators", + "earth-science-clouds-atmosphere-cloud-microphysics", + "earth-science-clouds-atmosphere-cloud-properties", + "earth-science-clouds-atmosphere-cloud-types", + "earth-science-snow-ice-cryosphere-snow-cover", + "earth-science-snow-ice-terrestrial-hydrosphere-snow-cover" + ], + "license": "https://www.usa.gov/government-works", + "modified": "2026-09-22", + "programCode": [ + "026:000" + ], "publisher": { "@type": "org:Organization", - "name": "U.S. Geological Survey" - }, - "spatial": "-112.625, 35.125, -105.25, 43.75", - "theme": [ - "geospatial" - ], - "title": "Hydrologic Soil Group for the Upper Colorado River Basin in Maurer et al. (2002) Climate Data resolution (hsg_UCRB_Maurer_resolution.asc)" - }, - "description": "hsg_UCRB_Maurer_resolution.asc is an Esri ASCII grid representing the hydrologic soil group \n(HSG) for the Upper Colorado River Basin. The HSG for an area is determined by the least \nwater-transmitting layer in the soil column. The Natural Resources Conservation Service \n(NRCS) classifies four HSGs from Group A (high infiltration capacity and low overland flow \npotential) to Group D (low infiltration capacity and high overland flow potential). In Soil-Water \nBalance recharge simulations, a lookup table incorporates HSG and land-cover information \nfor each grid cell to define unique runoff curve numbers, vegetation rooting depths, interception \nvalues, and maximum daily recharge values.", + "name": "NASA/LARC/SD/ASDC" + }, + "spatial": "[\"CARTESIAN\", [{\"Boundary\": {\"Points\": [{\"Latitude\": -90, \"Longitude\": -180}, {\"Latitude\": -90, \"Longitude\": 180}, {\"Latitude\": 90, \"Longitude\": 180}, {\"Latitude\": 90, \"Longitude\": -180}, {\"Latitude\": -90, \"Longitude\": -180}]}}]]", + "temporal": "1983-07-01/2009-12-31", + "theme": [ + "Earth Science" + ], + "title": "International Satellite Cloud Climatology Project (ISCCP) Stage D2 Monthly Cloud Products - Revised Algorithm in Hierarchical Data Format" + }, + "description": "The ISCCP_D2 data set contains monthly, 280 KM equal-area grid data from various polar and geostationary satellites. Climatological Summary Product contents contain monthly average of D1 quantities including mean diurnal cycle, distribution and properties of total cloudiness and cloud types.\r\n\r\nThe International Satellite Cloud Climatology Project (ISCCP), the first project of the World Climate Research Program (WCRP), was established in 1982 (WMO-35 1982, Schiffer and Rossow 1983): \r\n- To produce a global, reduced resolution, calibrated and normalized radiance data set containing basic information on the properties of the atmosphere from which cloud parameters can be derived. \r\n- To stimulate and coordinate basic research on techniques for inferring the physical properties of clouds from the condensed radiance data set and to apply the resulting algorithms to derive and validate a global cloud climatology for improving the parameterization of clouds in climate models. \r\n- To promote research using ISCCP data that contributes to improved understanding of the Earth's radiation budget and hydrological cycle. \r\n\r\nSince 1983 an international group of institutions has collected and analyzed satellite radiance measurements from up to five geostationary and two polar orbiting satellites to infer the global distribution of cloud properties and their diurnal, seasonal and interannual variations. The primary focus of the first phase of the project (1983-1995) was the elucidation of the role of clouds in the radiation budget (top of the atmosphere and surface). In the second phase of the project (1995 onwards) the analysis also concerns improving understanding of clouds in the global hydrological cycle. \r\n\r\nThe ISCCP analysis combines satellite-measured radiances (Stage B3 data, Schiffer and Rossow 1985), Rossow et al. 1987) with the TOVS atmospheric temperature-humidity and ice/snow correlative data sets to obtain information about clouds and the surface. The analysis method first determines the presence of absence of clouds in each individual image pixel and retrieves the radiometric properties of the cloud for each cloudy pixel and of the surface for each clear pixel. The pixel analysis is performed separately for each satellite radiance data set and the results reported in the Stage DX data product, which has a nominal resolution of 30 km and 3 hours. The Stage D1 product is produced by summarizing the pixel-level results every 3 hours on an equal-area map with 280 km resolution and merging the results from separate satellites with the atmospheric and ice/snow data sets to produce global coverage at each time. The Stage D2 data product is produced by averaging the Stage D1 data over each month, first at each of the eight three hour time intervals and then over all time intervals.", "distribution_titles": [ - "Digital Data", "Original Metadata" ], - "harvest_record": "https://catalog.data.gov/harvest_record/16315e3e-0794-463b-96e0-0270748e17a6", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/16315e3e-0794-463b-96e0-0270748e17a6/raw", + "harvest_record": "https://catalog.data.gov/harvest_record/0c7114e9-cf64-4d12-a671-4abd01286512", + "harvest_record_raw": "https://catalog.data.gov/harvest_record/0c7114e9-cf64-4d12-a671-4abd01286512/raw", "has_download": true, "has_spatial": true, - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_54f57f83-ee11-44ce-82d7-bb5f1e06e86f", - "keyword": [ - "Arizona", - "California", - "Colorado", - "Nevada", - "New Mexico", - "USGS:54f57f83-ee11-44ce-82d7-bb5f1e06e86f", - "Upper Colorado River Basin", - "Utah", - "Wyoming", - "environment", - "geoscientificInformation", - "groundwater", - "groundwater recharge", - "hydrologic soil group", - "inlandWaters" - ], - "last_harvested_date": "2026-09-17T00:36:00.724309", + "identifier": "10.5067/ISCCP/D2", + "keyword": [ + "earth-science-atmospheric-chemistry-atmosphere-oxygen-compounds", + "earth-science-atmospheric-chemistry-atmosphere-trace-gases-trace-species", + "earth-science-atmospheric-pressure-atmosphere-atmospheric-pressure-measurements", + "earth-science-atmospheric-pressure-atmosphere-surface-pressure", + "earth-science-atmospheric-radiation-atmosphere-optical-depth-thickness", + "earth-science-atmospheric-radiation-atmosphere-reflectance", + "earth-science-atmospheric-temperature-atmosphere-surface-temperature", + "earth-science-atmospheric-water-vapor-atmosphere-water-vapor-indicators", + "earth-science-clouds-atmosphere-cloud-microphysics", + "earth-science-clouds-atmosphere-cloud-properties", + "earth-science-clouds-atmosphere-cloud-types", + "earth-science-snow-ice-cryosphere-snow-cover", + "earth-science-snow-ice-terrestrial-hydrosphere-snow-cover" + ], + "last_harvested_date": "2026-09-23T00:17:49.244521", "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", + "id": "f4ca4614-8901-409b-8553-2e994ad10023", + "logo": "https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png", + "name": "National Aeronautics and Space Administration", "organization_type": "Federal Government", - "slug": "doi" + "slug": "nasa" }, "parent_identifier": null, "popularity": 1, - "publisher": "U.S. Geological Survey", - "slug": "hydrologic-soil-group-for-the-upper-colorado-river-basin-in-maurer-et-al-2002-climate-data", - "spatial_centroid": { - "lat": 38.575, - "lon": -109.675 - }, - "spatial_shape": { - "coordinates": [ - [ - [ - -112.625, - 35.125 - ], - [ - -112.625, - 43.75 - ], - [ - -105.25, - 43.75 - ], - [ - -105.25, - 35.125 - ], - [ - -112.625, - 35.125 - ] - ] - ], - "type": "Polygon" - }, - "theme": [ - "geospatial" - ], - "title": "Hydrologic Soil Group for the Upper Colorado River Basin in Maurer et al. (2002) Climate Data resolution (hsg_UCRB_Maurer_resolution.asc)", + "publisher": "NASA/LARC/SD/ASDC", + "slug": "international-satellite-cloud-climatology-project-isccp-stage-d2-monthly-cloud-products-re", + "spatial_centroid": null, + "spatial_shape": null, + "theme": [ + "Earth Science" + ], + "title": "International Satellite Cloud Climatology Project (ISCCP) Stage D2 Monthly Cloud Products - Revised Algorithm in Hierarchical Data Format", "type": "dataset" }, { - "_score": 31.959618, + "_score": 11.623006, "_sort": [ - 1789605257090, - 31.959618, + 1790122668845, + 11.623006, 1, - "bfcbbb22-7596-41f3-8562-e0d74b5eb014" + "4cfd56fb-eafd-4d45-83ba-ce7a0edc7d20" ], "dcat": { + "@type": "dcat:Dataset", "accessLevel": "public", "bureauCode": [ - "010:12" + "026:00" ], "contactPoint": { "@type": "vcard:Contact", - "fn": "John A Engott", - "hasEmail": "mailto:jaengott@usgs.gov" - }, - "description": "The shapefile associated with this metadata file represents the spatial distribution of mean annual \nwater-budget components, in inches, for the Island of Oahu, Hawaii. The water-budget components \nin the shapefile were computed by a water-budget model for a scenario representative of average \nclimate conditions (1978–2007 rainfall) and 2010 land cover, as described in USGS Scientific \nInvestigations Report (SIR) 2015-5010. The model was developed for estimating groundwater \nrecharge and other water-budget components for each subarea of the model. The model subareas \nwere generated using Esri ArcGIS software by intersecting (merging) multiple spatial data sets \nthat characterize the spatial distribution of rainfall, fog interception, irrigation, reference \nevapotranspiration, direct runoff, soil type, and land cover. These spatial data sets characterize \nthe spatial distribution of hydrologic and physical conditions that the model uses to compute \ngroundwater recharge and other water-budget components.The model-subarea data set (387,533 \npolygons) was subsequently intersected with the 0-ft elevation contour of the top of the basalt \naquifer to produce the 395,955 polygons in this shapefile. This metadata file describes the process \nof merging these spatial data sets, The shapefile attribute information associated with each \npolygon present an estimate of mean annual rainfall, fog interception, irrigation, septic-system \nleachate, runoff, canopy evaporation, actual evapotranspiration, storm-drain capture, net precipitation, \ntotal evapotranspiration, recharge, and seepage from reservoirs and cesspools. This shapefile also \nincludes select geographic and land-cover attributes of the polygons. Brief descriptions of the \nwater-budget components and attributes are included in this metadata file. Refer to USGS \nSIR 2015-5010 for further details of the methods and sources used to determine these \ncomponents and attributes.", + "fn": "Earthdata Forum", + "hasEmail": "mailto:earthdata-support@nasa.gov" + }, + "description": "ISCCP_DX_1 is the International Satellite Cloud Climatology Project (ISCCP) Stage DX Pixel Level Cloud Product - Revised Algorithm in Binary Format data set. It contains 3-hourly, 30 KM satellite image projection data from various polar and geostationary satellites. Pixel Level Cloud Product contents include calibrated radiances, cloud detection results, and cloud and surface properties from radiative analysis. Data collection for this data set is complete.\r\n\r\nISCCP was the first project of the World Climate Research Program (WCRP) and was established in 1982 (WMO-35 1982, Schiffer and Rossow 1983) to:\r\nproduce a global, reduced resolution, calibrated and normalized radiance data set containing basic information on the properties of the atmosphere from which cloud parameters can be derived; stimulate and coordinate basic research on techniques for inferring the physical properties of clouds from the condensed radiance data set and to apply the resulting algorithms to derive and validate a global cloud climatology for improving the parameterization of clouds in climate models; and promote research using ISCCP data that contributes to improved understanding of the Earth's radiation budget and hydrological cycle.\r\n\r\nStarting in 1983, an international group of institutions collected and analyzed satellite radiance measurements from up to five geostationary and two polar orbiting satellites to infer the global distribution of cloud properties and their diurnal, seasonal and inter-annual variations. The primary focus of the first phase of the project (1983-1995) was the elucidation of the role of clouds in the radiation budget (top of the atmosphere and surface). In the second phase of the project (1995 onward) the analysis was also concerned with improving understanding of clouds in the global hydrological cycle.\r\n\r\nThe ISCCP analysis combined satellite-measured radiances (Stage B3 data, Schiffer and Rossow 1985, Rossow et al. 1987) with the Tiros Operational Vertical Sounder (TOVS) atmospheric temperature-humidity and ice/snow correlative data sets to obtain information about clouds and the surface. The analysis method first determined the presence of or absence of clouds in each individual image pixel and retrieved the radiometric properties of the cloud for each cloudy pixel and of the surface for each clear pixel. The pixel analysis was performed separately for each satellite radiance data set and the results were reported in the Stage DX data product, which had a nominal resolution of 30 km and 3 hours. The Stage D1 product was produced by summarizing the pixel-level results every 3 hours on an equal-area map with 280 km resolution and merging the results from separate satellites with the atmospheric and ice/snow data sets to produce global coverage at each time. The Stage D2 data product was produced by averaging the Stage D1 data over each month, first at each of the eight three hour time intervals and then over all time intervals.", "distribution": [ { "@type": "dcat:Distribution", - "accessURL": "https://doi.org/10.5066/P9GO0SU1", - "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.38975e2a-b3ce-44cd-bf4c-9c827c0e1309.xml", - "format": "XML", + "conformsTo": "http://www.isotc211.org/2005/gmi", + "description": "The metadata's original source.", + "downloadURL": "https://cmr.earthdata.nasa.gov/search/concepts/C3880704255-LARC_CLOUD.iso19115", + "format": "ISO", "mediaType": "text/xml", "title": "Original Metadata" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://asdc.larc.nasa.gov/citing-data", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://asdc.larc.nasa.gov/documents/isccp/guide/base_isccp_dx_dataset.pdf", + "format": "PDF", + "mediaType": "application/pdf" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://asdc.larc.nasa.gov/documents/isccp/guide/isccp_project.pdf", + "format": "PDF", + "mediaType": "application/pdf" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://asdc.larc.nasa.gov/documents/isccp/read_software/isccp_dx_read.f", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://asdc.larc.nasa.gov/documents/isccp/read_software/linux_isccp_dx_read.f", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://asdc.larc.nasa.gov/documents/isccp/readme/readme_isccp_dx_nat.txt", + "format": "TXT", + "mediaType": "text/plain" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://asdc.larc.nasa.gov/project/ISCCP", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://climatedataguide.ucar.edu/", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://cmr.earthdata.nasa.gov/virtual-directory/collections/C3880704255-LARC_CLOUD", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://doi.org/10.5067/ISCCP/DX", + "format": "HTML", + "mediaType": "text/html" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://earthdata.nasa.gov/esds/competitive-programs/measures/data-analysis-for-isccp", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://earthobservatory.nasa.gov/features/ShadowsDoubt", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://earthobservatory.nasa.gov/features/StarsCloudsCrops", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://isccp.giss.nasa.gov/", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://isccp.giss.nasa.gov/docs/documents.html", + "format": "HTML", + "mediaType": "text/html" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://isccp.giss.nasa.gov/errors.html", + "format": "HTML", + "mediaType": "text/html" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://isccp.giss.nasa.gov/newalg.html", + "format": "HTML", + "mediaType": "text/html" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://isccp.giss.nasa.gov/products/products.html", + "format": "HTML", + "mediaType": "text/html" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://science.nasa.gov/mission/aura/science-and-data/", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://search.earthdata.nasa.gov/search/granules?p=C3880704255-LARC_CLOUD", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://www.earthdata.nasa.gov/learn/sensing-our-planet/but-the-winds-but-the-spaces", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://www.giss.nasa.gov/tools/panoply/", + "format": "BIN", + "mediaType": "application/octet-stream" } ], - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_38975e2a-b3ce-44cd-bf4c-9c827c0e1309", - "keyword": [ - "Hawaii", - "Oahu", - "Pacific islands", - "USGS:38975e2a-b3ce-44cd-bf4c-9c827c0e1309", - "canopy evaporation", - "environment", - "evapotranspiration", - "fog interception", - "geoscientificInformation", - "groundwater recharge", - "inlandWaters", - "irrigation", - "rainfall", - "runoff", - "soil-water balance", - "storm-drain capture", - "water-budget model" - ], - "modified": "2020-11-17T00:00:00Z", + "identifier": "10.5067/ISCCP/DX", + "keyword": [ + "earth-science-atmospheric-pressure-atmosphere-atmospheric-pressure-measurements", + "earth-science-atmospheric-radiation-atmosphere-reflectance", + "earth-science-atmospheric-temperature-atmosphere-surface-temperature", + "earth-science-clouds-atmosphere-cloud-properties", + "earth-science-clouds-atmosphere-cloud-types", + "earth-science-infrared-wavelengths-spectral-engineering-infrared-imagery", + "earth-science-visible-wavelengths-spectral-engineering-visible-imagery" + ], + "license": "https://www.usa.gov/government-works", + "modified": "2026-09-22", + "programCode": [ + "026:000" + ], "publisher": { "@type": "org:Organization", - "name": "U.S. Geological Survey" - }, - "spatial": "-158.282291463, 21.253656969, -157.644933809, 21.714009852", - "theme": [ - "geospatial" - ], - "title": "Mean annual water-budget components for the Island of Oahu, Hawaii, for average climate conditions, 1978-2007 rainfall and 2010 land cover (version 2.0)" - }, - "description": "The shapefile associated with this metadata file represents the spatial distribution of mean annual \nwater-budget components, in inches, for the Island of Oahu, Hawaii. The water-budget components \nin the shapefile were computed by a water-budget model for a scenario representative of average \nclimate conditions (1978–2007 rainfall) and 2010 land cover, as described in USGS Scientific \nInvestigations Report (SIR) 2015-5010. The model was developed for estimating groundwater \nrecharge and other water-budget components for each subarea of the model. The model subareas \nwere generated using Esri ArcGIS software by intersecting (merging) multiple spatial data sets \nthat characterize the spatial distribution of rainfall, fog interception, irrigation, reference \nevapotranspiration, direct runoff, soil type, and land cover. These spatial data sets characterize \nthe spatial distribution of hydrologic and physical conditions that the model uses to compute \ngroundwater recharge and other water-budget components.The model-subarea data set (387,533 \npolygons) was subsequently intersected with the 0-ft elevation contour of the top of the basalt \naquifer to produce the 395,955 polygons in this shapefile. This metadata file describes the process \nof merging these spatial data sets, The shapefile attribute information associated with each \npolygon present an estimate of mean annual rainfall, fog interception, irrigation, septic-system \nleachate, runoff, canopy evaporation, actual evapotranspiration, storm-drain capture, net precipitation, \ntotal evapotranspiration, recharge, and seepage from reservoirs and cesspools. This shapefile also \nincludes select geographic and land-cover attributes of the polygons. Brief descriptions of the \nwater-budget components and attributes are included in this metadata file. Refer to USGS \nSIR 2015-5010 for further details of the methods and sources used to determine these \ncomponents and attributes.", + "name": "NASA/LARC/SD/ASDC" + }, + "spatial": "[\"CARTESIAN\", [{\"Boundary\": {\"Points\": [{\"Latitude\": -90, \"Longitude\": -180}, {\"Latitude\": -90, \"Longitude\": 180}, {\"Latitude\": 90, \"Longitude\": 180}, {\"Latitude\": 90, \"Longitude\": -180}, {\"Latitude\": -90, \"Longitude\": -180}]}}]]", + "temporal": "1983-06-30/2009-12-31", + "theme": [ + "Earth Science" + ], + "title": "International Satellite Cloud Climatology Project (ISCCP) Stage DX Pixel Level Cloud Product - Revised Algorithm in Binary Format" + }, + "description": "ISCCP_DX_1 is the International Satellite Cloud Climatology Project (ISCCP) Stage DX Pixel Level Cloud Product - Revised Algorithm in Binary Format data set. It contains 3-hourly, 30 KM satellite image projection data from various polar and geostationary satellites. Pixel Level Cloud Product contents include calibrated radiances, cloud detection results, and cloud and surface properties from radiative analysis. Data collection for this data set is complete.\r\n\r\nISCCP was the first project of the World Climate Research Program (WCRP) and was established in 1982 (WMO-35 1982, Schiffer and Rossow 1983) to:\r\nproduce a global, reduced resolution, calibrated and normalized radiance data set containing basic information on the properties of the atmosphere from which cloud parameters can be derived; stimulate and coordinate basic research on techniques for inferring the physical properties of clouds from the condensed radiance data set and to apply the resulting algorithms to derive and validate a global cloud climatology for improving the parameterization of clouds in climate models; and promote research using ISCCP data that contributes to improved understanding of the Earth's radiation budget and hydrological cycle.