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Notebook","category":"Sustainable Development","sub_category":"Data Catalogs and Interfaces","monthly_downloads":0,"total_dependent_repos":0,"total_dependent_packages":0,"readme":"# AI for Earth Data Sets\n\nThe \u003ca href=\"http://aka.ms/aiforearth\"\u003eMicrosoft AI for Earth program\u003c/a\u003e hosts geospatial data on Azure that is important to environmental sustainability and Earth science.  This repo hosts documentation and demonstration notebooks for all the data that is managed by AI for Earth.  It also serves as a \"staging ground\" for the [Planetary Computer Data Catalog](https://planetarycomputer.microsoft.com/catalog).\n\nIf you have feedback about any of this data, or want to request additions to our data program, email [`aiforearthdatasets@microsoft.com`](mailto:aiforearthdatasets@microsoft.com?subject=data%20question).\n\n## Table of contents\n\n- [AI for Earth Data Sets](#ai-for-earth-data-sets)\n  - [Table of contents](#table-of-contents)\n- [Data sets](#data-sets)\n  - [ALOS World 3D](#alos-world-3d)\n  - [ASTER L1T (2000-2006)](#aster-l1t-2000-2006)\n  - [Copernicus DEM](#copernicus-dem)\n  - [Daymet](#daymet)\n  - [Deltares Global Flood Maps](#deltares-global-flood-maps)\n  - [Deltares Global Water Availability](#deltares-global-water-availability)\n  - [Esri 10m Land Cover](#esri-10m-land-cover)\n  - [Global Biodiversity Information Facility (GBIF)](#global-biodiversity-information-facility-gbif)\n  - [Harmonized Global Biomass](#harmonized-global-biomass)\n  - [Harmonized Landsat Sentinel-2](#harmonized-landsat-sentinel-2)\n  - [High Resolution Electricity Access (HREA)](#high-resolution-electricity-access-hrea)\n  - [High Resolution Ocean Surface Wave Hindcast](#high-resolution-ocean-surface-wave-hindcast)\n  - [Labeled Information Library of Alexandria: Biology and Conservation (LILA BC)](#labeled-information-library-of-alexandria-biology-and-conservation-lila-bc)\n  - [Landsat TM/MSS Collection 2](#landsat-tmmss-collection-2)\n  - [Landsat 7 Collection 2 Level-2](#landsat-7-collection-2-level-2)\n  - [Landsat 8 Collection 2 Level-2](#landsat-8-collection-2-level-2)\n  - [MODIS (40 individual products)](#modis-40-individual-products)\n  - [Monitoring Trends in Burn Severity Mosaics](#monitoring-trends-in-burn-severity-mosaics)\n  - [National Solar Radiation Database](#national-solar-radiation-database)\n  - [NASADEM](#nasadem)\n  - [NREL Puerto Rico 100 (PR100)](#nrel-puerto-rico-100-dataset-pr100)\n  - [NREL PV Rooftop Database](#nrel-pv-rooftop-database)\n  - [NOAA Climate Data Records (CDR)](#noaa-climate-data-records-cdr)\n  - [NOAA Climate Forecast System (CFS)](#noaa-climate-forecast-system-cfs)\n  - [NOAA Digital Coast Imagery](#noaa-digital-coast-imagery)\n  - [NOAA GFS Warm Start Initial Conditions](#noaa-gfs-warm-start-initial-conditions)\n  - [NOAA GOES-R](#noaa-goes-r)\n  - [NOAA Global Ensemble Forecast System (GEFS)](#noaa-global-ensemble-forecast-system-gefs)\n  - [NOAA Global Forecast System (GFS)](#noaa-global-forecast-system-gfs)\n  - [NOAA Global Hydro Estimator (GHE)](#noaa-global-hydro-estimator-ghe)\n  - [NOAA High-Resolution Rapid Refresh (HRRR)](#noaa-high-resolution-rapid-refresh-hrrr)\n  - [NOAA