\r\n\r\nStarting in 1983, an international group of institutions collected and analyzed satellite radiance measurements from up to five geostationary and two polar orbiting satellites to infer the global distribution of cloud properties and their diurnal, seasonal and inter-annual variations. The primary focus of the first phase of the project (1983-1995) was the elucidation of the role of clouds in the radiation budget (top of the atmosphere and surface). In the second phase of the project (1995 onward) the analysis was also concerned with improving understanding of clouds in the global hydrological cycle.\r\n\r\nThe ISCCP analysis combined satellite-measured radiances (Stage B3 data, Schiffer and Rossow 1985, Rossow et al. 1987) with the Tiros Operational Vertical Sounder (TOVS) atmospheric temperature-humidity and ice/snow correlative data sets to obtain information about clouds and the surface. The analysis method first determined the presence of or absence of clouds in each individual image pixel and retrieved the radiometric properties of the cloud for each cloudy pixel and of the surface for each clear pixel. The pixel analysis was performed separately for each satellite radiance data set and the results were reported in the Stage DX data product, which had a nominal resolution of 30 km and 3 hours. The Stage D1 product was produced by summarizing the pixel-level results every 3 hours on an equal-area map with 280 km resolution and merging the results from separate satellites with the atmospheric and ice/snow data sets to produce global coverage at each time. The Stage D2 data product was produced by averaging the Stage D1 data over each month, first at each of the eight three hour time intervals and then over all time intervals.", "distribution_titles": [ - "Digital Data", "Original Metadata" ], - "harvest_record": "https://catalog.data.gov/harvest_record/e02aefa5-2e2b-4952-8e9d-adfabbb63dd9", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/e02aefa5-2e2b-4952-8e9d-adfabbb63dd9/raw", + "harvest_record": "https://catalog.data.gov/harvest_record/318b868e-b8f7-43fe-b1de-7d6a49039587", + "harvest_record_raw": "https://catalog.data.gov/harvest_record/318b868e-b8f7-43fe-b1de-7d6a49039587/raw", "has_download": true, "has_spatial": true, - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_38975e2a-b3ce-44cd-bf4c-9c827c0e1309", - "keyword": [ - "Hawaii", - "Oahu", - "Pacific islands", - "USGS:38975e2a-b3ce-44cd-bf4c-9c827c0e1309", - "canopy evaporation", - "environment", - "evapotranspiration", - "fog interception", - "geoscientificInformation", - "groundwater recharge", - "inlandWaters", - "irrigation", - "rainfall", - "runoff", - "soil-water balance", - "storm-drain capture", - "water-budget model" - ], - "last_harvested_date": "2026-09-17T00:34:17.090421", + "identifier": "10.5067/ISCCP/DX", + "keyword": [ + "earth-science-atmospheric-pressure-atmosphere-atmospheric-pressure-measurements", + "earth-science-atmospheric-radiation-atmosphere-reflectance", + "earth-science-atmospheric-temperature-atmosphere-surface-temperature", + "earth-science-clouds-atmosphere-cloud-properties", + "earth-science-clouds-atmosphere-cloud-types", + "earth-science-infrared-wavelengths-spectral-engineering-infrared-imagery", + "earth-science-visible-wavelengths-spectral-engineering-visible-imagery" + ], + "last_harvested_date": "2026-09-23T00:17:48.845462", "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", + "id": "f4ca4614-8901-409b-8553-2e994ad10023", + "logo": "https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png", + "name": "National Aeronautics and Space Administration", "organization_type": "Federal Government", - "slug": "doi" + "slug": "nasa" }, "parent_identifier": null, "popularity": 1, - "publisher": "U.S. Geological Survey", - "slug": "mean-annual-water-budget-components-for-the-island-of-oahu-hawaii-for-average-climate-cond", - "spatial_centroid": { - "lat": 21.4377981222, - "lon": -158.02734840140002 - }, - "spatial_shape": { - "coordinates": [ - [ - [ - -158.282291463, - 21.253656969 - ], - [ - -158.282291463, - 21.714009852 - ], - [ - -157.644933809, - 21.714009852 - ], - [ - -157.644933809, - 21.253656969 - ], - [ - -158.282291463, - 21.253656969 - ] - ] - ], - "type": "Polygon" - }, - "theme": [ - "geospatial" - ], - "title": "Mean annual water-budget components for the Island of Oahu, Hawaii, for average climate conditions, 1978-2007 rainfall and 2010 land cover (version 2.0)", + "publisher": "NASA/LARC/SD/ASDC", + "slug": "international-satellite-cloud-climatology-project-isccp-stage-dx-pixel-level-cloud-product", + "spatial_centroid": null, + "spatial_shape": null, + "theme": [ + "Earth Science" + ], + "title": "International Satellite Cloud Climatology Project (ISCCP) Stage DX Pixel Level Cloud Product - Revised Algorithm in Binary Format", "type": "dataset" }, { - "_score": 14.828577, + "_score": 59.01831, "_sort": [ - 1789604988184, - 14.828577, - 3, - "d54f5359-a6d4-43e5-b526-b61c064d5c2b" + 1790122667750, + 59.01831, + 1, + "3dd81fdf-7297-4dfe-8f30-dac14345b3d7" ], "dcat": { + "@type": "dcat:Dataset", "accessLevel": "public", "bureauCode": [ - "010:12" + "026:00" ], "contactPoint": { "@type": "vcard:Contact", - "fn": "Jennifer S. Stanton", - "hasEmail": "mailto:jstanton@usgs.gov" - }, - "description": "The water-budget components geodatabase contains selected data from maps in the, \n\"Selected Approaches to Estimate Water-Budget Components of the High Plains, 1940 \nthrough 1949 and 2000 through 2009\" report (Stanton and others, 2011).Data were \ncollected and synthesized from existing climate models including the Parameter-Elevation \nRegressions on Independent Slopes Model (PRISM) (Daly and others, 1994), and the Snow \naccumulation and ablation model (SNOW-17) (Anderson, 2006), and used in soil-water \nbalance models to compute various components of a water budget. The methodologies \nused to compute the averages and volumes for the data in this geodatabase are slightly \ndifferent for different components and models.", + "fn": "Earthdata Forum", + "hasEmail": "mailto:earthdata-support@nasa.gov" + }, + "description": "This data set contains a mean monthly climatology for several climate variables averaged over the period from 1961 to 1990, and constructed from a data set of station 1961-1990 climatological normals, numbering between 19,800 (precipitation) and 3,615 (windspeed; see New et al, 1999 for details). The station data were interpolated as a function of latitude, longitude and elevation using thin-plate splines. The data comprise a suite of climate elements: precipitation, mean, maximum, and minimum temperature, frost frequency, diurnal temperature range, radiation, wet-day frequency, vapor pressure, wind, and cloud cover. There are 23 files in this data set provided at 0.5 and 1.0 degree spatial resolutions.", "distribution": [ { "@type": "dcat:Distribution", - "accessURL": "https://doi.org/10.5066/P9UHH793", - "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.db072ee1-887b-4321-8f3d-cf18830e7a34.xml", - "format": "XML", + "conformsTo": "http://www.isotc211.org/2005/gmi", + "description": "The metadata's original source.", + "downloadURL": "https://cmr.earthdata.nasa.gov/search/concepts/C2785293782-ORNL_CLOUD.iso19115", + "format": "ISO", "mediaType": "text/xml", "title": "Original Metadata" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://daac.ornl.gov/graphics/browse/sdat-tds/1015_1_fit.png", + "format": "PNG", + "mediaType": "image/png" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://data.ornldaac.earthdata.nasa.gov/protected/bundle/cru_monthly_mean_xdeg_1015.zip", + "format": "ZIP", + "mediaType": "application/zip" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://data.ornldaac.earthdata.nasa.gov/public/islscp_ii/near-surface_met/cru_monthly_mean_xdeg/comp/0_cru_mean_readme.txt", + "format": "TXT", + "mediaType": "text/plain" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://data.ornldaac.earthdata.nasa.gov/public/islscp_ii/near-surface_met/cru_monthly_mean_xdeg/comp/1_cru_monthly_mean_doc.pdf", + "format": "PDF", + "mediaType": "application/pdf" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://doi.org/10.3334/ORNLDAAC/1015", + "format": "HTML", + "mediaType": "text/html" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://search.earthdata.nasa.gov/search/granules?p=C2785293782-ORNL_CLOUD", + "format": "BIN", + "mediaType": "application/octet-stream" } ], - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_db072ee1-887b-4321-8f3d-cf18830e7a34", - "keyword": [ - "Colorado", - "Great Plains", - "High Plains", - "High Plains aquifer", - "Kansas", - "Nebraska", - "New Mexico", - "Ogallala aquifer", - "Oklahoma", - "Precipitation", - "South Dakota", - "Texas", - "USGS:db072ee1-887b-4321-8f3d-cf18830e7a34", - "Wyoming", - "aquifers", - "central High Plains", - "environment", - "geoscientificInformation", - "ground water", - "groundwater", - "inlandWaters", - "northern High Plains", - "southern High Plains" - ], - "modified": "2020-11-17T00:00:00Z", + "identifier": "10.3334/ORNLDAAC/1015", + "keyword": [ + "earth-science-atmospheric-temperature-atmosphere-surface-temperature", + "earth-science-atmospheric-water-vapor-atmosphere-water-vapor-indicators", + "earth-science-clouds-atmosphere-cloud-properties", + "earth-science-precipitation-atmosphere-precipitation-amount", + "earth-science-topography-land-surface-terrain-elevation" + ], + "license": "https://www.usa.gov/government-works", + "modified": "2026-09-22", + "programCode": [ + "026:000" + ], "publisher": { "@type": "org:Organization", - "name": "U.S. Geological Survey" - }, - "spatial": "-106.022041, 31.594384, -96.233280, 43.825034", - "theme": [ - "geospatial" - ], - "title": "DS-777 Average Annual Precipitation data, 1940 to 1949, in inches estimated from the Parameter-Elevation Regressions on Independent Slopes Model (PRISM) for the High Plains Aquifer in Parts of Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming" - }, - "description": "The water-budget components geodatabase contains selected data from maps in the, \n\"Selected Approaches to Estimate Water-Budget Components of the High Plains, 1940 \nthrough 1949 and 2000 through 2009\" report (Stanton and others, 2011).Data were \ncollected and synthesized from existing climate models including the Parameter-Elevation \nRegressions on Independent Slopes Model (PRISM) (Daly and others, 1994), and the Snow \naccumulation and ablation model (SNOW-17) (Anderson, 2006), and used in soil-water \nbalance models to compute various components of a water budget. The methodologies \nused to compute the averages and volumes for the data in this geodatabase are slightly \ndifferent for different components and models.", + "name": "ORNL_DAAC" + }, + "spatial": "[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -180.0, \"NorthBoundingCoordinate\": 90.0, \"EastBoundingCoordinate\": 180.0, \"SouthBoundingCoordinate\": -90.0}]]", + "temporal": "1986-01-01/1995-12-31", + "theme": [ + "Earth Science" + ], + "title": "ISLSCP II Climate Research Unit CRU05 Monthly Climate Data" + }, + "description": "This data set contains a mean monthly climatology for several climate variables averaged over the period from 1961 to 1990, and constructed from a data set of station 1961-1990 climatological normals, numbering between 19,800 (precipitation) and 3,615 (windspeed; see New et al, 1999 for details). The station data were interpolated as a function of latitude, longitude and elevation using thin-plate splines. The data comprise a suite of climate elements: precipitation, mean, maximum, and minimum temperature, frost frequency, diurnal temperature range, radiation, wet-day frequency, vapor pressure, wind, and cloud cover. There are 23 files in this data set provided at 0.5 and 1.0 degree spatial resolutions.", "distribution_titles": [ - "Digital Data", "Original Metadata" ], - "harvest_record": "https://catalog.data.gov/harvest_record/38fb1279-9e77-45b8-95b0-f63e37df9033", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/38fb1279-9e77-45b8-95b0-f63e37df9033/raw", + "harvest_record": "https://catalog.data.gov/harvest_record/e68efab6-fae6-4705-afd4-c20b935c7747", + "harvest_record_raw": "https://catalog.data.gov/harvest_record/e68efab6-fae6-4705-afd4-c20b935c7747/raw", "has_download": true, "has_spatial": true, - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_db072ee1-887b-4321-8f3d-cf18830e7a34", - "keyword": [ - "Colorado", - "Great Plains", - "High Plains", - "High Plains aquifer", - "Kansas", - "Nebraska", - "New Mexico", - "Ogallala aquifer", - "Oklahoma", - "Precipitation", - "South Dakota", - "Texas", - "USGS:db072ee1-887b-4321-8f3d-cf18830e7a34", - "Wyoming", - "aquifers", - "central High Plains", - "environment", - "geoscientificInformation", - "ground water", - "groundwater", - "inlandWaters", - "northern High Plains", - "southern High Plains" - ], - "last_harvested_date": "2026-09-17T00:29:48.184531", + "identifier": "10.3334/ORNLDAAC/1015", + "keyword": [ + "earth-science-atmospheric-temperature-atmosphere-surface-temperature", + "earth-science-atmospheric-water-vapor-atmosphere-water-vapor-indicators", + "earth-science-clouds-atmosphere-cloud-properties", + "earth-science-precipitation-atmosphere-precipitation-amount", + "earth-science-topography-land-surface-terrain-elevation" + ], + "last_harvested_date": "2026-09-23T00:17:47.750117", "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", + "id": "f4ca4614-8901-409b-8553-2e994ad10023", + "logo": "https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png", + "name": "National Aeronautics and Space Administration", "organization_type": "Federal Government", - "slug": "doi" + "slug": "nasa" }, "parent_identifier": null, - "popularity": 3, - "publisher": "U.S. Geological Survey", - "slug": "ds-777-average-annual-precipitation-data-1940-to-1949-in-inches-estimated-from-the-paramet", - "spatial_centroid": { - "lat": 36.486644, - "lon": -102.1065366 - }, - "spatial_shape": { - "coordinates": [ - [ - [ - -106.022041, - 31.594384 - ], - [ - -106.022041, - 43.825034 - ], - [ - -96.23328, - 43.825034 - ], - [ - -96.23328, - 31.594384 - ], - [ - -106.022041, - 31.594384 - ] - ] - ], - "type": "Polygon" - }, - "theme": [ - "geospatial" - ], - "title": "DS-777 Average Annual Precipitation data, 1940 to 1949, in inches estimated from the Parameter-Elevation Regressions on Independent Slopes Model (PRISM) for the High Plains Aquifer in Parts of Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming", + "popularity": 1, + "publisher": "ORNL_DAAC", + "slug": "islscp-ii-climate-research-unit-cru05-monthly-climate-data", + "spatial_centroid": null, + "spatial_shape": null, + "theme": [ + "Earth Science" + ], + "title": "ISLSCP II Climate Research Unit CRU05 Monthly Climate Data", "type": "dataset" }, { - "_score": 14.857659, + "_score": 8.876841, "_sort": [ - 1789604493819, - 14.857659, - 2, - "1b471c58-aa54-4375-b5df-778657a6849a" + 1790122667037, + 8.876841, + 1, + "28c58c69-0b6e-48df-a9a7-f02ee3d4b2ba" ], "dcat": { + "@type": "dcat:Dataset", "accessLevel": "public", "bureauCode": [ - "010:12" + "026:00" ], "contactPoint": { "@type": "vcard:Contact", - "fn": "Jennifer S. Stanton", - "hasEmail": "mailto:jstanton@usgs.gov" - }, - "description": "The water-budget components geodatabase contains selected data from maps in the, \n\"Selected Approaches to Estimate Water-Budget Components of the High Plains, 1940 \nthrough 1949 and 2000 through 2009\" report (Stanton and others, 2011).Data were \ncollected and synthesized from existing climate models including the Parameter-Elevation \nRegressions on Independent Slopes Model (PRISM) (Daly and others, 1994), and the Snow \naccumulation and ablation model (SNOW-17) (Anderson, 2006), and used in soil-water \nbalance models to compute various components of a water budget. The methodologies \nused to compute the averages and volumes for the data in this geodatabase are slightly \ndifferent for different components and models.", + "fn": "Earthdata Forum", + "hasEmail": "mailto:earthdata-support@nasa.gov" + }, + "description": "The objective of this study was to derive continuous fields of vegetation cover from multi-temporal Advanced Very High Resolution Radiometer (AVHRR) data using all available bands and derived Normalized Difference Vegetation Index (NDVI). The continuous fields describe sub-pixel proportions of cover for tree, herbaceous, bare ground and water cover types. For tree cover, additional fields describing leaf longevity (evergreen and deciduous) and leaf morphology (broadleaf and needleleaf) were also generated. The modeling of carbon dynamics and climate require knowing tree characteristics such as these. These products were resampled and aggregated to 0.25, 0.5 and 1.0 degree grids for the International Satellite Land Surface Climatology Project (ISLSCP) data initiative II. The data set describes the geographic distributions of three fundamental vegetation characteristics: tree, herbaceous and bare ground cover, plus a water layer. For tree cover, leaf longevity and morphology layers were produced.\n\nThis data set is one of the products of the International Satellite Land-Surface Climatology Project, Initiative II (ISLSCP II) data collection which contains 50 global time series data sets for the ten-year period 1986 to 1995. Selected data sets span even longer periods. ISLSCP II is a consistent collection of data sets that were compiled from existing data sources and algorithms, and were designed to satisfy the needs of modelers and investigators of the global carbon, water and energy cycle. The data were acquired from a number of U.S. and international agencies, universities, and institutions. The global data sets were mapped at consistent spatial (1, 0.5 and 0.25 degrees) and temporal (monthly, with meteorological data at finer (e.g., 3-hour)) resolutions and reformatted into a common ASCII format. The data and documentation have undergone two peer reviews.\n\nISLSCP is one of several projects of Global Energy and Water Cycle Experiment (GEWEX) [http://www.gewex.org/] and has the lead role in addressing land-atmosphere interactions -- process modeling, data retrieval algorithms, field experiment design and execution, and the development of global data sets.", "distribution": [ { "@type": "dcat:Distribution", - "accessURL": "https://doi.org/10.5066/P90XT1YP", - "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.fab4301e-91af-41bd-ae87-6e598372d09c.xml", - "format": "XML", + "conformsTo": "http://www.isotc211.org/2005/gmi", + "description": "The metadata's original source.", + "downloadURL": "https://cmr.earthdata.nasa.gov/search/concepts/C2784863182-ORNL_CLOUD.iso19115", + "format": "ISO", "mediaType": "text/xml", "title": "Original Metadata" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://daac.ornl.gov/graphics/browse/sdat-tds/931_1_fit.png", + "format": "PNG", + "mediaType": "image/png" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://data.ornldaac.earthdata.nasa.gov/protected/bundle/veg_continuous_fields_xdeg_931.zip", + "format": "ZIP", + "mediaType": "application/zip" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://data.ornldaac.earthdata.nasa.gov/public/islscp_ii/vegetation/veg_continuous_fields_xdeg/comp/0_veg_cont_fields_readme.txt", + "format": "TXT", + "mediaType": "text/plain" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://data.ornldaac.earthdata.nasa.gov/public/islscp_ii/vegetation/veg_continuous_fields_xdeg/comp/1_veg_continuous_fields_doc.pdf", + "format": "PDF", + "mediaType": "application/pdf" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://doi.org/10.3334/ORNLDAAC/931", + "format": "HTML", + "mediaType": "text/html" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://search.earthdata.nasa.gov/search/granules?p=C2784863182-ORNL_CLOUD", + "format": "BIN", + "mediaType": "application/octet-stream" } ], - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_fab4301e-91af-41bd-ae87-6e598372d09c", - "keyword": [ - "Colorado", - "Great Plains", - "High Plains", - "High Plains aquifer", - "Kansas", - "Nebraska", - "New Mexico", - "Ogallala aquifer", - "Oklahoma", - "SOil WATer (SOWAT) Balance Model", - "South Dakota", - "Texas", - "USGS:fab4301e-91af-41bd-ae87-6e598372d09c", - "Wyoming", - "aquifers", - "central High Plains", - "environment", - "geoscientificInformation", - "ground water", - "groundwater", - "inlandWaters", - "northern High Plains", - "recharge", - "southern High Plains" - ], - "modified": "2020-11-17T00:00:00Z", + "identifier": "10.3334/ORNLDAAC/931", + "keyword": [ + "earth-science-atmospheric-radiation-atmosphere-albedo", + "earth-science-atmospheric-radiation-atmosphere-reflectance", + "earth-science-land-use-land-cover-land-surface-land-use-land-cover-classification", + "earth-science-vegetation-biosphere-canopy-characteristics", + "earth-science-vegetation-biosphere-leaf-characteristics", + "earth-science-vegetation-biosphere-plant-characteristics", + "earth-science-vegetation-biosphere-vegetation-cover", + "earth-science-vegetation-biosphere-vegetation-index" + ], + "license": "https://www.usa.gov/government-works", + "modified": "2026-09-22", + "programCode": [ + "026:000" + ], "publisher": { "@type": "org:Organization", - "name": "U.S. Geological Survey" - }, - "spatial": "-106.019428, 31.594384, -96.222657, 43.807131", - "theme": [ - "geospatial" - ], - "title": "DS-777 Average Annual Recharge, 2000 to 2009, in inches estimated from the SOil WATer (SOWAT) Balance Model for the High Plains Aquifer in Parts of Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming" - }, - "description": "The water-budget components geodatabase contains selected data from maps in the, \n\"Selected Approaches to Estimate Water-Budget Components of the High Plains, 1940 \nthrough 1949 and 2000 through 2009\" report (Stanton and others, 2011).Data were \ncollected and synthesized from existing climate models including the Parameter-Elevation \nRegressions on Independent Slopes Model (PRISM) (Daly and others, 1994), and the Snow \naccumulation and ablation model (SNOW-17) (Anderson, 2006), and used in soil-water \nbalance models to compute various components of a water budget. The methodologies \nused to compute the averages and volumes for the data in this geodatabase are slightly \ndifferent for different components and models.", + "name": "ORNL_DAAC" + }, + "spatial": "[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -180.0, \"NorthBoundingCoordinate\": 90.0, \"EastBoundingCoordinate\": 180.0, \"SouthBoundingCoordinate\": -90.0}]]", + "temporal": "1992-04-01/1993-05-31", + "theme": [ + "Earth Science" + ], + "title": "ISLSCP II Continuous Fields of Vegetation Cover, 1992-1993" + }, + "description": "The objective of this study was to derive continuous fields of vegetation cover from multi-temporal Advanced Very High Resolution Radiometer (AVHRR) data using all available bands and derived Normalized Difference Vegetation Index (NDVI). The continuous fields describe sub-pixel proportions of cover for tree, herbaceous, bare ground and water cover types. For tree cover, additional fields describing leaf longevity (evergreen and deciduous) and leaf morphology (broadleaf and needleleaf) were also generated. The modeling of carbon dynamics and climate require knowing tree characteristics such as these. These products were resampled and aggregated to 0.25, 0.5 and 1.0 degree grids for the International Satellite Land Surface Climatology Project (ISLSCP) data initiative II. The data set describes the geographic distributions of three fundamental vegetation characteristics: tree, herbaceous and bare ground cover, plus a water layer. For tree cover, leaf longevity and morphology layers were produced.\n\nThis data set is one of the products of the International Satellite Land-Surface Climatology Project, Initiative II (ISLSCP II) data collection which contains 50 global time series data sets for the ten-year period 1986 to 1995. Selected data sets span even longer periods. ISLSCP II is a consistent collection of data sets that were compiled from existing data sources and algorithms, and were designed to satisfy the needs of modelers and investigators of the global carbon, water and energy cycle. The data were acquired from a number of U.S. and international agencies, universities, and institutions. The global data sets were mapped at consistent spatial (1, 0.5 and 0.25 degrees) and temporal (monthly, with meteorological data at finer (e.g., 3-hour)) resolutions and reformatted into a common ASCII format. The data and documentation have undergone two peer reviews.\n\nISLSCP is one of several projects of Global Energy and Water Cycle Experiment (GEWEX) [http://www.gewex.org/] and has the lead role in addressing land-atmosphere interactions -- process modeling, data retrieval algorithms, field experiment design and execution, and the development of global data sets.", "distribution_titles": [ - "Digital Data", "Original Metadata" ], - "harvest_record": "https://catalog.data.gov/harvest_record/195803d1-fd40-440b-8d1a-f2312199ccd2", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/195803d1-fd40-440b-8d1a-f2312199ccd2/raw", + "harvest_record": "https://catalog.data.gov/harvest_record/c4f613a6-f63e-42f1-afd6-6a1f48ed251c", + "harvest_record_raw": "https://catalog.data.gov/harvest_record/c4f613a6-f63e-42f1-afd6-6a1f48ed251c/raw", "has_download": true, "has_spatial": true, - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_fab4301e-91af-41bd-ae87-6e598372d09c", - "keyword": [ - "Colorado", - "Great Plains", - "High Plains", - "High Plains aquifer", - "Kansas", - "Nebraska", - "New Mexico", - "Ogallala aquifer", - "Oklahoma", - "SOil WATer (SOWAT) Balance Model", - "South Dakota", - "Texas", - "USGS:fab4301e-91af-41bd-ae87-6e598372d09c", - "Wyoming", - "aquifers", - "central High Plains", - "environment", - "geoscientificInformation", - "ground water", - "groundwater", - "inlandWaters", - "northern High Plains", - "recharge", - "southern High Plains" - ], - "last_harvested_date": "2026-09-17T00:21:33.819582", + "identifier": "10.3334/ORNLDAAC/931", + "keyword": [ + "earth-science-atmospheric-radiation-atmosphere-albedo", + "earth-science-atmospheric-radiation-atmosphere-reflectance", + "earth-science-land-use-land-cover-land-surface-land-use-land-cover-classification", + "earth-science-vegetation-biosphere-canopy-characteristics", + "earth-science-vegetation-biosphere-leaf-characteristics", + "earth-science-vegetation-biosphere-plant-characteristics", + "earth-science-vegetation-biosphere-vegetation-cover", + "earth-science-vegetation-biosphere-vegetation-index" + ], + "last_harvested_date": "2026-09-23T00:17:47.037991", "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", + "id": "f4ca4614-8901-409b-8553-2e994ad10023", + "logo": "https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png", + "name": "National Aeronautics and Space Administration", "organization_type": "Federal Government", - "slug": "doi" + "slug": "nasa" }, "parent_identifier": null, - "popularity": 2, - "publisher": "U.S. Geological Survey", - "slug": "ds-777-average-annual-recharge-2000-to-2009-in-inches-estimated-from-the-soil-water-sowat-", - "spatial_centroid": { - "lat": 36.4794828, - "lon": -102.1007196 - }, - "spatial_shape": { - "coordinates": [ - [ - [ - -106.019428, - 31.594384 - ], - [ - -106.019428, - 43.807131 - ], - [ - -96.222657, - 43.807131 - ], - [ - -96.222657, - 31.594384 - ], - [ - -106.019428, - 31.594384 - ] - ] - ], - "type": "Polygon" - }, - "theme": [ - "geospatial" - ], - "title": "DS-777 Average Annual Recharge, 2000 to 2009, in inches estimated from the SOil WATer (SOWAT) Balance Model for the High Plains Aquifer in Parts of Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming", + "popularity": 1, + "publisher": "ORNL_DAAC", + "slug": "islscp-ii-continuous-fields-of-vegetation-cover-1992-1993", + "spatial_centroid": null, + "spatial_shape": null, + "theme": [ + "Earth Science" + ], + "title": "ISLSCP II Continuous Fields of Vegetation Cover, 1992-1993", "type": "dataset" }, { - "_score": 14.828577, + "_score": 11.614737, "_sort": [ - 1789604431519, - 14.828577, - 3, - "f07c05d7-519b-48b4-a4af-6dc7795e2151" + 1790122665932, + 11.614737, + 1, + "5c4879bb-7784-4f31-b137-259eddb40aaf" ], "dcat": { + "@type": "dcat:Dataset", "accessLevel": "public", "bureauCode": [ - "010:12" + "026:00" ], "contactPoint": { "@type": "vcard:Contact", - "fn": "Jennifer S. Stanton", - "hasEmail": "mailto:jstanton@usgs.gov" - }, - "description": "The water-budget-components geodatabase contains selected data from maps in the,\n\"Selected Approaches to Estimate Water-Budget Components of the High Plains, 1940 \nthrough 1949 and 2000 through 2009\" report (Stanton and others, 2011). Data were \ncollected and synthesized from existing climate models including the Parameter-Elevation \nRegressions on Independent Slopes Model (PRISM) (Daly and others, 1994), and the \nSnow accumulation and ablation model (SNOW-17) (Anderson, 2006), and used in \nsoil-water balance models to compute various components of a water budget. The \nmethodologies used to compute the averages and volumes for the data in this \ngeodatabase are slightly different for different components and models.", + "fn": "Earthdata Forum", + "hasEmail": "mailto:earthdata-support@nasa.gov" + }, + "description": "The Fourier-Adjusted, Sensor and Solar zenith angle corrected, Interpolated, Reconstructed (FASIR) adjusted Normalized Difference Vegetation Index (NDVI) data sets were generated to provide a 17-year, satellite record of monthly changes in the photosynthetic activity of terrestrial vegetation. FASIR-NDVI data are also used in climate models and biogeochemical models to calculate photosynthesis, the exchange of CO2 between the atmosphere and the land surface, land-surface evapotranspiration and the absorption and release of energy by the land surface. There are three data files provided at spatial resolutions of 0.25, 0.5 and 1.0 degree in latitude and longitude. FASIR adjustments concentrated on reducing NDVI variations arising from atmospheric, calibration, view and illumination geometries and other effects not related to actual vegetation change.\n\nFASIR NDVI was also generated to provide inputs for computing a 17-year time series of associated biophysical parameters, provided as a separate data set in this data collection. The production of the FASIR NDVI data set and its associated biophysical parameters was funded by NASA's Land Surface Hydrology program and the Higher Education Funding Council for Wales (HEFCW) as a core component of the International Satellite Land Surface Climatology Project (ISLSCP) Initiative II Data Collection.", "distribution": [ { "@type": "dcat:Distribution", - "accessURL": "https://doi.org/10.5066/P9UKMDQZ", - "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.d8b44992-7421-4ee5-9da6-6172253cfc7b.xml", - "format": "XML", + "conformsTo": "http://www.isotc211.org/2005/gmi", + "description": "The metadata's original source.", + "downloadURL": "https://cmr.earthdata.nasa.gov/search/concepts/C2784893177-ORNL_CLOUD.iso19115", + "format": "ISO", "mediaType": "text/xml", "title": "Original Metadata" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://daac.ornl.gov/graphics/browse/sdat-tds/972_1_fit.png", + "format": "PNG", + "mediaType": "image/png" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://data.ornldaac.earthdata.nasa.gov/protected/bundle/fasir_ndvi_monthly_xdeg_972.zip", + "format": "ZIP", + "mediaType": "application/zip" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://data.ornldaac.earthdata.nasa.gov/public/islscp_ii/vegetation/fasir_ndvi_monthly_xdeg/comp/0_fasir_ndvi_readme.txt", + "format": "TXT", + "mediaType": "text/plain" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://data.ornldaac.earthdata.nasa.gov/public/islscp_ii/vegetation/fasir_ndvi_monthly_xdeg/comp/1_fasir_ndvi_doc.pdf", + "format": "PDF", + "mediaType": "application/pdf" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://doi.org/10.3334/ORNLDAAC/972", + "format": "HTML", + "mediaType": "text/html" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://search.earthdata.nasa.gov/search/granules?p=C2784893177-ORNL_CLOUD", + "format": "BIN", + "mediaType": "application/octet-stream" } ], - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_d8b44992-7421-4ee5-9da6-6172253cfc7b", - "keyword": [ - "Colorado", - "Evapotranspiration", - "Great Plains", - "High Plains", - "High Plains aquifer", - "Kansas", - "Nebraska", - "New Mexico", - "Ogallala aquifer", - "Oklahoma", - "Potential evapotranspiration", - "South Dakota", - "Texas", - "USGS:d8b44992-7421-4ee5-9da6-6172253cfc7b", - "Wyoming", - "aquifers", - "central High Plains", - "environment", - "geoscientificInformation", - "ground water", - "groundwater", - "inlandWaters", - "northern High Plains", - "southern High Plains" - ], - "modified": "2020-11-17T00:00:00Z", + "identifier": "10.3334/ORNLDAAC/972", + "keyword": [ + "earth-science-land-use-land-cover-land-surface-land-use-land-cover-classification", + "earth-science-surface-radiative-properties-land-surface-albedo", + "earth-science-surface-radiative-properties-land-surface-reflectance", + "earth-science-vegetation-biosphere-canopy-characteristics", + "earth-science-vegetation-biosphere-leaf-characteristics", + "earth-science-vegetation-biosphere-plant-characteristics", + "earth-science-vegetation-biosphere-vegetation-cover", + "earth-science-vegetation-biosphere-vegetation-index" + ], + "license": "https://www.usa.gov/government-works", + "modified": "2026-09-22", + "programCode": [ + "026:000" + ], "publisher": { "@type": "org:Organization", - "name": "U.S. Geological Survey" - }, - "spatial": "-106.016870, 31.598356, -96.219992, 43.810915", - "theme": [ - "geospatial" - ], - "title": "DS-777 Average Annual Potential Evapotranspiration, 2000 to 2009, in inches estimated from the National Weather Service (NWS) Snow Accumulation and Ablation (SNOW-17) Model for the High Plains Aquifer in Parts of Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming" - }, - "description": "The water-budget-components geodatabase contains selected data from maps in the,\n\"Selected Approaches to Estimate Water-Budget Components of the High Plains, 1940 \nthrough 1949 and 2000 through 2009\" report (Stanton and others, 2011). Data were \ncollected and synthesized from existing climate models including the Parameter-Elevation \nRegressions on Independent Slopes Model (PRISM) (Daly and others, 1994), and the \nSnow accumulation and ablation model (SNOW-17) (Anderson, 2006), and used in \nsoil-water balance models to compute various components of a water budget. The \nmethodologies used to compute the averages and volumes for the data in this \ngeodatabase are slightly different for different components and models.", + "name": "ORNL_DAAC" + }, + "spatial": "[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -180.0, \"NorthBoundingCoordinate\": 90.0, \"EastBoundingCoordinate\": 180.0, \"SouthBoundingCoordinate\": -90.0}]]", + "temporal": "1982-01-01/1998-12-31", + "theme": [ + "Earth Science" + ], + "title": "ISLSCP II FASIR-adjusted NDVI, 1982-1998" + }, + "description": "The Fourier-Adjusted, Sensor and Solar zenith angle corrected, Interpolated, Reconstructed (FASIR) adjusted Normalized Difference Vegetation Index (NDVI) data sets were generated to provide a 17-year, satellite record of monthly changes in the photosynthetic activity of terrestrial vegetation. FASIR-NDVI data are also used in climate models and biogeochemical models to calculate photosynthesis, the exchange of CO2 between the atmosphere and the land surface, land-surface evapotranspiration and the absorption and release of energy by the land surface. There are three data files provided at spatial resolutions of 0.25, 0.5 and 1.0 degree in latitude and longitude. FASIR adjustments concentrated on reducing NDVI variations arising from atmospheric, calibration, view and illumination geometries and other effects not related to actual vegetation change.\n\nFASIR NDVI was also generated to provide inputs for computing a 17-year time series of associated biophysical parameters, provided as a separate data set in this data collection. The production of the FASIR NDVI data set and its associated biophysical parameters was funded by NASA's Land Surface Hydrology program and the Higher Education Funding Council for Wales (HEFCW) as a core component of the International Satellite Land Surface Climatology Project (ISLSCP) Initiative II Data Collection.", "distribution_titles": [ - "Digital Data", "Original Metadata" ], - "harvest_record": "https://catalog.data.gov/harvest_record/6ae24d0a-73af-4e94-8156-fcaede190ff0", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/6ae24d0a-73af-4e94-8156-fcaede190ff0/raw", + "harvest_record": "https://catalog.data.gov/harvest_record/f88ca682-0edc-4ac6-b657-7fd0e07f425e", + "harvest_record_raw": "https://catalog.data.gov/harvest_record/f88ca682-0edc-4ac6-b657-7fd0e07f425e/raw", "has_download": true, "has_spatial": true, - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_d8b44992-7421-4ee5-9da6-6172253cfc7b", - "keyword": [ - "Colorado", - "Evapotranspiration", - "Great Plains", - "High Plains", - "High Plains aquifer", - "Kansas", - "Nebraska", - "New Mexico", - "Ogallala aquifer", - "Oklahoma", - "Potential evapotranspiration", - "South Dakota", - "Texas", - "USGS:d8b44992-7421-4ee5-9da6-6172253cfc7b", - "Wyoming", - "aquifers", - "central High Plains", - "environment", - "geoscientificInformation", - "ground water", - "groundwater", - "inlandWaters", - "northern High Plains", - "southern High Plains" - ], - "last_harvested_date": "2026-09-17T00:20:31.519153", + "identifier": "10.3334/ORNLDAAC/972", + "keyword": [ + "earth-science-land-use-land-cover-land-surface-land-use-land-cover-classification", + "earth-science-surface-radiative-properties-land-surface-albedo", + "earth-science-surface-radiative-properties-land-surface-reflectance", + "earth-science-vegetation-biosphere-canopy-characteristics", + "earth-science-vegetation-biosphere-leaf-characteristics", + "earth-science-vegetation-biosphere-plant-characteristics", + "earth-science-vegetation-biosphere-vegetation-cover", + "earth-science-vegetation-biosphere-vegetation-index" + ], + "last_harvested_date": "2026-09-23T00:17:45.932678", "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", + "id": "f4ca4614-8901-409b-8553-2e994ad10023", + "logo": "https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png", + "name": "National Aeronautics and Space Administration", "organization_type": "Federal Government", - "slug": "doi" + "slug": "nasa" }, "parent_identifier": null, - "popularity": 3, - "publisher": "U.S. Geological Survey", - "slug": "ds-777-average-annual-potential-evapotranspiration-2000-to-2009-in-inches-estimated-from-t", - "spatial_centroid": { - "lat": 36.4833796, - "lon": -102.0981188 - }, - "spatial_shape": { - "coordinates": [ - [ - [ - -106.01687, - 31.598356 - ], - [ - -106.01687, - 43.810915 - ], - [ - -96.219992, - 43.810915 - ], - [ - -96.219992, - 31.598356 - ], - [ - -106.01687, - 31.598356 - ] - ] - ], - "type": "Polygon" - }, - "theme": [ - "geospatial" - ], - "title": "DS-777 Average Annual Potential Evapotranspiration, 2000 to 2009, in inches estimated from the National Weather Service (NWS) Snow Accumulation and Ablation (SNOW-17) Model for the High Plains Aquifer in Parts of Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming", + "popularity": 1, + "publisher": "ORNL_DAAC", + "slug": "islscp-ii-fasir-adjusted-ndvi-1982-1998", + "spatial_centroid": null, + "spatial_shape": null, + "theme": [ + "Earth Science" + ], + "title": "ISLSCP II FASIR-adjusted NDVI, 1982-1998", "type": "dataset" }, { - "_score": 9.946478, + "_score": 11.576915, "_sort": [ - 1789603740709, - 9.946478, - 1, - "87e0ce3b-8413-44c3-99e5-07c79744fa92" + 1790122665199, + 11.576915, + 2, + "1040dd4a-73ba-432e-a209-de8d923d3f23" ], "dcat": { + "@type": "dcat:Dataset", "accessLevel": "public", "bureauCode": [ - "010:12" + "026:00" ], "contactPoint": { "@type": "vcard:Contact", - "fn": "David E Ladd", - "hasEmail": "mailto:deladd@usgs.gov" - }, - "description": "As part of the U.S. Geological Survey Groundwater Resources Program study of \nAppalachian Plateaus aquifers, mean-annual and mean-seasonal water-budget \nestimates for the period 1980 through 2011 were determined for a 162,000 \nsquare-mile area covering parts of New York, Pennsylvania, Maryland, Ohio, \nWest Virginia, Kentucky, Virginia, Tennessee, North Carolina, Georgia, Alabama, \nand Mississippi. Mean-annual and mean-seasonal precipitation, recharge, and \nactual evapotranspiration (ET) estimates were derived from annual and monthly \nSoil-Water-Balance (SWB) model (McCoy and others, 2015; Westenbroek \nand others, 2010) output and compiled in a geodatabase. Precipitation estimates \nfrom the Appalachian Plateaus SWB model were derived from daily Daymet \nclimate grids (Thornton and others, 2012). Estimates of recharge from the \nSWB model were calculated using a modified Thornthwaite-Mather soil-water \naccounting method (Thornthwaite and Mather, 1957; Westenbroek and others, \n2010). Estimates of ET from the SWB model were derived by adjusting a \nspatially-variable estimate of potential ET (Hargreaves and Samani, 1985) with \nestimates of precipitation and soil-moisture (Westenbrok and others, 2010). \nThe geodatabase contains polygon and point feature classes representing the \nmodel grid cells and their centers, respectively, and two tables containing \nmean-annual and mean-seasonal estimates for each cell. Mean-annual \nestimates were computed for full calendar years (January through December) \nand are presented in inches per year (in/yr) for the 1980 through 2011 period. \nMean-seasonal estimates for spring (March through May), summer (June \nthrough August) and fall (September through November) are presented in \ninches for the 1980 through 2011 period. Mean-seasonal estimates for \nwinter (December through February), also presented in inches, were \ncalculated for December 1980 through February 2011.", + "fn": "Earthdata Forum", + "hasEmail": "mailto:earthdata-support@nasa.gov" + }, + "description": "The Global Inventory Modelling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI) data sets were generated to provide a 22-year satellite record of monthly changes in terrestrial vegetation. This data set contains three data files provided at spatial resolutions of 0.25, 0.5 and 1.0 degree in latitude and longitude with data from July 1981 through December 2002. New features include reduced NDVI variations arising from calibration, view geometry, volcanic aerosols, and other effects not related to actual vegetation change. In particular, NOAA-9 descending node data from September 1994 to January 1995, volcanic stratospheric aerosol correction for 1982-1984 and 1991-1994, and improved NDVI using empirical mode decomposition/reconstruction (EMD) to minimize effects of orbital drift. Global NDVI was generated to provide inputs for computing the time series of biophysical parameters contained in the International Satellite Land Surface Climatology Project (ISLSCP) Initiative II collection. NDVI is used in climate models and biogeochemical models to calculate photosynthesis, the exchange of CO2 between the atmosphere and the land surface, land-surface evapotranspiration and the absorption and release of energy by the land surface.", "distribution": [ { "@type": "dcat:Distribution", - "accessURL": "https://doi.org/10.5066/F7X06544", - "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.dba98e35-d294-402c-b31e-4ee461bc6dd1.xml", - "format": "XML", + "conformsTo": "http://www.isotc211.org/2005/gmi", + "description": "The metadata's original source.", + "downloadURL": "https://cmr.earthdata.nasa.gov/search/concepts/C2784893549-ORNL_CLOUD.iso19115", + "format": "ISO", "mediaType": "text/xml", "title": "Original Metadata" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://daac.ornl.gov/graphics/browse/sdat-tds/973_1_fit.png", + "format": "PNG", + "mediaType": "image/png" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://data.ornldaac.earthdata.nasa.gov/protected/bundle/gimms_ndvi_monthly_xdeg_973.zip", + "format": "ZIP", + "mediaType": "application/zip" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://data.ornldaac.earthdata.nasa.gov/public/islscp_ii/vegetation/gimms_ndvi_monthly_xdeg/comp/0_gimms_ndvi_readme.txt", + "format": "TXT", + "mediaType": "text/plain" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://data.ornldaac.earthdata.nasa.gov/public/islscp_ii/vegetation/gimms_ndvi_monthly_xdeg/comp/1_gimms_ndvi_doc.pdf", + "format": "PDF", + "mediaType": "application/pdf" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://doi.org/10.3334/ORNLDAAC/973", + "format": "HTML", + "mediaType": "text/html" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://search.earthdata.nasa.gov/search/granules?p=C2784893549-ORNL_CLOUD", + "format": "BIN", + "mediaType": "application/octet-stream" } ], - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_dba98e35-d294-402c-b31e-4ee461bc6dd1", - "keyword": [ - "Alabama", - "Appalalachian Plateaus", - "Georgia", - "Kentucky", - "Maryland", - "Mississippi", - "Mississippian aquifer", - "New York", - "North Carolina", - "Ohio", - "Pennsylvania", - "Pennsylvanian aquifer", - "Permian aquifer", - "Soil-Water-Balance model", - "Tennessee", - "USGS:dba98e35-d294-402c-b31e-4ee461bc6dd1", - "Virginia", - "West Virginia", - "aquifer", - "environment", - "evapotranspiration", - "geoscientificInformation", - "groundwater", - "hydrologic budget", - "inlandWaters", - "precipitation", - "recharge" - ], - "modified": "2020-11-17T00:00:00Z", + "identifier": "10.3334/ORNLDAAC/973", + "keyword": [ + "earth-science-land-use-land-cover-land-surface-land-use-land-cover-classification", + "earth-science-surface-radiative-properties-land-surface-albedo", + "earth-science-surface-radiative-properties-land-surface-reflectance", + "earth-science-vegetation-biosphere-canopy-characteristics", + "earth-science-vegetation-biosphere-leaf-characteristics", + "earth-science-vegetation-biosphere-plant-characteristics", + "earth-science-vegetation-biosphere-vegetation-cover", + "earth-science-vegetation-biosphere-vegetation-index" + ], + "license": "https://www.usa.gov/government-works", + "modified": "2026-09-22", + "programCode": [ + "026:000" + ], "publisher": { "@type": "org:Organization", - "name": "U.S. Geological Survey" - }, - "spatial": "-88.992632, 31.180164, -75.057322, 43.797973", - "theme": [ - "geospatial" - ], - "title": "Mean-annual and mean-seasonal water-budget estimates from a Soil-Water-Balance model of the Appalachian Plateaus, 1980 through 2011" - }, - "description": "As part of the U.S. Geological Survey Groundwater Resources Program study of \nAppalachian Plateaus aquifers, mean-annual and mean-seasonal water-budget \nestimates for the period 1980 through 2011 were determined for a 162,000 \nsquare-mile area covering parts of New York, Pennsylvania, Maryland, Ohio, \nWest Virginia, Kentucky, Virginia, Tennessee, North Carolina, Georgia, Alabama, \nand Mississippi. Mean-annual and mean-seasonal precipitation, recharge, and \nactual evapotranspiration (ET) estimates were derived from annual and monthly \nSoil-Water-Balance (SWB) model (McCoy and others, 2015; Westenbroek \nand others, 2010) output and compiled in a geodatabase. Precipitation estimates \nfrom the Appalachian Plateaus SWB model were derived from daily Daymet \nclimate grids (Thornton and others, 2012). Estimates of recharge from the \nSWB model were calculated using a modified Thornthwaite-Mather soil-water \naccounting method (Thornthwaite and Mather, 1957; Westenbroek and others, \n2010). Estimates of ET from the SWB model were derived by adjusting a \nspatially-variable estimate of potential ET (Hargreaves and Samani, 1985) with \nestimates of precipitation and soil-moisture (Westenbrok and others, 2010). \nThe geodatabase contains polygon and point feature classes representing the \nmodel grid cells and their centers, respectively, and two tables containing \nmean-annual and mean-seasonal estimates for each cell. Mean-annual \nestimates were computed for full calendar years (January through December) \nand are presented in inches per year (in/yr) for the 1980 through 2011 period. \nMean-seasonal estimates for spring (March through May), summer (June \nthrough August) and fall (September through November) are presented in \ninches for the 1980 through 2011 period. Mean-seasonal estimates for \nwinter (December through February), also presented in inches, were \ncalculated for December 1980 through February 2011.", + "name": "ORNL_DAAC" + }, + "spatial": "[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -180.0, \"NorthBoundingCoordinate\": 90.0, \"EastBoundingCoordinate\": 180.0, \"SouthBoundingCoordinate\": -90.0}]]", + "temporal": "1981-07-01/2002-12-31", + "theme": [ + "Earth Science" + ], + "title": "ISLSCP II GIMMS Monthly NDVI, 1981-2002" + }, + "description": "The Global Inventory Modelling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI) data sets were generated to provide a 22-year satellite record of monthly changes in terrestrial vegetation. This data set contains three data files provided at spatial resolutions of 0.25, 0.5 and 1.0 degree in latitude and longitude with data from July 1981 through December 2002. New features include reduced NDVI variations arising from calibration, view geometry, volcanic aerosols, and other effects not related to actual vegetation change. In particular, NOAA-9 descending node data from September 1994 to January 1995, volcanic stratospheric aerosol correction for 1982-1984 and 1991-1994, and improved NDVI using empirical mode decomposition/reconstruction (EMD) to minimize effects of orbital drift. Global NDVI was generated to provide inputs for computing the time series of biophysical parameters contained in the International Satellite Land Surface Climatology Project (ISLSCP) Initiative II collection. NDVI is used in climate models and biogeochemical models to calculate photosynthesis, the exchange of CO2 between the atmosphere and the land surface, land-surface evapotranspiration and the absorption and release of energy by the land surface.", "distribution_titles": [ - "Digital Data", "Original Metadata" ], - "harvest_record": "https://catalog.data.gov/harvest_record/5668cce5-c29f-44ee-8cc4-590b8c24760b", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/5668cce5-c29f-44ee-8cc4-590b8c24760b/raw", + "harvest_record": "https://catalog.data.gov/harvest_record/667a66ed-0d6b-4393-b417-5a878f424605", + "harvest_record_raw": "https://catalog.data.gov/harvest_record/667a66ed-0d6b-4393-b417-5a878f424605/raw", "has_download": true, "has_spatial": true, - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_dba98e35-d294-402c-b31e-4ee461bc6dd1", - "keyword": [ - "Alabama", - "Appalalachian Plateaus", - "Georgia", - "Kentucky", - "Maryland", - "Mississippi", - "Mississippian aquifer", - "New York", - "North Carolina", - "Ohio", - "Pennsylvania", - "Pennsylvanian aquifer", - "Permian aquifer", - "Soil-Water-Balance model", - "Tennessee", - "USGS:dba98e35-d294-402c-b31e-4ee461bc6dd1", - "Virginia", - "West Virginia", - "aquifer", - "environment", - "evapotranspiration", - "geoscientificInformation", - "groundwater", - "hydrologic budget", - "inlandWaters", - "precipitation", - "recharge" - ], - "last_harvested_date": "2026-09-17T00:09:00.709909", + "identifier": "10.3334/ORNLDAAC/973", + "keyword": [ + "earth-science-land-use-land-cover-land-surface-land-use-land-cover-classification", + "earth-science-surface-radiative-properties-land-surface-albedo", + "earth-science-surface-radiative-properties-land-surface-reflectance", + "earth-science-vegetation-biosphere-canopy-characteristics", + "earth-science-vegetation-biosphere-leaf-characteristics", + "earth-science-vegetation-biosphere-plant-characteristics", + "earth-science-vegetation-biosphere-vegetation-cover", + "earth-science-vegetation-biosphere-vegetation-index" + ], + "last_harvested_date": "2026-09-23T00:17:45.199172", "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", + "id": "f4ca4614-8901-409b-8553-2e994ad10023", + "logo": "https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png", + "name": "National Aeronautics and Space Administration", "organization_type": "Federal Government", - "slug": "doi" + "slug": "nasa" }, "parent_identifier": null, - "popularity": 1, - "publisher": "U.S. Geological Survey", - "slug": "mean-annual-and-mean-seasonal-water-budget-estimates-from-a-soil-water-balance-model--2011", - "spatial_centroid": { - "lat": 36.2272876, - "lon": -83.418508 - }, - "spatial_shape": { - "coordinates": [ - [ - [ - -88.992632, - 31.180164 - ], - [ - -88.992632, - 43.797973 - ], - [ - -75.057322, - 43.797973 - ], - [ - -75.057322, - 31.180164 - ], - [ - -88.992632, - 31.180164 - ] - ] - ], - "type": "Polygon" - }, - "theme": [ - "geospatial" - ], - "title": "Mean-annual and mean-seasonal water-budget estimates from a Soil-Water-Balance model of the Appalachian Plateaus, 1980 through 2011", + "popularity": 2, + "publisher": "ORNL_DAAC", + "slug": "islscp-ii-gimms-monthly-ndvi-1981-2002", + "spatial_centroid": null, + "spatial_shape": null, + "theme": [ + "Earth Science" + ], + "title": "ISLSCP II GIMMS Monthly NDVI, 1981-2002", "type": "dataset" }, { - "_score": 14.828577, + "_score": 8.180333, "_sort": [ - 1789603523602, - 14.828577, - 1, - "35dc6334-671e-49a3-99cf-836c81bd89bf" + 1790122662289, + 8.180333, + 2, + "9de5d5ab-6430-44c4-bc28-e3491252a6cf" ], "dcat": { + "@type": "dcat:Dataset", "accessLevel": "public", "bureauCode": [ - "010:12" + "026:00" ], "contactPoint": { "@type": "vcard:Contact", - "fn": "J. LaRue Smith", - "hasEmail": "mailto:jlsmith@usgs.gov" - }, - "description": "Hydrologic landscape regions group areas according to their similarity in landscape and climate characteristics. \nThese characteristics represent variables assumed to affect hydrologic processes in the environment. Hydrologic \nlandscape regions in Nevada were delineated using geographic information system tools and statistical methods \nincluding cluster analysis. The data layers of hydrogeology, precipitation, soil permeability, land surface slope \nand aspect were used to identify the hydrologic landscape regions. Sixteen hydrologic landscape regions were \nidentified through cluster analysis. The hydrologic landscape regions are noncontiguous in nature and can range \nfrom small areas which tend to be in the mountain ranges to very large areas in the basins.", + "fn": "Earthdata Forum", + "hasEmail": "mailto:earthdata-support@nasa.gov" + }, + "description": "This International Satellite Land Surface Climatology Project (ISLSCP) Initiative II data set, ISLSCP II Global Sea Ice Concentration, is based on the Goddard Space Flight Center (GSFC) Sea Ice Concentrations from Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) and the Defense Meteorological Satellites Program (DMSP) Special Sensor Microwave/Imager (SSM/I) Passive Microwave Data. This data set contains four zip files which includes sea ice concentration (in percentage of ocean area covered by sea ice), table data and map data. These original data were re-gridded by the National Snow and Ice Data Center (NSIDC) from their original 25-km spatial resolution and EASE-Grid into equal angle Earth grids with quarter, half and one degree spatial resolutions in latitude/longitude. The ISLSCP II staff have taken the one degree resolution original data provided by the Principal Investigator and created global maps of monthly sea ice concentration on a global one degree grid using the latitude and longitude coordinates that were provided. Individual monthly files were created and written to the ASCII format. The re-gridded one degree original data were also adjusted to match the one degree ISLSCP II land/water mask.", "distribution": [ { "@type": "dcat:Distribution", - "accessURL": "https://doi.org/10.5066/P92HOQMU", - "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.901db279-906b-489f-a960-85cf610dfc9e.xml", - "format": "XML", + "conformsTo": "http://www.isotc211.org/2005/gmi", + "description": "The metadata's original source.", + "downloadURL": "https://cmr.earthdata.nasa.gov/search/concepts/C2784896705-ORNL_CLOUD.iso19115", + "format": "ISO", "mediaType": "text/xml", "title": "Original Metadata" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://daac.ornl.gov/graphics/browse/sdat-tds/981_1_fit.png", + "format": "PNG", + "mediaType": "image/png" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://data.ornldaac.earthdata.nasa.gov/protected/bundle/sea_ice_extent_xdeg_981.zip", + "format": "ZIP", + "mediaType": "application/zip" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://data.ornldaac.earthdata.nasa.gov/public/islscp_ii/snow_sea-ice_oceans/sea_ice_extent_xdeg/comp/0_sea_ice_extent_readme.txt", + "format": "TXT", + "mediaType": "text/plain" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://data.ornldaac.earthdata.nasa.gov/public/islscp_ii/snow_sea-ice_oceans/sea_ice_extent_xdeg/comp/1_sea_ice_extent_doc.pdf", + "format": "PDF", + "mediaType": "application/pdf" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://doi.org/10.3334/ORNLDAAC/981", + "format": "HTML", + "mediaType": "text/html" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://search.earthdata.nasa.gov/search/granules?p=C2784896705-ORNL_CLOUD", + "format": "BIN", + "mediaType": "application/octet-stream" } ], - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_901db279-906b-489f-a960-85cf610dfc9e", - "keyword": [ - "Great Basin", - "Nevada", - "USGS:901db279-906b-489f-a960-85cf610dfc9e", - "environment", - "geoscientificInformation", - "hydrogeology", - "hydrologic landscape regions", - "inlandWaters", - "land surface aspect", - "land surface slope", - "precipitation", - "soil permeability" - ], - "modified": "2020-11-17T00:00:00Z", + "identifier": "10.3334/ORNLDAAC/981", + "keyword": [ + "earth-science-cryospheric-indicators-climate-indicators-sea-ice-concentration", + "earth-science-sea-ice-cryosphere-sea-ice-concentration", + "earth-science-sea-ice-oceans-ice-extent", + "earth-science-sea-ice-oceans-sea-ice-concentration" + ], + "license": "https://www.usa.gov/government-works", + "modified": "2026-09-22", + "programCode": [ + "026:000" + ], "publisher": { "@type": "org:Organization", - "name": "U.S. Geological Survey" - }, - "spatial": "-120.180324, 34.967066, -113.694509, 42.039355", - "theme": [ - "geospatial" - ], - "title": "Hydrologic landscape regions of Nevada" - }, - "description": "Hydrologic landscape regions group areas according to their similarity in landscape and climate characteristics. \nThese characteristics represent variables assumed to affect hydrologic processes in the environment. Hydrologic \nlandscape regions in Nevada were delineated using geographic information system tools and statistical methods \nincluding cluster analysis. The data layers of hydrogeology, precipitation, soil permeability, land surface slope \nand aspect were used to identify the hydrologic landscape regions. Sixteen hydrologic landscape regions were \nidentified through cluster analysis. The hydrologic landscape regions are noncontiguous in nature and can range \nfrom small areas which tend to be in the mountain ranges to very large areas in the basins.", + "name": "ORNL_DAAC" + }, + "spatial": "[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -180.0, \"NorthBoundingCoordinate\": 90.0, \"EastBoundingCoordinate\": 180.0, \"SouthBoundingCoordinate\": -90.0}]]", + "temporal": "1986-01-01/1995-12-31", + "theme": [ + "Earth Science" + ], + "title": "ISLSCP II Global Sea Ice Concentration" + }, + "description": "This International Satellite Land Surface Climatology Project (ISLSCP) Initiative II data set, ISLSCP II Global Sea Ice Concentration, is based on the Goddard Space Flight Center (GSFC) Sea Ice Concentrations from Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) and the Defense Meteorological Satellites Program (DMSP) Special Sensor Microwave/Imager (SSM/I) Passive Microwave Data. This data set contains four zip files which includes sea ice concentration (in percentage of ocean area covered by sea ice), table data and map data. These original data were re-gridded by the National Snow and Ice Data Center (NSIDC) from their original 25-km spatial resolution and EASE-Grid into equal angle Earth grids with quarter, half and one degree spatial resolutions in latitude/longitude. The ISLSCP II staff have taken the one degree resolution original data provided by the Principal Investigator and created global maps of monthly sea ice concentration on a global one degree grid using the latitude and longitude coordinates that were provided. Individual monthly files were created and written to the ASCII format. The re-gridded one degree original data were also adjusted to match the one degree ISLSCP II land/water mask.", "distribution_titles": [ - "Digital Data", "Original Metadata" ], - "harvest_record": "https://catalog.data.gov/harvest_record/2f48f824-e064-46e5-883f-e70604c1c8c1", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/2f48f824-e064-46e5-883f-e70604c1c8c1/raw", + "harvest_record": "https://catalog.data.gov/harvest_record/1f288c24-6c98-4c15-bd95-13d79db0d5a7", + "harvest_record_raw": "https://catalog.data.gov/harvest_record/1f288c24-6c98-4c15-bd95-13d79db0d5a7/raw", "has_download": true, "has_spatial": true, - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_901db279-906b-489f-a960-85cf610dfc9e", - "keyword": [ - "Great Basin", - "Nevada", - "USGS:901db279-906b-489f-a960-85cf610dfc9e", - "environment", - "geoscientificInformation", - "hydrogeology", - "hydrologic landscape regions", - "inlandWaters", - "land surface aspect", - "land surface slope", - "precipitation", - "soil permeability" - ], - "last_harvested_date": "2026-09-17T00:05:23.602445", + "identifier": "10.3334/ORNLDAAC/981", + "keyword": [ + "earth-science-cryospheric-indicators-climate-indicators-sea-ice-concentration", + "earth-science-sea-ice-cryosphere-sea-ice-concentration", + "earth-science-sea-ice-oceans-ice-extent", + "earth-science-sea-ice-oceans-sea-ice-concentration" + ], + "last_harvested_date": "2026-09-23T00:17:42.289509", "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", + "id": "f4ca4614-8901-409b-8553-2e994ad10023", + "logo": "https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png", + "name": "National Aeronautics and Space Administration", "organization_type": "Federal Government", - "slug": "doi" + "slug": "nasa" }, "parent_identifier": null, - "popularity": 1, - "publisher": "U.S. Geological Survey", - "slug": "hydrologic-landscape-regions-of-nevada", - "spatial_centroid": { - "lat": 37.795981600000005, - "lon": -117.58599799999999 - }, - "spatial_shape": { - "coordinates": [ - [ - [ - -120.180324, - 34.967066 - ], - [ - -120.180324, - 42.039355 - ], - [ - -113.694509, - 42.039355 - ], - [ - -113.694509, - 34.967066 - ], - [ - -120.180324, - 34.967066 - ] - ] - ], - "type": "Polygon" - }, - "theme": [ - "geospatial" - ], - "title": "Hydrologic landscape regions of Nevada", + "popularity": 2, + "publisher": "ORNL_DAAC", + "slug": "islscp-ii-global-sea-ice-concentration", + "spatial_centroid": null, + "spatial_shape": null, + "theme": [ + "Earth Science" + ], + "title": "ISLSCP II Global Sea Ice Concentration", "type": "dataset" }, { - "_score": 35.19064, + "_score": 13.744064, "_sort": [ - 1789603440914, - 35.19064, - 1, - "f9d2b5c2-2aca-4a63-95ec-c9d9e90267e6" + 1790122661170, + 13.744064, + 4, + "ff9f54e8-f5ef-4cab-8f3e-417b23f4a04c" ], "dcat": { + "@type": "dcat:Dataset", "accessLevel": "public", "bureauCode": [ - "010:12" + "026:00" ], "contactPoint": { "@type": "vcard:Contact", - "fn": "Oklahoma-Texas Water Science Center", - "hasEmail": "mailto:gs-w-txpublic-info@usgs.gov" - }, - "description": "Estimates of area and aerial extent of land-use categories are an essential component \nfor computing the water budget of the High Plains aquifer. These raster land-use land \nclass data represent yearly simulated future land use for the High Plains from 2009 to \n2050 These data were developed using the FOREcasting SCEnarios (FORE-SCE) of \nfuture land cover model (Sohl and others, 2007; Sohl and Sayler 2008) for two (A2 and \nB2) of the four Intergovernmental Panel on Climate Change (IPCC) climate scenarios \nand then processed using a Geographic Information System (GIS). The GIS software \nused to process these data was Environmental Systems Research Institute (ESRI, Inc.) \nArcGIS Desktop 10.0.", + "fn": "Earthdata Forum", + "hasEmail": "mailto:earthdata-support@nasa.gov" + }, + "description": "The Historical Croplands Cover data set was developed to understand the consequences of historical changes in land use and land cover for ecosystem goods and services. In particular, this data set can be used to study how global changes in cultivated area has influenced climate, biogeochemical cycles, biodiversity, etc. This data set can be used directly within spatially-explicit climate and biogeochemical models.\r\n\r\nThis is a gridded data set describing the fraction of each grid cell in the globe that is occupied by cultivated land from 1700 to 1992. Data layers are provided for every 50 years from 1700 to 1850, every 10 years from 1850 to 1980, and every year from 1986 to 1992.\r\n\r\nThere are two sources of global land cover/land use data. The most recent estimates are derived from satellite measurements, and are available in a spatially-explicit fashion for roughly the last 30 years. The other estimate is based on ground-based sources such as census statistics, land surveys, estimates by historical geographers, etc. These land inventory data are only available at the scale of political units, but have the advantage of being historical. Ramankutty and Foley (1998) derived a spatially-explicit data set of croplands in 1992 by synthesizing remotely-sensed land cover data with contemporary land inventory data. Furthermore, Ramankutty and Foley (1999) extended this data set into the past (back to 1700) using historical land inventory data.\r\n\r\nThe data set should only be used for continental-to-global scale analysis and modeling. The data set captures the broad patterns of cropland change over history, but not necessarily the fine details at local to regional scales - please check the data quality before using it at fine spatial scales. The quality of historical data for the Russian Federation is poor. The quality of data prior to 1850 is poor -- only continental-scale historical data were used for that period.", "distribution": [ { "@type": "dcat:Distribution", - "accessURL": "https://doi.org/10.5066/P9FEQ22K", - "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.ce171d76-dfc7-49ea-9375-3e0596ecc68e.xml", - "format": "XML", + "conformsTo": "http://www.isotc211.org/2005/gmi", + "description": "The metadata's original source.", + "downloadURL": "https://cmr.earthdata.nasa.gov/search/concepts/C2784888334-ORNL_CLOUD.iso19115", + "format": "ISO", "mediaType": "text/xml", "title": "Original Metadata" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://daac.ornl.gov/graphics/browse/sdat-tds/966_1_fit.png", + "format": "PNG", + "mediaType": "image/png" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://data.ornldaac.earthdata.nasa.gov/protected/bundle/historic_cropland_xdeg_966.zip", + "format": "ZIP", + "mediaType": "application/zip" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://data.ornldaac.earthdata.nasa.gov/public/islscp_ii/vegetation/historic_cropland_xdeg/comp/0_historic_cropland_readme.txt", + "format": "TXT", + "mediaType": "text/plain" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://data.ornldaac.earthdata.nasa.gov/public/islscp_ii/vegetation/historic_cropland_xdeg/comp/1_historic_cropland_doc.pdf", + "format": "PDF", + "mediaType": "application/pdf" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://doi.org/10.3334/ORNLDAAC/966", + "format": "HTML", + "mediaType": "text/html" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://search.earthdata.nasa.gov/search/granules?p=C2784888334-ORNL_CLOUD", + "format": "BIN", + "mediaType": "application/octet-stream" } ], - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_ce171d76-dfc7-49ea-9375-3e0596ecc68e", - "keyword": [ - "Colorado", - "Great Plains", - "High Plains", - "High Plains aquifer", - "Kansas", - "LULC", - "Nebraska", - "New Mexico", - "Ogallala aquifer", - "Oklahoma", - "South Dakota", - "Texas", - "USGS:ce171d76-dfc7-49ea-9375-3e0596ecc68e", - "Wyoming", - "environment", - "geoscientificInformation", - "inlandWaters", - "land cover", - "land use", - "landcover", - "landuse" - ], - "modified": "2020-11-17T00:00:00Z", + "identifier": "10.3334/ORNLDAAC/966", + "keyword": [ + "earth-science-land-use-land-cover-land-surface-land-use-land-cover-classification", + "earth-science-surface-radiative-properties-land-surface-albedo", + "earth-science-surface-radiative-properties-land-surface-reflectance", + "earth-science-vegetation-biosphere-canopy-characteristics", + "earth-science-vegetation-biosphere-leaf-characteristics", + "earth-science-vegetation-biosphere-plant-characteristics", + "earth-science-vegetation-biosphere-vegetation-cover", + "earth-science-vegetation-biosphere-vegetation-index" + ], + "license": "https://www.usa.gov/government-works", + "modified": "2026-09-22", + "programCode": [ + "026:000" + ], "publisher": { "@type": "org:Organization", - "name": "U.S. Geological Survey" - }, - "spatial": "-106.016217, 31.598356, -96.227959, 43.806414", - "theme": [ - "geospatial" - ], - "title": "DS-777 Annual Model-Forecasted Land-Use/Land-Cover Rasters from 2009 to 2050 for the B2 Climate Scenario for the High Plains Aquifer in Parts of Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming" - }, - "description": "Estimates of area and aerial extent of land-use categories are an essential component \nfor computing the water budget of the High Plains aquifer. These raster land-use land \nclass data represent yearly simulated future land use for the High Plains from 2009 to \n2050 These data were developed using the FOREcasting SCEnarios (FORE-SCE) of \nfuture land cover model (Sohl and others, 2007; Sohl and Sayler 2008) for two (A2 and \nB2) of the four Intergovernmental Panel on Climate Change (IPCC) climate scenarios \nand then processed using a Geographic Information System (GIS). The GIS software \nused to process these data was Environmental Systems Research Institute (ESRI, Inc.) \nArcGIS Desktop 10.0.", + "name": "ORNL_DAAC" + }, + "spatial": "[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -180.0, \"NorthBoundingCoordinate\": 90.0, \"EastBoundingCoordinate\": 180.0, \"SouthBoundingCoordinate\": -90.0}]]", + "temporal": "1700-01-01/1992-12-31", + "theme": [ + "Earth Science" + ], + "title": "ISLSCP II Historical Croplands Cover, 1700-1992" + }, + "description": "The Historical Croplands Cover data set was developed to understand the consequences of historical changes in land use and land cover for ecosystem goods and services. In particular, this data set can be used to study how global changes in cultivated area has influenced climate, biogeochemical cycles, biodiversity, etc. This data set can be used directly within spatially-explicit climate and biogeochemical models.\r\n\r\nThis is a gridded data set describing the fraction of each grid cell in the globe that is occupied by cultivated land from 1700 to 1992. Data layers are provided for every 50 years from 1700 to 1850, every 10 years from 1850 to 1980, and every year from 1986 to 1992.\r\n\r\nThere are two sources of global land cover/land use data. The most recent estimates are derived from satellite measurements, and are available in a spatially-explicit fashion for roughly the last 30 years. The other estimate is based on ground-based sources such as census statistics, land surveys, estimates by historical geographers, etc. These land inventory data are only available at the scale of political units, but have the advantage of being historical. Ramankutty and Foley (1998) derived a spatially-explicit data set of croplands in 1992 by synthesizing remotely-sensed land cover data with contemporary land inventory data. Furthermore, Ramankutty and Foley (1999) extended this data set into the past (back to 1700) using historical land inventory data.\r\n\r\nThe data set should only be used for continental-to-global scale analysis and modeling. The data set captures the broad patterns of cropland change over history, but not necessarily the fine details at local to regional scales - please check the data quality before using it at fine spatial scales. The quality of historical data for the Russian Federation is poor. The quality of data prior to 1850 is poor -- only continental-scale historical data were used for that period.", "distribution_titles": [ - "Digital Data", "Original Metadata" ], - "harvest_record": "https://catalog.data.gov/harvest_record/b34cf7e7-7570-4e68-ba53-1614d1430389", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/b34cf7e7-7570-4e68-ba53-1614d1430389/raw", + "harvest_record": "https://catalog.data.gov/harvest_record/d25a4da0-2e22-4733-86e0-d87e6ccb376c", + "harvest_record_raw": "https://catalog.data.gov/harvest_record/d25a4da0-2e22-4733-86e0-d87e6ccb376c/raw", "has_download": true, "has_spatial": true, - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_ce171d76-dfc7-49ea-9375-3e0596ecc68e", - "keyword": [ - "Colorado", - "Great Plains", - "High Plains", - "High Plains aquifer", - "Kansas", - "LULC", - "Nebraska", - "New Mexico", - "Ogallala aquifer", - "Oklahoma", - "South Dakota", - "Texas", - "USGS:ce171d76-dfc7-49ea-9375-3e0596ecc68e", - "Wyoming", - "environment", - "geoscientificInformation", - "inlandWaters", - "land cover", - "land use", - "landcover", - "landuse" - ], - "last_harvested_date": "2026-09-17T00:04:00.914981", + "identifier": "10.3334/ORNLDAAC/966", + "keyword": [ + "earth-science-land-use-land-cover-land-surface-land-use-land-cover-classification", + "earth-science-surface-radiative-properties-land-surface-albedo", + "earth-science-surface-radiative-properties-land-surface-reflectance", + "earth-science-vegetation-biosphere-canopy-characteristics", + "earth-science-vegetation-biosphere-leaf-characteristics", + "earth-science-vegetation-biosphere-plant-characteristics", + "earth-science-vegetation-biosphere-vegetation-cover", + "earth-science-vegetation-biosphere-vegetation-index" + ], + "last_harvested_date": "2026-09-23T00:17:41.170485", "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", + "id": "f4ca4614-8901-409b-8553-2e994ad10023", + "logo": "https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png", + "name": "National Aeronautics and Space Administration", "organization_type": "Federal Government", - "slug": "doi" + "slug": "nasa" }, "parent_identifier": null, - "popularity": 1, - "publisher": "U.S. Geological Survey", - "slug": "ds-777-annual-model-forecasted-land-use-land-cover-rasters-from-2009-to-2050-for-the-b2-cl", - "spatial_centroid": { - "lat": 36.4815792, - "lon": -102.1009138 - }, - "spatial_shape": { - "coordinates": [ - [ - [ - -106.016217, - 31.598356 - ], - [ - -106.016217, - 43.806414 - ], - [ - -96.227959, - 43.806414 - ], - [ - -96.227959, - 31.598356 - ], - [ - -106.016217, - 31.598356 - ] - ] - ], - "type": "Polygon" - }, - "theme": [ - "geospatial" - ], - "title": "DS-777 Annual Model-Forecasted Land-Use/Land-Cover Rasters from 2009 to 2050 for the B2 Climate Scenario for the High Plains Aquifer in Parts of Colorado, Kansas, Nebraska, New Mexico, Oklahoma, South Dakota, Texas, and Wyoming", + "popularity": 4, + "publisher": "ORNL_DAAC", + "slug": "islscp-ii-historical-croplands-cover-1700-1992", + "spatial_centroid": null, + "spatial_shape": null, + "theme": [ + "Earth Science" + ], + "title": "ISLSCP II Historical Croplands Cover, 1700-1992", "type": "dataset" }, { - "_score": 17.590618, + "_score": 12.251391, "_sort": [ - 1789603021200, - 17.590618, + 1790122660813, + 12.251391, 1, - "b9eaecc3-857d-495c-ab5f-5a4d22188160" + "1a79fd18-1e6a-4cb7-91db-78778c5b416d" ], "dcat": { + "@type": "dcat:Dataset", "accessLevel": "public", "bureauCode": [ - "010:12" + "026:00" ], "contactPoint": { "@type": "vcard:Contact", - "fn": "Randall J. Hunt", - "hasEmail": "mailto:rjhunt@usgs.gov" - }, - "description": "A GFLOW model was constructed of the Park Falls Unit as part of a larger study of the \nChequamegon-Nicolet National Forest. The model supports the goals of the project by \nproviding improved characterization of the groundwater/surface-water system and a tool \nto evaluate the sensitivity of hydrologic flows and temperature to future climate and land \nuse changes.", + "fn": "Earthdata Forum", + "hasEmail": "mailto:earthdata-support@nasa.gov" + }, + "description": "The Historical Land Cover and Land Use data set was developed to provide the global change community with historical land use estimates. The data set describes historical land use changes over a 300-year historical period (1700-1990).\n\nTesting against historical data is an important step for validating integrated models of global environmental change. Owing to long time lags in the climate and biogeochemical systems, these models should aim to simulate the land use dynamics for long periods, i.e., spanning decades to centuries. Developing such models requires an understanding of past and current trends and is therefore strongly data dependent. For this purpose, a historical database of the global environment has been developed: HYDE. Historical statistical inventories on agricultural land (census data, tax records, land surveys, etc) and different spatial analysis techniques were used to create a geographically-explicit data set of land use change, with a regular time interval. The data set can be used to test integrated models of global change. Continental-scale historical data were used for that period.", "distribution": [ { "@type": "dcat:Distribution", - "accessURL": "https://doi.org/10.5066/F7RV0KTV", - "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.f01ef6df-e461-43e1-b9cb-af561c85cfca.xml", - "format": "XML", + "conformsTo": "http://www.isotc211.org/2005/gmi", + "description": "The metadata's original source.", + "downloadURL": "https://cmr.earthdata.nasa.gov/search/concepts/C2784888644-ORNL_CLOUD.iso19115", + "format": "ISO", "mediaType": "text/xml", "title": "Original Metadata" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://daac.ornl.gov/graphics/browse/sdat-tds/967_1_fit.png", + "format": "PNG", + "mediaType": "image/png" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://data.ornldaac.earthdata.nasa.gov/protected/bundle/historic_landcover_xdeg_967.zip", + "format": "ZIP", + "mediaType": "application/zip" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://data.ornldaac.earthdata.nasa.gov/public/islscp_ii/vegetation/historic_landcover_xdeg/comp/0_historic_landcover_readme.txt", + "format": "TXT", + "mediaType": "text/plain" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://data.ornldaac.earthdata.nasa.gov/public/islscp_ii/vegetation/historic_landcover_xdeg/comp/1_historic_landcover_doc.pdf", + "format": "PDF", + "mediaType": "application/pdf" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://doi.org/10.3334/ORNLDAAC/967", + "format": "HTML", + "mediaType": "text/html" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://search.earthdata.nasa.gov/search/granules?p=C2784888644-ORNL_CLOUD", + "format": "BIN", + "mediaType": "application/octet-stream" } ], - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_f01ef6df-e461-43e1-b9cb-af561c85cfca", - "keyword": [ - "Ashland County", - "Chequamegon-Nicolet National Forest", - "GFLOW", - "Groundwater", - "Groundwater Model", - "InlandWaters", - "Iron County", - "Oneida County", - "PEST", - "Park Falls Unit", - "Precambrian bedrock", - "Price County", - "Soil-Water-Balance Code", - "USGS:f01ef6df-e461-43e1-b9cb-af561c85cfca", - "Vilas County", - "Wisconsin", - "environment", - "geoscientificInformation", - "inlandWaters", - "usgsgroundwatermodel" - ], - "modified": "2020-11-17T00:00:00Z", + "identifier": "10.3334/ORNLDAAC/967", + "keyword": [ + "earth-science-land-use-land-cover-land-surface-land-use-land-cover-classification", + "earth-science-surface-radiative-properties-land-surface-albedo", + "earth-science-surface-radiative-properties-land-surface-reflectance", + "earth-science-vegetation-biosphere-canopy-characteristics", + "earth-science-vegetation-biosphere-leaf-characteristics", + "earth-science-vegetation-biosphere-plant-characteristics", + "earth-science-vegetation-biosphere-vegetation-cover", + "earth-science-vegetation-biosphere-vegetation-index" + ], + "license": "https://www.usa.gov/government-works", + "modified": "2026-09-22", + "programCode": [ + "026:000" + ], "publisher": { "@type": "org:Organization", - "name": "U.S. Geological Survey" - }, - "spatial": "-90.532320, 45.573894, -89.884892, 46.041184", - "theme": [ - "geospatial" - ], - "title": "GFLOW groundwater flow model for the Park Falls Unit of the Chequamegon-Nicolet National Forest, Wisconsin" - }, - "description": "A GFLOW model was constructed of the Park Falls Unit as part of a larger study of the \nChequamegon-Nicolet National Forest. The model supports the goals of the project by \nproviding improved characterization of the groundwater/surface-water system and a tool \nto evaluate the sensitivity of hydrologic flows and temperature to future climate and land \nuse changes.", + "name": "ORNL_DAAC" + }, + "spatial": "[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -180.0, \"NorthBoundingCoordinate\": 90.0, \"EastBoundingCoordinate\": 180.0, \"SouthBoundingCoordinate\": -90.0}]]", + "temporal": "1700-01-01/1990-12-31", + "theme": [ + "Earth Science" + ], + "title": "ISLSCP II Historical Land Cover and Land Use, 1700-1990" + }, + "description": "The Historical Land Cover and Land Use data set was developed to provide the global change community with historical land use estimates. The data set describes historical land use changes over a 300-year historical period (1700-1990).\n\nTesting against historical data is an important step for validating integrated models of global environmental change. Owing to long time lags in the climate and biogeochemical systems, these models should aim to simulate the land use dynamics for long periods, i.e., spanning decades to centuries. Developing such models requires an understanding of past and current trends and is therefore strongly data dependent. For this purpose, a historical database of the global environment has been developed: HYDE. Historical statistical inventories on agricultural land (census data, tax records, land surveys, etc) and different spatial analysis techniques were used to create a geographically-explicit data set of land use change, with a regular time interval. The data set can be used to test integrated models of global change. Continental-scale historical data were used for that period.", "distribution_titles": [ - "Digital Data", "Original Metadata" ], - "harvest_record": "https://catalog.data.gov/harvest_record/39496c37-5890-4412-a029-eb9fa8157e00", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/39496c37-5890-4412-a029-eb9fa8157e00/raw", + "harvest_record": "https://catalog.data.gov/harvest_record/6d8dd9fa-b65a-4542-870b-fa017f99f97e", + "harvest_record_raw": "https://catalog.data.gov/harvest_record/6d8dd9fa-b65a-4542-870b-fa017f99f97e/raw", "has_download": true, "has_spatial": true, - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_f01ef6df-e461-43e1-b9cb-af561c85cfca", - "keyword": [ - "Ashland County", - "Chequamegon-Nicolet National Forest", - "GFLOW", - "Groundwater", - "Groundwater Model", - "InlandWaters", - "Iron County", - "Oneida County", - "PEST", - "Park Falls Unit", - "Precambrian bedrock", - "Price County", - "Soil-Water-Balance Code", - "USGS:f01ef6df-e461-43e1-b9cb-af561c85cfca", - "Vilas County", - "Wisconsin", - "environment", - "geoscientificInformation", - "inlandWaters", - "usgsgroundwatermodel" - ], - "last_harvested_date": "2026-09-16T23:57:01.200362", + "identifier": "10.3334/ORNLDAAC/967", + "keyword": [ + "earth-science-land-use-land-cover-land-surface-land-use-land-cover-classification", + "earth-science-surface-radiative-properties-land-surface-albedo", + "earth-science-surface-radiative-properties-land-surface-reflectance", + "earth-science-vegetation-biosphere-canopy-characteristics", + "earth-science-vegetation-biosphere-leaf-characteristics", + "earth-science-vegetation-biosphere-plant-characteristics", + "earth-science-vegetation-biosphere-vegetation-cover", + "earth-science-vegetation-biosphere-vegetation-index" + ], + "last_harvested_date": "2026-09-23T00:17:40.813471", "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", + "id": "f4ca4614-8901-409b-8553-2e994ad10023", + "logo": "https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png", + "name": "National Aeronautics and Space Administration", "organization_type": "Federal Government", - "slug": "doi" + "slug": "nasa" }, "parent_identifier": null, "popularity": 1, - "publisher": "U.S. Geological Survey", - "slug": "gflow-groundwater-flow-model-for-the-park-falls-unit-of-the-chequamegon-nicolet-national-f", - "spatial_centroid": { - "lat": 45.760810000000006, - "lon": -90.2733488 - }, - "spatial_shape": { - "coordinates": [ - [ - [ - -90.53232, - 45.573894 - ], - [ - -90.53232, - 46.041184 - ], - [ - -89.884892, - 46.041184 - ], - [ - -89.884892, - 45.573894 - ], - [ - -90.53232, - 45.573894 - ] - ] - ], - "type": "Polygon" - }, - "theme": [ - "geospatial" - ], - "title": "GFLOW groundwater flow model for the Park Falls Unit of the Chequamegon-Nicolet National Forest, Wisconsin", + "publisher": "ORNL_DAAC", + "slug": "islscp-ii-historical-land-cover-and-land-use-1700-1990", + "spatial_centroid": null, + "spatial_shape": null, + "theme": [ + "Earth Science" + ], + "title": "ISLSCP II Historical Land Cover and Land Use, 1700-1990", "type": "dataset" }, { - "_score": 12.275196, + "_score": 11.2865925, "_sort": [ - 1789601470073, - 12.275196, - 3, - "c5c0860e-eada-4094-92be-0d582f10ed06" + 1790122641757, + 11.2865925, + 2, + "6afe261f-ba7e-4d02-a1f6-b3968c01e98b" ], "dcat": { + "@type": "dcat:Dataset", "accessLevel": "public", "bureauCode": [ - "010:12" + "026:00" ], "contactPoint": { "@type": "vcard:Contact", - "fn": "Michael E. Wieczorek", - "hasEmail": "mailto:mewieczo@usgs.gov" - }, - "description": "This tabular data set represents the average daily minimum temperature in Celsius multiplied by 100 for 2002, \ncompiled for every MRB_E2RF1 catchment of selected Major River Basins (MRBs, Crawford and others, 2006). \nThe source data were the Near-Real-Time High-Resolution Monthly Average Maximum/Minimum Temperature for \nthe Conterminous United States for 2002 raster data set produced by the Spatial Climate Analysis Service at \nOregon State University.\n\t\t\nThe MRB_E2RF1 catchments are based on a modified version of the Environmental Protection Agency's (USEPA) \nERF1_2 and include enhancements to support national and regional-scale surface-water quality modeling \n(Nolan and others, 2002; Brakebill and others, 2011).\n\t\t\nData were compiled for every MRB_E2RF1 catchment for the conterminous United States covering New England and \nMid-Atlantic (MRB1), South Atlantic-Gulf and Tennessee (MRB2), the Great Lakes, Ohio, Upper Mississippi, and \nSouris-Red-Rainy (MRB3), the Missouri (MRB4), the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf (MRB5), \nthe Rio Grande, Colorado, and the Great basin (MRB6), the Pacific Northwest (MRB7) river basins, and California (MRB8).", + "fn": "Earthdata Forum", + "hasEmail": "mailto:earthdata-support@nasa.gov" + }, + "description": "This dataset provides estimates of greenness trends, above- and belowground carbon stocks, and climate variables of the persistent mangrove forests on the coasts of Mexico (PMFM) at a 1 km resolution from 2001 through 2015. Data are available as one-time estimates or across the temporal range; typically as monthly summaries. One-time estimates of aboveground carbon and soil organic carbon stocks for the PMFM derived from existing sources are provided. Also included are the monthly mean normalized difference vegetation index (NDVI) from MOD13A3 used to derive greenness trends, monthly mean air temperature, and total monthly precipitation from Daymet for 2001-2015 across the PMFM. Other files include the distribution and coverage of PMFM across Mexico. Distributions are provided as four categories of PMFM: (1) Arid mangroves with Surface Water as main input, along the Gulf of California and Pacific Coast (ARsw); (2) humid mangroves with surface water input along the Pacific Coast (HUsw-Pa); (3) humid mangroves with surface water input along the coast of the Gulf of Mexico (HUsw-Gf); (4) humid mangroves with groundwater input along the Gulf of Mexico and Caribbean Sea (HUgw). These data provide a baseline for national monitoring programs, carbon accounting models, and greenness trends in coastal wetlands.", "distribution": [ { "@type": "dcat:Distribution", - "accessURL": "https://doi.org/10.5066/P9EKKOEN", - "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.aaf1493e-d284-4b81-b5b3-a7bca1c13c63.xml", - "format": "XML", + "conformsTo": "http://www.isotc211.org/2005/gmi", + "description": "The metadata's original source.", + "downloadURL": "https://cmr.earthdata.nasa.gov/search/concepts/C2345881744-ORNL_CLOUD.iso19115", + "format": "ISO", "mediaType": "text/xml", "title": "Original Metadata" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://daac.ornl.gov/CMS/guides/CStocks_Greenness_Mangroves_MX_Fig1.jpg", + "format": "JPEG", + "mediaType": "image/jpeg" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://data.ornldaac.earthdata.nasa.gov/protected/bundle/CStocks_Greenness_Mangroves_MX_1853.zip", + "format": "ZIP", + "mediaType": "application/zip" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://data.ornldaac.earthdata.nasa.gov/public/cms/CStocks_Greenness_Mangroves_MX/comp/CStocks_Greenness_Mangroves_MX.pdf", + "format": "PDF", + "mediaType": "application/pdf" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://doi.org/10.3334/ORNLDAAC/1853", + "format": "HTML", + "mediaType": "text/html" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://search.earthdata.nasa.gov/search/granules?p=C2345881744-ORNL_CLOUD", + "format": "BIN", + "mediaType": "application/octet-stream" } ], - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_aaf1493e-d284-4b81-b5b3-a7bca1c13c63", - "keyword": [ - "Average monthly minimum temperature", - "CALI", - "COGB", - "California", - "Catchment", - "Conterminous United States", - "GLMR", - "Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy", - "Inland waters", - "LMTG", - "Lower Mississippi, Arkansas-White-Red, and Texas-Gulf", - "MORI", - "MRB", - "MRB1", - "MRB2", - "MRB3", - "MRB4", - "MRB5", - "MRB6", - "MRB7", - "MRB8", - "MRB_E2RF1", - "MRB_E2RF1WS", - "Major River Basins", - "Missouri", - "NAWQA", - "NEMA", - "New England and Mid-Atlantic", - "PANW", - "Pacific Northwest", - "Rio Grande, Colorado, and Great Basin", - "SAGT", - "SPARROW", - "South Atlantic-Gulf and Tennessee", - "USGS:aaf1493e-d284-4b81-b5b3-a7bca1c13c63", - "environment", - "geoscientificInformation", - "inlandWaters" - ], - "modified": "2020-11-17T00:00:00Z", + "identifier": "10.3334/ORNLDAAC/1853", + "keyword": [ + "earth-science-ecosystems-biosphere-marine-ecosystems", + "earth-science-land-use-land-cover-land-surface", + "earth-science-soils-land-surface-carbon", + "earth-science-vegetation-biosphere-vegetation-index" + ], + "license": "https://www.usa.gov/government-works", + "modified": "2026-09-22", + "programCode": [ + "026:000" + ], "publisher": { "@type": "org:Organization", - "name": "U.S. Geological Survey" - }, - "spatial": "-127.910792, 23.243486, -65.327751, 51.657387", - "theme": [ - "geospatial" - ], - "title": "Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: Average Daily Minimum Temperature, 2002" - }, - "description": "This tabular data set represents the average daily minimum temperature in Celsius multiplied by 100 for 2002, \ncompiled for every MRB_E2RF1 catchment of selected Major River Basins (MRBs, Crawford and others, 2006). \nThe source data were the Near-Real-Time High-Resolution Monthly Average Maximum/Minimum Temperature for \nthe Conterminous United States for 2002 raster data set produced by the Spatial Climate Analysis Service at \nOregon State University.\n\t\t\nThe MRB_E2RF1 catchments are based on a modified version of the Environmental Protection Agency's (USEPA) \nERF1_2 and include enhancements to support national and regional-scale surface-water quality modeling \n(Nolan and others, 2002; Brakebill and others, 2011).\n\t\t\nData were compiled for every MRB_E2RF1 catchment for the conterminous United States covering New England and \nMid-Atlantic (MRB1), South Atlantic-Gulf and Tennessee (MRB2), the Great Lakes, Ohio, Upper Mississippi, and \nSouris-Red-Rainy (MRB3), the Missouri (MRB4), the Lower Mississippi, Arkansas-White-Red, and Texas-Gulf (MRB5), \nthe Rio Grande, Colorado, and the Great basin (MRB6), the Pacific Northwest (MRB7) river basins, and California (MRB8).", + "name": "ORNL_DAAC" + }, + "spatial": "[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -114.055, \"NorthBoundingCoordinate\": 29.7262, \"EastBoundingCoordinate\": -86.5302, \"SouthBoundingCoordinate\": 14.4292}]]", + "temporal": "2001-01-01/2015-12-31", + "theme": [ + "Earth Science" + ], + "title": "Greenness Trends and Carbon Stocks of Mangrove Forests Across Mexico, 2001-2015" + }, + "description": "This dataset provides estimates of greenness trends, above- and belowground carbon stocks, and climate variables of the persistent mangrove forests on the coasts of Mexico (PMFM) at a 1 km resolution from 2001 through 2015. Data are available as one-time estimates or across the temporal range; typically as monthly summaries. One-time estimates of aboveground carbon and soil organic carbon stocks for the PMFM derived from existing sources are provided. Also included are the monthly mean normalized difference vegetation index (NDVI) from MOD13A3 used to derive greenness trends, monthly mean air temperature, and total monthly precipitation from Daymet for 2001-2015 across the PMFM. Other files include the distribution and coverage of PMFM across Mexico. Distributions are provided as four categories of PMFM: (1) Arid mangroves with Surface Water as main input, along the Gulf of California and Pacific Coast (ARsw); (2) humid mangroves with surface water input along the Pacific Coast (HUsw-Pa); (3) humid mangroves with surface water input along the coast of the Gulf of Mexico (HUsw-Gf); (4) humid mangroves with groundwater input along the Gulf of Mexico and Caribbean Sea (HUgw). These data provide a baseline for national monitoring programs, carbon accounting models, and greenness trends in coastal wetlands.", "distribution_titles": [ - "Digital Data", "Original Metadata" ], - "harvest_record": "https://catalog.data.gov/harvest_record/3a39a47d-a77b-4492-a70f-bc29afbebb79", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/3a39a47d-a77b-4492-a70f-bc29afbebb79/raw", + "harvest_record": "https://catalog.data.gov/harvest_record/fdb20d88-8e18-43d4-a4d1-bcd765e7a40b", + "harvest_record_raw": "https://catalog.data.gov/harvest_record/fdb20d88-8e18-43d4-a4d1-bcd765e7a40b/raw", "has_download": true, "has_spatial": true, - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_aaf1493e-d284-4b81-b5b3-a7bca1c13c63", - "keyword": [ - "Average monthly minimum temperature", - "CALI", - "COGB", - "California", - "Catchment", - "Conterminous United States", - "GLMR", - "Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy", - "Inland waters", - "LMTG", - "Lower Mississippi, Arkansas-White-Red, and Texas-Gulf", - "MORI", - "MRB", - "MRB1", - "MRB2", - "MRB3", - "MRB4", - "MRB5", - "MRB6", - "MRB7", - "MRB8", - "MRB_E2RF1", - "MRB_E2RF1WS", - "Major River Basins", - "Missouri", - "NAWQA", - "NEMA", - "New England and Mid-Atlantic", - "PANW", - "Pacific Northwest", - "Rio Grande, Colorado, and Great Basin", - "SAGT", - "SPARROW", - "South Atlantic-Gulf and Tennessee", - "USGS:aaf1493e-d284-4b81-b5b3-a7bca1c13c63", - "environment", - "geoscientificInformation", - "inlandWaters" - ], - "last_harvested_date": "2026-09-16T23:31:10.073236", + "identifier": "10.3334/ORNLDAAC/1853", + "keyword": [ + "earth-science-ecosystems-biosphere-marine-ecosystems", + "earth-science-land-use-land-cover-land-surface", + "earth-science-soils-land-surface-carbon", + "earth-science-vegetation-biosphere-vegetation-index" + ], + "last_harvested_date": "2026-09-23T00:17:21.757413", "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", + "id": "f4ca4614-8901-409b-8553-2e994ad10023", + "logo": "https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png", + "name": "National Aeronautics and Space Administration", "organization_type": "Federal Government", - "slug": "doi" + "slug": "nasa" }, "parent_identifier": null, - "popularity": 3, - "publisher": "U.S. Geological Survey", - "slug": "attributes-for-mrb_e2rf1-catchments-by-major-river-basins-in-the-conterminous-united--2002", - "spatial_centroid": { - "lat": 34.6090464, - "lon": -102.8775756 - }, - "spatial_shape": { - "coordinates": [ - [ - [ - -127.910792, - 23.243486 - ], - [ - -127.910792, - 51.657387 - ], - [ - -65.327751, - 51.657387 - ], - [ - -65.327751, - 23.243486 - ], - [ - -127.910792, - 23.243486 - ] - ] - ], - "type": "Polygon" - }, - "theme": [ - "geospatial" - ], - "title": "Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: Average Daily Minimum Temperature, 2002", + "popularity": 2, + "publisher": "ORNL_DAAC", + "slug": "greenness-trends-and-carbon-stocks-of-mangrove-forests-across-mexico-2001-2015", + "spatial_centroid": null, + "spatial_shape": null, + "theme": [ + "Earth Science" + ], + "title": "Greenness Trends and Carbon Stocks of Mangrove Forests Across Mexico, 2001-2015", "type": "dataset" }, { - "_score": 20.382847, + "_score": 15.599131, "_sort": [ - 1789601190892, - 20.382847, - 2, - "6e42dd7b-c9fe-4103-b683-982ef9f54847" + 1790122631000, + 15.599131, + 1, + "5841b7e6-dc31-4038-89ee-5225047e42ec" ], "dcat": { + "@type": "dcat:Dataset", "accessLevel": "public", "bureauCode": [ - "010:12" + "026:00" ], "contactPoint": { "@type": "vcard:Contact", - "fn": "New Jersey Water Science Center", - "hasEmail": "mailto:gs-w-nj_datarelease@usgs.gov" - }, - "description": "A MODFLOW-2005 model, using the SWI2 package, was developed for the Sandy Hook Unit, \nGateway National Recreation Area (hereafter Sandy Hook) in New Jersey to evaluate the \nresponse of groundwater resources to expected sea-level rise (SLR) and changes in \ngroundwater recharge associated with global climate change. The National Park Service (NPS), \namong other agencies, is mandated to evaluate the effects of global climate change on NPS \nparks and promote resiliency and sustainability of park resources to the extent possible. Sandy \nHook is visited by thousands of people each year who take advantage of the historical and natural \nresources and recreational opportunities which are threatened by global climate change, including \nSLR, changes in precipitation and groundwater recharge, and changes in the frequency and \nseverity of coastal storms. Fresh groundwater resources are important to the ecosystems of \nSandy Hook. The Bayside Holly Forest, one of only two known old-growth American holly \n(Ilex opaca) maritime forests, is particularly vulnerable to global climate change because of the \nproximity of the water table to land surface in low-lying areas and the potential for saltwater \nintrusion and inundation. Groundwater-flow simulations completed for this study include a \nBaseline scenario, three SLR scenarios (0.2, 0.4, and 0.6 meters [m]), two Recharge \nscenarios—a 10-percent Increased Recharge scenario and a 10-percent Decreased Recharge \nscenario—and a scenario with 0.6 m of SLR and 10-percent increase in recharge. Understanding \nthe possible effects of SLR and changes in recharge will allow the NPS to allocate scarce \nresources to best prepare for and manage climate-change-driven changes in the groundwater \nsystem and the subsequent effects on park ecosystems. This USGS data release contains \nall of the input and output files for the simulations described in the associated model \ndocumentation report (https://doi.org/10.3133/sir20205080).", + "fn": "Earthdata Forum", + "hasEmail": "mailto:earthdata-support@nasa.gov" + }, + "description": "This data set was developed to describe the state of the global land cover in terms of 15 major vegetation types, plus water, before alteration by humans. It forms a complement to the historical croplands data set developed by Ramankutty and Foley (1999). By overlaying the two, one can determine the extent to which natural vegetation has been cleared for cultivation. This data set can be used directly within spatially-explicit climate and biogeochemical models. There are four total files in this data set. Two files contain the land cover types representing potential natural vegetation before human alteration, and two other files contain those points in the original data set submitted by the Principal Investigator that have been modified in order to match the land/water mask of the ISLSCP Initiative II.\r\n\r\nThe geographic distribution of contemporary land cover types can be derived from remotely-sensed data. However, humans now dominate much of the world and there is little evidence of the pre-human-settlement natural vegetation or Potential Natural Vegetation (PNV). PNV, as defined here, does not necessarily represent the world'??s natural pre-human-disturbance vegetation. Rather, our definition of PNV represents the world's vegetation cover that would most likely exist now in equilibrium with present-day climate and natural disturbance, in the absence of human activities.", "distribution": [ { "@type": "dcat:Distribution", - "accessURL": "https://doi.org/10.5066/F7BP018M", - "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.d806c8b2-60ce-4a4c-9460-7002e2b6b0ce.xml", - "format": "XML", + "conformsTo": "http://www.isotc211.org/2005/gmi", + "description": "The metadata's original source.", + "downloadURL": "https://cmr.earthdata.nasa.gov/search/concepts/C2784887174-ORNL_CLOUD.iso19115", + "format": "ISO", "mediaType": "text/xml", "title": "Original Metadata" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://daac.ornl.gov/graphics/browse/sdat-tds/961_1_fit.png", + "format": "PNG", + "mediaType": "image/png" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://data.ornldaac.earthdata.nasa.gov/protected/bundle/potential_veg_xdeg_961.zip", + "format": "ZIP", + "mediaType": "application/zip" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://data.ornldaac.earthdata.nasa.gov/public/islscp_ii/vegetation/potential_veg_xdeg/comp/0_potential_veg_readme.txt", + "format": "TXT", + "mediaType": "text/plain" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://data.ornldaac.earthdata.nasa.gov/public/islscp_ii/vegetation/potential_veg_xdeg/comp/1_potential_veg_doc.pdf", + "format": "PDF", + "mediaType": "application/pdf" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://doi.org/10.3334/ORNLDAAC/961", + "format": "HTML", + "mediaType": "text/html" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://search.earthdata.nasa.gov/search/granules?p=C2784887174-ORNL_CLOUD", + "format": "BIN", + "mediaType": "application/octet-stream" } ], - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_d806c8b2-60ce-4a4c-9460-7002e2b6b0ce", - "keyword": [ - "Gateway National Recreation Area", - "Groundwater", - "Groundwater Model", - "MODFLOW-2005", - "Monmouth County", - "New Jersey", - "SWI2", - "Saltwater Intrusion", - "Sandy Hook", - "Sea-Level Rise", - "USGS:d806c8b2-60ce-4a4c-9460-7002e2b6b0ce", - "environment", - "geoscientificInformation", - "inlandWaters", - "usgsgroundwatermodel" - ], - "modified": "2021-07-07T00:00:00Z", + "identifier": "10.3334/ORNLDAAC/961", + "keyword": [ + "earth-science-land-use-land-cover-land-surface-land-use-land-cover-classification", + "earth-science-surface-radiative-properties-land-surface-reflectance", + "earth-science-vegetation-biosphere-deciduous-vegetation", + "earth-science-vegetation-biosphere-vegetation-cover", + "earth-science-vegetation-biosphere-vegetation-index" + ], + "license": "https://www.usa.gov/government-works", + "modified": "2026-09-22", + "programCode": [ + "026:000" + ], "publisher": { "@type": "org:Organization", - "name": "U.S. Geological Survey" - }, - "spatial": "-74.026267, 40.398602, -73.971351, 40.484865", - "theme": [ - "geospatial" - ], - "title": "MODFLOW-2005 with SWI2 used to evaluate the water-table response to sea-level rise and change in recharge, Sandy Hook Unit, Gateway National Recreation Area, New Jersey" - }, - "description": "A MODFLOW-2005 model, using the SWI2 package, was developed for the Sandy Hook Unit, \nGateway National Recreation Area (hereafter Sandy Hook) in New Jersey to evaluate the \nresponse of groundwater resources to expected sea-level rise (SLR) and changes in \ngroundwater recharge associated with global climate change. The National Park Service (NPS), \namong other agencies, is mandated to evaluate the effects of global climate change on NPS \nparks and promote resiliency and sustainability of park resources to the extent possible. Sandy \nHook is visited by thousands of people each year who take advantage of the historical and natural \nresources and recreational opportunities which are threatened by global climate change, including \nSLR, changes in precipitation and groundwater recharge, and changes in the frequency and \nseverity of coastal storms. Fresh groundwater resources are important to the ecosystems of \nSandy Hook. The Bayside Holly Forest, one of only two known old-growth American holly \n(Ilex opaca) maritime forests, is particularly vulnerable to global climate change because of the \nproximity of the water table to land surface in low-lying areas and the potential for saltwater \nintrusion and inundation. Groundwater-flow simulations completed for this study include a \nBaseline scenario, three SLR scenarios (0.2, 0.4, and 0.6 meters [m]), two Recharge \nscenarios—a 10-percent Increased Recharge scenario and a 10-percent Decreased Recharge \nscenario—and a scenario with 0.6 m of SLR and 10-percent increase in recharge. Understanding \nthe possible effects of SLR and changes in recharge will allow the NPS to allocate scarce \nresources to best prepare for and manage climate-change-driven changes in the groundwater \nsystem and the subsequent effects on park ecosystems. This USGS data release contains \nall of the input and output files for the simulations described in the associated model \ndocumentation report (https://doi.org/10.3133/sir20205080).", + "name": "ORNL_DAAC" + }, + "spatial": "[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -180.0, \"NorthBoundingCoordinate\": 90.0, \"EastBoundingCoordinate\": 180.0, \"SouthBoundingCoordinate\": -90.0}]]", + "temporal": "1992-04-01/1993-04-01", + "theme": [ + "Earth Science" + ], + "title": "ISLSCP II Potential Natural Vegetation Cover" + }, + "description": "This data set was developed to describe the state of the global land cover in terms of 15 major vegetation types, plus water, before alteration by humans. It forms a complement to the historical croplands data set developed by Ramankutty and Foley (1999). By overlaying the two, one can determine the extent to which natural vegetation has been cleared for cultivation. This data set can be used directly within spatially-explicit climate and biogeochemical models. There are four total files in this data set. Two files contain the land cover types representing potential natural vegetation before human alteration, and two other files contain those points in the original data set submitted by the Principal Investigator that have been modified in order to match the land/water mask of the ISLSCP Initiative II.\r\n\r\nThe geographic distribution of contemporary land cover types can be derived from remotely-sensed data. However, humans now dominate much of the world and there is little evidence of the pre-human-settlement natural vegetation or Potential Natural Vegetation (PNV). PNV, as defined here, does not necessarily represent the world'??s natural pre-human-disturbance vegetation. Rather, our definition of PNV represents the world's vegetation cover that would most likely exist now in equilibrium with present-day climate and natural disturbance, in the absence of human activities.", "distribution_titles": [ - "Digital Data", "Original Metadata" ], - "harvest_record": "https://catalog.data.gov/harvest_record/529c1a55-6ed8-451c-863b-2b9729e0911f", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/529c1a55-6ed8-451c-863b-2b9729e0911f/raw", + "harvest_record": "https://catalog.data.gov/harvest_record/b2511173-6f20-41c5-9fe2-d517e83d0588", + "harvest_record_raw": "https://catalog.data.gov/harvest_record/b2511173-6f20-41c5-9fe2-d517e83d0588/raw", "has_download": true, "has_spatial": true, - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_d806c8b2-60ce-4a4c-9460-7002e2b6b0ce", - "keyword": [ - "Gateway National Recreation Area", - "Groundwater", - "Groundwater Model", - "MODFLOW-2005", - "Monmouth County", - "New Jersey", - "SWI2", - "Saltwater Intrusion", - "Sandy Hook", - "Sea-Level Rise", - "USGS:d806c8b2-60ce-4a4c-9460-7002e2b6b0ce", - "environment", - "geoscientificInformation", - "inlandWaters", - "usgsgroundwatermodel" - ], - "last_harvested_date": "2026-09-16T23:26:30.892784", + "identifier": "10.3334/ORNLDAAC/961", + "keyword": [ + "earth-science-land-use-land-cover-land-surface-land-use-land-cover-classification", + "earth-science-surface-radiative-properties-land-surface-reflectance", + "earth-science-vegetation-biosphere-deciduous-vegetation", + "earth-science-vegetation-biosphere-vegetation-cover", + "earth-science-vegetation-biosphere-vegetation-index" + ], + "last_harvested_date": "2026-09-23T00:17:11.000862", "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", + "id": "f4ca4614-8901-409b-8553-2e994ad10023", + "logo": "https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png", + "name": "National Aeronautics and Space Administration", "organization_type": "Federal Government", - "slug": "doi" + "slug": "nasa" }, "parent_identifier": null, - "popularity": 2, - "publisher": "U.S. Geological Survey", - "slug": "modflow-2005-with-swi2-used-to-evaluate-the-water-table-response-to-sea-level-rise-and-cha", - "spatial_centroid": { - "lat": 40.433107199999995, - "lon": -74.0043006 - }, - "spatial_shape": { - "coordinates": [ - [ - [ - -74.026267, - 40.398602 - ], - [ - -74.026267, - 40.484865 - ], - [ - -73.971351, - 40.484865 - ], - [ - -73.971351, - 40.398602 - ], - [ - -74.026267, - 40.398602 - ] - ] - ], - "type": "Polygon" - }, - "theme": [ - "geospatial" - ], - "title": "MODFLOW-2005 with SWI2 used to evaluate the water-table response to sea-level rise and change in recharge, Sandy Hook Unit, Gateway National Recreation Area, New Jersey", + "popularity": 1, + "publisher": "ORNL_DAAC", + "slug": "islscp-ii-potential-natural-vegetation-cover", + "spatial_centroid": null, + "spatial_shape": null, + "theme": [ + "Earth Science" + ], + "title": "ISLSCP II Potential Natural Vegetation Cover", "type": "dataset" }, { - "_score": 11.974232, + "_score": 14.388378, "_sort": [ - 1789601046003, - 11.974232, - 4, - "d17743ff-0310-40cb-87e2-831dda5dbf61" + 1790122629903, + 14.388378, + 2, + "c4ed95f1-f4ae-4a04-9a42-1148af6245f7" ], "dcat": { + "@type": "dcat:Dataset", "accessLevel": "public", "bureauCode": [ - "010:12" + "026:00" ], "contactPoint": { "@type": "vcard:Contact", - "fn": "Fred D Tillman", - "hasEmail": "mailto:ftillman@usgs.gov" - }, - "description": "The Colorado River and its tributaries supply water to more than 35 million people in the United States \nand 3 million people in Mexico, irrigating more than 4.5 million acres of farmland, and generating about \n12 billion kilowatt hours of hydroelectric power annually. Planning for the sustainable management of \nthe Colorado River in future climates requires an understanding of the Upper Colorado River Basin \ngroundwater system. The Upper Colorado River Basin, encompassing more than 110,000 square \nmiles (mi2), contains the headwaters of the Colorado River and is an important source of snowmelt \nrunoff to the River. Groundwater discharge also is an important source of water in the River and its \ntributaries, with estimates ranging from 21 to 58 percent of streamflow in the upper basin.\n\t\t\t\nA study by Castle and others (2014) using remotely sensed gravity observations from the NASA \nGravity Recovery and Climate Experiment (GRACE) mission found that UCRB groundwater was \ndepleted by more than 17 million acre-feet (ft) from December 2004 to November 2013. Understanding \ngroundwater-budget components, including groundwater recharge, is important to sustainably \nmanage both groundwater and surface-water supplies in the Colorado River Basin.", + "fn": "Earthdata Forum", + "hasEmail": "mailto:earthdata-support@nasa.gov" + }, + "description": "The University of New Hampshire (UNH)/Global Runoff Data Centre (GRDC) composite runoff data combines simulated water balance model runoff estimates derived from climate forcing with monitored river discharge. It can be viewed as a data assimilation applied in a water balance model context (conceptually similar to the commonly used 4DDA techniques used in meteorological modeling). Such a data assimilation scheme preserves the spatial specificity of the water balance calculations while constrained by the more accurate discharge measurement. There are 11 data files in this data set and 1 changemap file which shows the differences between the ISLSCP II land/water mask and the original data set.", "distribution": [ { "@type": "dcat:Distribution", - "accessURL": "https://doi.org/10.5066/P9ZFQFJD", - "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.850b5cf3-7b38-4a2e-bb0a-4b91f6b6332f.xml", - "format": "XML", + "conformsTo": "http://www.isotc211.org/2005/gmi", + "description": "The metadata's original source.", + "downloadURL": "https://cmr.earthdata.nasa.gov/search/concepts/C2784897571-ORNL_CLOUD.iso19115", + "format": "ISO", "mediaType": "text/xml", "title": "Original Metadata" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://daac.ornl.gov/graphics/browse/sdat-tds/994_1_fit.png", + "format": "PNG", + "mediaType": "image/png" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://data.ornldaac.earthdata.nasa.gov/protected/bundle/comp_runoff_monthly_xdeg_994.zip", + "format": "ZIP", + "mediaType": "application/zip" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://data.ornldaac.earthdata.nasa.gov/public/islscp_ii/hydrology_soils/comp_runoff_monthly_xdeg/comp/0_comp_runoff_month_readme.txt", + "format": "TXT", + "mediaType": "text/plain" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://data.ornldaac.earthdata.nasa.gov/public/islscp_ii/hydrology_soils/comp_runoff_monthly_xdeg/comp/1_comp_runoff_month_doc.pdf", + "format": "PDF", + "mediaType": "application/pdf" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://doi.org/10.3334/ORNLDAAC/994", + "format": "HTML", + "mediaType": "text/html" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://search.earthdata.nasa.gov/search/granules?p=C2784897571-ORNL_CLOUD", + "format": "BIN", + "mediaType": "application/octet-stream" } ], - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_850b5cf3-7b38-4a2e-bb0a-4b91f6b6332f", - "keyword": [ - "Arizona", - "California", - "Colorado", - "DCHP", - "Daymet", - "Nevada", - "New Mexico", - "USGS:850b5cf3-7b38-4a2e-bb0a-4b91f6b6332f", - "Upper Colorado River Basin", - "Utah", - "Wyoming", - "environment", - "geoscientificInformation", - "groundwater", - "groundwater recharge", - "inlandWaters", - "soil-water balance" - ], - "modified": "2020-11-17T00:00:00Z", + "identifier": "10.3334/ORNLDAAC/994", + "keyword": [ + "earth-science-ecological-dynamics-biosphere-ecosystem-functions", + "earth-science-ecosystems-biosphere-terrestrial-ecosystems", + "earth-science-topography-land-surface-topographic-effects" + ], + "license": "https://www.usa.gov/government-works", + "modified": "2026-09-22", + "programCode": [ + "026:000" + ], "publisher": { "@type": "org:Organization", - "name": "U.S. Geological Survey" - }, - "spatial": "-113.920363928, 34.965779618, -105.25, 43.986766736", - "theme": [ - "geospatial" - ], - "title": "Input Digital Datasets for the Soil-Water Balance Groundwater Recharge Model of the Upper Colorado River Basin" - }, - "description": "The Colorado River and its tributaries supply water to more than 35 million people in the United States \nand 3 million people in Mexico, irrigating more than 4.5 million acres of farmland, and generating about \n12 billion kilowatt hours of hydroelectric power annually. Planning for the sustainable management of \nthe Colorado River in future climates requires an understanding of the Upper Colorado River Basin \ngroundwater system. The Upper Colorado River Basin, encompassing more than 110,000 square \nmiles (mi2), contains the headwaters of the Colorado River and is an important source of snowmelt \nrunoff to the River. Groundwater discharge also is an important source of water in the River and its \ntributaries, with estimates ranging from 21 to 58 percent of streamflow in the upper basin.\n\t\t\t\nA study by Castle and others (2014) using remotely sensed gravity observations from the NASA \nGravity Recovery and Climate Experiment (GRACE) mission found that UCRB groundwater was \ndepleted by more than 17 million acre-feet (ft) from December 2004 to November 2013. Understanding \ngroundwater-budget components, including groundwater recharge, is important to sustainably \nmanage both groundwater and surface-water supplies in the Colorado River Basin.", + "name": "ORNL_DAAC" + }, + "spatial": "[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -180.0, \"NorthBoundingCoordinate\": 90.0, \"EastBoundingCoordinate\": 180.0, \"SouthBoundingCoordinate\": -90.0}]]", + "temporal": "1986-01-01/1995-12-31", + "theme": [ + "Earth Science" + ], + "title": "ISLSCP II UNH/GRDC Composite Monthly Runoff" + }, + "description": "The University of New Hampshire (UNH)/Global Runoff Data Centre (GRDC) composite runoff data combines simulated water balance model runoff estimates derived from climate forcing with monitored river discharge. It can be viewed as a data assimilation applied in a water balance model context (conceptually similar to the commonly used 4DDA techniques used in meteorological modeling). Such a data assimilation scheme preserves the spatial specificity of the water balance calculations while constrained by the more accurate discharge measurement. There are 11 data files in this data set and 1 changemap file which shows the differences between the ISLSCP II land/water mask and the original data set.", "distribution_titles": [ - "Digital Data", "Original Metadata" ], - "harvest_record": "https://catalog.data.gov/harvest_record/3ccb6523-9b4b-49f1-bbea-1cc383c58929", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/3ccb6523-9b4b-49f1-bbea-1cc383c58929/raw", + "harvest_record": "https://catalog.data.gov/harvest_record/f24468cb-877e-4c76-a456-f042e729522c", + "harvest_record_raw": "https://catalog.data.gov/harvest_record/f24468cb-877e-4c76-a456-f042e729522c/raw", "has_download": true, "has_spatial": true, - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_850b5cf3-7b38-4a2e-bb0a-4b91f6b6332f", - "keyword": [ - "Arizona", - "California", - "Colorado", - "DCHP", - "Daymet", - "Nevada", - "New Mexico", - "USGS:850b5cf3-7b38-4a2e-bb0a-4b91f6b6332f", - "Upper Colorado River Basin", - "Utah", - "Wyoming", - "environment", - "geoscientificInformation", - "groundwater", - "groundwater recharge", - "inlandWaters", - "soil-water balance" - ], - "last_harvested_date": "2026-09-16T23:24:06.003803", + "identifier": "10.3334/ORNLDAAC/994", + "keyword": [ + "earth-science-ecological-dynamics-biosphere-ecosystem-functions", + "earth-science-ecosystems-biosphere-terrestrial-ecosystems", + "earth-science-topography-land-surface-topographic-effects" + ], + "last_harvested_date": "2026-09-23T00:17:09.903628", "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", + "id": "f4ca4614-8901-409b-8553-2e994ad10023", + "logo": "https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png", + "name": "National Aeronautics and Space Administration", "organization_type": "Federal Government", - "slug": "doi" + "slug": "nasa" }, "parent_identifier": null, - "popularity": 4, - "publisher": "U.S. Geological Survey", - "slug": "input-digital-datasets-for-the-soil-water-balance-groundwater-recharge-model-of-the-upper-", - "spatial_centroid": { - "lat": 38.574174465199995, - "lon": -110.45221835679999 - }, - "spatial_shape": { - "coordinates": [ - [ - [ - -113.920363928, - 34.965779618 - ], - [ - -113.920363928, - 43.986766736 - ], - [ - -105.25, - 43.986766736 - ], - [ - -105.25, - 34.965779618 - ], - [ - -113.920363928, - 34.965779618 - ] - ] - ], - "type": "Polygon" - }, - "theme": [ - "geospatial" - ], - "title": "Input Digital Datasets for the Soil-Water Balance Groundwater Recharge Model of the Upper Colorado River Basin", + "popularity": 2, + "publisher": "ORNL_DAAC", + "slug": "islscp-ii-unh-grdc-composite-monthly-runoff", + "spatial_centroid": null, + "spatial_shape": null, + "theme": [ + "Earth Science" + ], + "title": "ISLSCP II UNH/GRDC Composite Monthly Runoff", "type": "dataset" }, { - "_score": 24.01099, + "_score": 7.8486943, "_sort": [ - 1789601012177, - 24.01099, - 3, - "ce120dc2-fe52-439c-b58d-ed71cb442150" + 1790122628444, + 7.8486943, + 1, + "555e1a5c-631a-4266-8538-a29ebdce1d5b" ], "dcat": { + "@type": "dcat:Dataset", "accessLevel": "public", "bureauCode": [ - "010:12" + "026:00" ], "contactPoint": { "@type": "vcard:Contact", - "fn": "Fred D Tillman", - "hasEmail": "mailto:ftillman@usgs.gov" - }, - "description": "overland_flow_direction_UCRB_Maurer_resolution.asc is an Esri ASCII grid representing overland \nflow direction in the Upper Colorado River Basin using the D8 flow-routing convention.", + "fn": "Earthdata Forum", + "hasEmail": "mailto:earthdata-support@nasa.gov" + }, + "description": "The GPM Ground Validation Airborne Snow Observatory (ASO) OLYMPEX dataset consists of snow depth, bare earth surface, land surface classification and a Red, Green, Blue (RGB) composite image, provided at 3 m spatial resolution during the GPM Ground Validation Olympic Mountains Experiment (OLYMPEX) field campaign held in the Pacific Northwest. These data were collected by a Riegl Q1560 scanning LiDAR and an ITRES CASI-1500 imaging spectrometer , both part of the NASA Airborne Snow Observatory (ASO), during two separate periods, February 8-9, 2016 and March 29-30, 2016. A previous September 2014 flight was used to obtain no-snow measurements used for deriving snow depth. The data are provided in GeoTIFF format.", "distribution": [ { "@type": "dcat:Distribution", - "accessURL": "https://doi.org/10.5066/P9DW3W86", - "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.f4f235c4-7666-4ba3-bd7d-0b9b56ae1fda.xml", - "format": "XML", + "conformsTo": "http://www.isotc211.org/2005/gmi", + "description": "The metadata's original source.", + "downloadURL": "https://cmr.earthdata.nasa.gov/search/concepts/C1979129209-GHRC_DAAC.iso19115", + "format": "ISO", "mediaType": "text/xml", "title": "Original Metadata" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "http://dx.doi.org/10.5067/GPMGV/OLYMPEX/DATA101", + "format": "HTML", + "mediaType": "text/html" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "http://olympex.atmos.washington.edu/", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://doi.org/10.1016/j.rse.2016.06.018", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://doi.org/10.1175/JHM-D-17-0076.1", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://dx.doi.org/10.1109/TGRS.2006.890412", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://dx.doi.org/10.1175/BAMS-D-16-0182.1", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://ghrc.earthdata.nasa.gov/browseui/#pub/gpmasoolyx__1/docs/gpmasoolyx_dataset.pdf", + "format": "PDF", + "mediaType": "application/pdf" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://ghrc.nsstc.nasa.gov/home/about-ghrc/citing-ghrc-daac-data", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://ghrc.nsstc.nasa.gov/home/field-campaigns/olympex", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://search.earthdata.nasa.gov/search/granules?p=C1979129209-GHRC_DAAC", + "format": "BIN", + "mediaType": "application/octet-stream" } ], - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_f4f235c4-7666-4ba3-bd7d-0b9b56ae1fda", - "keyword": [ - "Arizona", - "California", - "Colorado", - "Nevada", - "New Mexico", - "USGS:f4f235c4-7666-4ba3-bd7d-0b9b56ae1fda", - "Upper Colorado River Basin", - "Utah", - "Wyoming", - "environment", - "geoscientificInformation", - "groundwater", - "groundwater recharge", - "inlandWaters", - "overland flow direction" - ], - "modified": "2020-11-17T00:00:00Z", + "identifier": "10.5067/GPMGV/OLYMPEX/LIDAR/DATA101", + "keyword": [ + "earth-science-cryospheric-indicators-climate-indicators-snow-depth", + "earth-science-land-use-land-cover-land-surface-land-use-land-cover-classification", + "earth-science-topography-land-surface-terrain-elevation", + "earth-science-visible-wavelengths-spectral-engineering-visible-imagery" + ], + "license": "https://www.usa.gov/government-works", + "modified": "2026-09-22", + "programCode": [ + "026:000" + ], "publisher": { "@type": "org:Organization", - "name": "U.S. Geological Survey" - }, - "spatial": "-112.625, 35.125, -105.25, 43.75", - "theme": [ - "geospatial" - ], - "title": "Overland Flow Direction Information for the Upper Colorado River Basin in Maurer et al. (2002) Climate Data resolution (overland_flow_direction_UCRB_Maurer_resolution.asc)" - }, - "description": "overland_flow_direction_UCRB_Maurer_resolution.asc is an Esri ASCII grid representing overland \nflow direction in the Upper Colorado River Basin using the D8 flow-routing convention.", + "name": "NASA/MSFC/GHRC" + }, + "spatial": "[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -124.185, \"NorthBoundingCoordinate\": 48.0909, \"EastBoundingCoordinate\": -123.129, \"SouthBoundingCoordinate\": 47.493}]]", + "temporal": "2014-09-04/2016-03-30", + "theme": [ + "Earth Science" + ], + "title": "GPM Ground Validation Airborne Snow Observatory (ASO) OLYMPEX V1" + }, + "description": "The GPM Ground Validation Airborne Snow Observatory (ASO) OLYMPEX dataset consists of snow depth, bare earth surface, land surface classification and a Red, Green, Blue (RGB) composite image, provided at 3 m spatial resolution during the GPM Ground Validation Olympic Mountains Experiment (OLYMPEX) field campaign held in the Pacific Northwest. These data were collected by a Riegl Q1560 scanning LiDAR and an ITRES CASI-1500 imaging spectrometer , both part of the NASA Airborne Snow Observatory (ASO), during two separate periods, February 8-9, 2016 and March 29-30, 2016. A previous September 2014 flight was used to obtain no-snow measurements used for deriving snow depth. The data are provided in GeoTIFF format.", "distribution_titles": [ - "Digital Data", "Original Metadata" ], - "harvest_record": "https://catalog.data.gov/harvest_record/19b6e9a7-fa80-45cb-ab3c-a2fcec0cf49b", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/19b6e9a7-fa80-45cb-ab3c-a2fcec0cf49b/raw", + "harvest_record": "https://catalog.data.gov/harvest_record/92b35bcb-8a6e-4322-bf37-655a576146ad", + "harvest_record_raw": "https://catalog.data.gov/harvest_record/92b35bcb-8a6e-4322-bf37-655a576146ad/raw", "has_download": true, "has_spatial": true, - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_f4f235c4-7666-4ba3-bd7d-0b9b56ae1fda", - "keyword": [ - "Arizona", - "California", - "Colorado", - "Nevada", - "New Mexico", - "USGS:f4f235c4-7666-4ba3-bd7d-0b9b56ae1fda", - "Upper Colorado River Basin", - "Utah", - "Wyoming", - "environment", - "geoscientificInformation", - "groundwater", - "groundwater recharge", - "inlandWaters", - "overland flow direction" - ], - "last_harvested_date": "2026-09-16T23:23:32.177571", + "identifier": "10.5067/GPMGV/OLYMPEX/LIDAR/DATA101", + "keyword": [ + "earth-science-cryospheric-indicators-climate-indicators-snow-depth", + "earth-science-land-use-land-cover-land-surface-land-use-land-cover-classification", + "earth-science-topography-land-surface-terrain-elevation", + "earth-science-visible-wavelengths-spectral-engineering-visible-imagery" + ], + "last_harvested_date": "2026-09-23T00:17:08.444989", "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", + "id": "f4ca4614-8901-409b-8553-2e994ad10023", + "logo": "https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png", + "name": "National Aeronautics and Space Administration", "organization_type": "Federal Government", - "slug": "doi" + "slug": "nasa" }, "parent_identifier": null, - "popularity": 3, - "publisher": "U.S. Geological Survey", - "slug": "overland-flow-direction-information-for-the-upper-colorado-river-basin-in-maurer-et-al-200", - "spatial_centroid": { - "lat": 38.575, - "lon": -109.675 - }, - "spatial_shape": { - "coordinates": [ - [ - [ - -112.625, - 35.125 - ], - [ - -112.625, - 43.75 - ], - [ - -105.25, - 43.75 - ], - [ - -105.25, - 35.125 - ], - [ - -112.625, - 35.125 - ] - ] - ], - "type": "Polygon" - }, - "theme": [ - "geospatial" - ], - "title": "Overland Flow Direction Information for the Upper Colorado River Basin in Maurer et al. (2002) Climate Data resolution (overland_flow_direction_UCRB_Maurer_resolution.asc)", + "popularity": 1, + "publisher": "NASA/MSFC/GHRC", + "slug": "gpm-ground-validation-airborne-snow-observatory-aso-olympex-v1", + "spatial_centroid": null, + "spatial_shape": null, + "theme": [ + "Earth Science" + ], + "title": "GPM Ground Validation Airborne Snow Observatory (ASO) OLYMPEX V1", "type": "dataset" }, { - "_score": 15.203146, + "_score": 13.337899, "_sort": [ - 1789600939921, - 15.203146, + 1790122625038, + 13.337899, 1, - "dd7e3233-6c6b-4728-ac90-38cd1dcd82fa" + "8e35d43d-30a6-4a25-8cd1-0aec49e6ac12" ], "dcat": { + "@type": "dcat:Dataset", "accessLevel": "public", "bureauCode": [ - "010:12" + "026:00" ], "contactPoint": { "@type": "vcard:Contact", - "fn": "Water Mission Area", - "hasEmail": "mailto:GS-W-model-data@usgs.gov" - }, - "description": "This is a polygon coverage of the Land Resource Regions and Major Land\nResource Areas of the conterminous United States. Land resource regions\nare geographic areas that are characterized by a particular pattern of\nsoils, climate, water resources and land uses. (USDA, Soil Conservation\nService, 1981). Major land resource areas are subregions of the\nland resource regions and comprise smaller homogeneous areas. The\nscale of this coverage is 1:2,000,000.\n\t\t\nNote: The Soil Conservation Service now (1995) is called the Natural\nResources Conservation Service.\n\t\t\nDescriptors:\n\t\t\nLand Resource Regions\nMajor Land Resource Areas\nUnited States", + "fn": "Earthdata Forum", + "hasEmail": "mailto:earthdata-support@nasa.gov" + }, + "description": "The GPM Ground Validation CAX1 Radar CFradial format OLYMPEX dataset consists of radar parameters, such as Radar reflectivity, Doppler velocity, Doppler width, Differential reflectivity, and Signal quality index, provided on a 0.4 to 1.0 km spatial resolution within the OLYMPEX field campaign study region in the state of Washington. These data were obtained for the GPM Ground Validation OLYMPEX field campaign by the SELEX Meteor 60DX10 Compact Weather (CAX1) radar. The CAX1 radar was located at the southern tip of Vancouver Island on the Canadian Forces Base (CFB) Esquimalt Albert Head (AHD) military training area. The CAX1 radar was operated by Environment and Climate Change Canada to support the OLYMPEX field campaign. These data are available in Cfradial netCDF-4 format from November 14, 2015 through April 1, 2016.", "distribution": [ { "@type": "dcat:Distribution", - "accessURL": "https://doi.org/10.5066/P9C2I3VQ", - "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.9b1592e8-a33b-4ec4-8e54-33a4bf74c17c.xml", - "format": "XML", + "conformsTo": "http://www.isotc211.org/2005/gmi", + "description": "The metadata's original source.", + "downloadURL": "https://cmr.earthdata.nasa.gov/search/concepts/C1981360835-GHRC_DAAC.iso19115", + "format": "ISO", "mediaType": "text/xml", "title": "Original Metadata" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "http://dx.doi.org/10.5067/GPMGV/OLYMPEX/DATA101", + "format": "HTML", + "mediaType": "text/html" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "http://olympex.atmos.washington.edu/", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://ams.confex.com/ams/17Mountain/webprogram/Paper296448.html", + "format": "HTML", + "mediaType": "text/html" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://dx.doi.org/10.1175/BAMS-D-16-0182.1", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://ghrc.earthdata.nasa.gov/browseui/#pub/gpmcax1cfolyx__1/docs/gpmcax1cfolyx_dataset.pdf", + "format": "PDF", + "mediaType": "application/pdf" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://ghrc.nsstc.nasa.gov/home/about-ghrc/citing-ghrc-daac-data", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://ghrc.nsstc.nasa.gov/home/field-campaigns/olympex", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://search.earthdata.nasa.gov/search/granules?p=C1981360835-GHRC_DAAC", + "format": "BIN", + "mediaType": "application/octet-stream" } ], - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_9b1592e8-a33b-4ec4-8e54-33a4bf74c17c", - "keyword": [ - "Land Resource Regions", - "Major Land Resource Areas", - "USGS:9b1592e8-a33b-4ec4-8e54-33a4bf74c17c", - "environment", - "geoscientificInformation", - "inlandWaters" - ], - "modified": "2020-11-17T00:00:00Z", + "identifier": "10.5067/GPMGV/OLYMPEX/XBAND/DATA301", + "keyword": [ + "earth-science-radar-spectral-engineering-doppler-velocity", + "earth-science-radar-spectral-engineering-radar-reflectivity", + "earth-science-radar-spectral-engineering-spectrum-width" + ], + "license": "https://www.usa.gov/government-works", + "modified": "2026-09-22", + "programCode": [ + "026:000" + ], "publisher": { "@type": "org:Organization", - "name": "U.S. Geological Survey" - }, - "spatial": "-128.07002717, 22.67774911, -65.25698378, 48.26194027", - "theme": [ - "geospatial" - ], - "title": "Major Land Resource Areas (MLRA)" - }, - "description": "This is a polygon coverage of the Land Resource Regions and Major Land\nResource Areas of the conterminous United States. Land resource regions\nare geographic areas that are characterized by a particular pattern of\nsoils, climate, water resources and land uses. (USDA, Soil Conservation\nService, 1981). Major land resource areas are subregions of the\nland resource regions and comprise smaller homogeneous areas. The\nscale of this coverage is 1:2,000,000.\n\t\t\nNote: The Soil Conservation Service now (1995) is called the Natural\nResources Conservation Service.\n\t\t\nDescriptors:\n\t\t\nLand Resource Regions\nMajor Land Resource Areas\nUnited States", + "name": "NASA/MSFC/GHRC" + }, + "spatial": "[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -124.376, \"NorthBoundingCoordinate\": 49.2854, \"EastBoundingCoordinate\": -122.58, \"SouthBoundingCoordinate\": 47.4888}]]", + "temporal": "2015-11-14/2016-04-01", + "theme": [ + "Earth Science" + ], + "title": "GPM Ground Validation CAX1 Radar CFradial format OLYMPEX V1" + }, + "description": "The GPM Ground Validation CAX1 Radar CFradial format OLYMPEX dataset consists of radar parameters, such as Radar reflectivity, Doppler velocity, Doppler width, Differential reflectivity, and Signal quality index, provided on a 0.4 to 1.0 km spatial resolution within the OLYMPEX field campaign study region in the state of Washington. These data were obtained for the GPM Ground Validation OLYMPEX field campaign by the SELEX Meteor 60DX10 Compact Weather (CAX1) radar. The CAX1 radar was located at the southern tip of Vancouver Island on the Canadian Forces Base (CFB) Esquimalt Albert Head (AHD) military training area. The CAX1 radar was operated by Environment and Climate Change Canada to support the OLYMPEX field campaign. These data are available in Cfradial netCDF-4 format from November 14, 2015 through April 1, 2016.", "distribution_titles": [ - "Digital Data", "Original Metadata" ], - "harvest_record": "https://catalog.data.gov/harvest_record/76d076f3-d146-4b61-a887-5b928eed4801", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/76d076f3-d146-4b61-a887-5b928eed4801/raw", + "harvest_record": "https://catalog.data.gov/harvest_record/41e8a2a6-25a7-4a2d-ac96-b5c953866ead", + "harvest_record_raw": "https://catalog.data.gov/harvest_record/41e8a2a6-25a7-4a2d-ac96-b5c953866ead/raw", "has_download": true, "has_spatial": true, - "identifier": "http://datainventory.doi.gov/id/dataset/USGS_9b1592e8-a33b-4ec4-8e54-33a4bf74c17c", - "keyword": [ - "Land Resource Regions", - "Major Land Resource Areas", - "USGS:9b1592e8-a33b-4ec4-8e54-33a4bf74c17c", - "environment", - "geoscientificInformation", - "inlandWaters" - ], - "last_harvested_date": "2026-09-16T23:22:19.921331", + "identifier": "10.5067/GPMGV/OLYMPEX/XBAND/DATA301", + "keyword": [ + "earth-science-radar-spectral-engineering-doppler-velocity", + "earth-science-radar-spectral-engineering-radar-reflectivity", + "earth-science-radar-spectral-engineering-spectrum-width" + ], + "last_harvested_date": "2026-09-23T00:17:05.038479", "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", + "id": "f4ca4614-8901-409b-8553-2e994ad10023", + "logo": "https://raw.githubusercontent.com/GSA/logo/refs/heads/master/nasa.png", + "name": "National Aeronautics and Space Administration", "organization_type": "Federal Government", - "slug": "doi" + "slug": "nasa" }, "parent_identifier": null, "popularity": 1, - "publisher": "U.S. Geological Survey", - "slug": "major-land-resource-areas-mlra-2f668", - "spatial_centroid": { - "lat": 32.911425574, - "lon": -102.944809814 - }, - "spatial_shape": { - "coordinates": [ - [ - [ - -128.07002717, - 22.67774911 - ], - [ - -128.07002717, - 48.26194027 - ], - [ - -65.25698378, - 48.26194027 - ], - [ - -65.25698378, - 22.67774911 - ], - [ - -128.07002717, - 22.67774911 - ] - ] - ], - "type": "Polygon" - }, - "theme": [ - "geospatial" - ], - "title": "Major Land Resource Areas (MLRA)", + "publisher": "NASA/MSFC/GHRC", + "slug": "gpm-ground-validation-cax1-radar-cfradial-format-olympex-v1", + "spatial_centroid": null, + "spatial_shape": null, + "theme": [ + "Earth Science" + ], + "title": "GPM Ground Validation CAX1 Radar CFradial format OLYMPEX V1", "type": "dataset" }, { - "_score": 8.121664, + "_score": 6.1792574, "_sort": [ - 1789584604291, - 8.121664, - 4, - "374f22e6-71ff-41c8-ad59-226d7c041e6e" + 1790122622106, + 6.1792574, + 1, + "cf2d6699-7ec6-48d3-90b7-4d2b0871ba8a" ], "dcat": { "@type": "dcat:Dataset", "accessLevel": "public", + "bureauCode": [ + "026:00" + ], "contactPoint": { "@type": "vcard:Contact", - "fn": "OpenData", - "hasEmail": "mailto:no-reply@data.sf.gov" - }, - "description": "<strong>A. SUMMARY</strong>\nThe Municipal Natural Gas Equipment Inventory serves to catalog natural gas-fueled equipment used in municipally owned buildings. \nThis inventory, implemented by the SF Environment Department, aims to establish an understanding of the scope of work needed to electrify municipal buildings and inform an effective and collaborative planning process.\nThis effort was identified as an action in Section BO-2.4 of the <u><a href=\"https://www.sfenvironment.org/files/events/2021_climate_action_plan.pdf\">2021 Climate Action Plan</a></u> and is included in the <u><a href=\"https://codelibrary.amlegal.com/codes/san_francisco/latest/sf_environment/0-0-0-577\">Environment Code Chapter 7</a></u> (Municipal Green Building Requirements). \n\n<strong>B. HOW THE DATASET IS CREATED</strong>\nThe list of buildings required to report data for the Municipal Natural Gas Equipment Inventory was compiled by cross-referencing the City’s <u><a href=\"https://data.sfgov.org/City-Infrastructure/City-Facilities/nc68-ngbr/about_datax\">Facility Systems of Record</a></u> and the <u><a href=\"https://sfpuc.org/about-us/reports/municipal-buildings-energy-benchmarking\">2020 municipal benchmarking report</a></u> to identify all city-owned buildings with non-zero carbon emissions. Numerous municipal buildings are exempt from these reporting requirements, including facilities of the Port of San Francisco and buildings with a primary purpose of providing collection, storage, treatment, delivery, distribution, and/or transmission of water, wastewater, and/or power utilities. \nEach department received an inventory template, provided by the Environment Department, to submit high level building data and detailed information on each piece of natural gas equipment in use in these buildings. Departments were asked to self-report the required building and equipment data over the course of a 6-month data collection period in 2023 and are asked to keep this inventory up to date in the following years as equipment is replaced. \n\n<strong>C. UPDATE PROCESS</strong>\nThe inventory will be regularly updated by department representatives via the inventory PowerApp. When a gas-powered equipment item is retired or replaced, departments are asked to mark it as no longer in use and provide information on any electric replacement equipment, if applicable. While departments have the flexibility to update the inventory at any time, they are encouraged to do so at 6 month intervals at the minimum. \n\nUpdated inventory data will be automatically reflected in this dataset. \n\n<strong>D. HOW TO USE THIS DATASET</strong>\nIt is important to note that this dataset does not include facilities of the Port of San Francisco and buildings with a primary purpose of providing collection, storage, treatment, delivery, distribution, and/or transmission of water, wastewater, and/or power utilities, in accordance with Environment Code Chapter 7 exemptions.", + "fn": "Earthdata Forum", + "hasEmail": "mailto:earthdata-support@nasa.gov" + }, + "description": "The GPM Ground Validation Environment Canada (EC) Weather Station XET C3VP dataset consists of surface meteorological data collected at the Environment Canada (EC) XET station at the Centre for Atmospheric Research Experiments (CARE) during the Canadian CloudSat/CALIPSO Validation Project (C3VP) field campaign. The campaign took place in southern Canada in support of multiple science missions, including the NASA GPM mission, in order to improve the modeling and remote sensing of winter precipitation. The XET C3VP dataset file includes temperature, pressure, wind speed and direction, relative humidity, solar radiation, grass temperature, soil temperature, snow depth, sunshine, and precipitation measurements from October 4, 2006 through March 31, 2007 in ASCII-csv format.", "distribution": [ { "@type": "dcat:Distribution", - "describedBy": "https://data.sf.gov/api/views/vc6r-v7av/columns.json", - "describedByType": "application/json", - "downloadURL": "https://data.sf.gov/api/v3/views/vc6r-v7av/query.json?accessType=DOWNLOAD", - "mediaType": "application/json" - }, - { - "@type": "dcat:Distribution", - "describedBy": "https://data.sf.gov/api/views/vc6r-v7av/columns.xml", - "describedByType": "application/xml", - "downloadURL": "https://data.sf.gov/api/v3/views/vc6r-v7av/query.xml?accessType=DOWNLOAD", - "mediaType": "application/xml" - }, - { - "@type": "dcat:Distribution", - "downloadURL": "https://data.sf.gov/api/v3/views/vc6r-v7av/export.csv?accessType=DOWNLOAD", - "mediaType": "text/csv" - }, - { - "@type": "dcat:Distribution", - "downloadURL": "https://data.sf.gov/api/v3/views/vc6r-v7av/export.kml?accessType=DOWNLOAD", - "mediaType": "application/vnd.google-earth.kml+xml" - }, - { - "@type": "dcat:Distribution", - "downloadURL": "https://data.sf.gov/api/v3/views/vc6r-v7av/export.kmz?accessType=DOWNLOAD", - "mediaType": "application/vnd.google-earth.kmz" - }, - { - "@type": "dcat:Distribution", - "downloadURL": "https://data.sf.gov/api/v3/views/vc6r-v7av/query.geojson?accessType=DOWNLOAD", - "mediaType": "application/geo+json" + "conformsTo": "http://www.isotc211.org/2005/gmi", + "description": "The metadata's original source.", + "downloadURL": "https://cmr.earthdata.nasa.gov/search/concepts/C1998274501-GHRC_DAAC.iso19115", + "format": "ISO", + "mediaType": "text/xml", + "title": "Original Metadata" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://ghrc.earthdata.nasa.gov/browseui/#pub/gpmxetc3vp__1/docs/RCSdataloggeroutputs_v2.003jun24.xls", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://ghrc.earthdata.nasa.gov/browseui/#pub/gpmxetc3vp__1/docs/gpmxetc3vp_dataset.pdf", + "format": "PDF", + "mediaType": "application/pdf" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://ghrc.nsstc.nasa.gov/home/about-ghrc/citing-ghrc-daac-data", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://gpm.nasa.gov/science/ground-validation/C3VP", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://search.earthdata.nasa.gov/search/granules?p=C1998274501-GHRC_DAAC", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://www.ec.gc.ca/rs-mn/default.asp?lang=En&n=F382596F-1", + "format": "BIN", + "mediaType": "application/octet-stream" + }, + { + "@type": "dcat:Distribution", + "downloadURL": "https://www.ocean-ops.org/dbcp/doc/AES_Canada_Guide20.pdf", + "format": "PDF", + "mediaType": "application/pdf" } ], - "identifier": "https://data.sf.gov/api/views/vc6r-v7av", - "issued": "2024-03-28", - "keyword": [ - "environment", - "environmental health", - "greenhouse gas emissions", - "natural gas" - ], - "landingPage": "https://data.sf.gov/d/vc6r-v7av", - "modified": "2026-09-11", + "identifier": "10.5067/GPMGV/C3VP/METSTATION/DATA201", + "keyword": [ + "earth-science-atmospheric-pressure-atmosphere-surface-pressure", + "earth-science-atmospheric-radiation-atmosphere-solar-radiation", + "earth-science-atmospheric-radiation-atmosphere-sunshine", + "earth-science-atmospheric-temperature-atmosphere-surface-temperature", + "earth-science-atmospheric-water-vapor-atmosphere-water-vapor-indicators", + "earth-science-atmospheric-winds-atmosphere-surface-winds", + "earth-science-cryospheric-indicators-climate-indicators-snow-depth", + "earth-science-precipitation-atmosphere-atmospheric-precipitation-indices", + "earth-science-soils-agriculture-soil-temperature" + ], + "license": "https://www.usa.gov/government-works", + "modified": "2026-09-22", + "programCode": [ + "026:000" + ], "publisher": { "@type": "org:Organization", - "name": "data.sf.gov" - }, - "theme": [ - "Energy and Environment" - ], - "title": "San Francisco Municipal Natural Gas Equipment Inventory" - }, - "description": "<strong>A. SUMMARY</strong>\nThe Municipal Natural Gas Equipment Inventory serves to catalog natural gas-fueled equipment used in municipally owned buildings. \nThis inventory, implemented by the SF Environment Department, aims to establish an understanding of the scope of work needed to electrify municipal buildings and inform an effective and collaborative planning process.\nThis effort was identified as an action in Section BO-2.4 of the <u><a href=\"https://www.sfenvironment.org/files/events/2021_climate_action_plan.pdf\">2021 Climate Action Plan</a></u> and is included in the <u><a href=\"https://codelibrary.amlegal.com/codes/san_francisco/latest/sf_environment/0-0-0-577\">Environment Code Chapter 7</a></u> (Municipal Green Building Requirements). \n\n<strong>B. HOW THE DATASET IS CREATED</strong>\nThe list of buildings required to report data for the Municipal Natural Gas Equipment Inventory was compiled by cross-referencing the City’s <u><a href=\"https://data.sfgov.org/City-Infrastructure/City-Facilities/nc68-ngbr/about_datax\">Facility Systems of Record</a></u> and the <u><a href=\"https://sfpuc.org/about-us/reports/municipal-buildings-energy-benchmarking\">2020 municipal benchmarking report</a></u> to identify all city-owned buildings with non-zero carbon emissions. Numerous municipal buildings are exempt from these reporting requirements, including facilities of the Port of San Francisco and buildings with a primary purpose of providing collection, storage, treatment, delivery, distribution, and/or transmission of water, wastewater, and/or power utilities. \nEach department received an inventory template, provided by the Environment Department, to submit high level building data and detailed information on each piece of natural gas equipment in use in these buildings. Departments were asked to self-report the required building and equipment data over the course of a 6-month data collection period in 2023 and are asked to keep this inventory up to date in the following years as equipment is replaced. \n\n<strong>C. UPDATE PROCESS</strong>\nThe inventory will be regularly updated by department representatives via the inventory PowerApp. When a gas-powered equipment item is retired or replaced, departments are asked to mark it as no longer in use and provide information on any electric replacement equipment, if applicable. While departments have the flexibility to update the inventory at any time, they are encouraged to do so at 6 month intervals at the minimum. \n\nUpdated inventory data will be automatically reflected in this dataset. \n\n<strong>D. HOW TO USE THIS DATASET</strong>\nIt is important to note that this dataset does not include facilities of the Port of San Francisco and buildings with a primary purpose of providing collection, storage, treatment, delivery, distribution, and/or transmission of water, wastewater, and/or power utilities, in accordance with Environment Code Chapter 7 exemptions.", - "distribution_titles": [], - "harvest_record": "https://catalog.data.gov/harvest_record/329bcedf-df1e-46c4-ad33-f4ed967101f6", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/329bcedf-df1e-46c4-ad33-f4ed967101f6/raw", + "name": "NASA/MSFC/GHRC" + }, + "spatial": "[\"CARTESIAN\", [{\"WestBoundingCoordinate\": -79.79, \"NorthBoundingCoordinate\": 44.24, \"EastBoundingCoordinate\": -79.77, \"SouthBoundingCoordinate\": 44.22}]]", + "temporal": "2006-10-04/2007-03-31", + "theme": [ + "Earth Science" + ], + "title": "GPM Ground Validation Environment Canada (EC) Weather Station XET C3VP V1" + }, + "description": "The GPM Ground Validation Environment Canada (EC) Weather Station XET C3VP dataset consists of surface meteorological data collected at the Environment Canada (EC) XET station at the Centre for Atmospheric Research Experiments (CARE) during the Canadian CloudSat/CALIPSO Validation Project (C3VP) field campaign. The campaign took place in southern Canada in support of multiple science missions, including the NASA GPM mission, in order to improve the modeling and remote sensing of winter precipitation. The XET C3VP dataset file includes temperature, pressure, wind speed and direction, relative humidity, solar radiation, grass temperature, soil temperature, snow depth, sunshine, and precipitation measurements from October 4, 2006 through March 31, 2007 in ASCII-csv format.", + "distribution_titles": [ + "Original Metadata" + ], + "harvest_record": "https://catalog.data.gov/harvest_record/460094dc-1110-41e2-9e98-aeb86792d509", + "harvest_record_raw": "https://catalog.data.gov/harvest_record/460094dc-1110-41e2-9e98-aeb86792d509/raw", "has_download": true, - "has_spatial": false, - "identifier": "https://data.sf.gov/api/views/vc6r-v7av", - "keyword": [ - "environment", - "environmental health", - "greenhouse gas emissions", - "natural gas" - ], - "last_harvested_date": "2026-09-16T18:50:04.291783", + "has_spatial": true, + "identifier": "10.5067/GPMGV/C3VP/METSTATION/DATA201", + "keyword": [ + "earth-science-atmospheric-pressure-atmosphere-surface-pressure", + "earth-science-atmospheric-radiation-atmosphere-solar-radiation", + "earth-science-atmospheric-radiation-atmosphere-sunshine", + "earth-science-atmospheric-temperature-atmosphere-surface-temperature", + "earth-science-atmospheric-water-vapor-atmosphere-water-vapor-indicators", + "earth-science-atmospheric-winds-atmosphere-surface-winds", + "earth-s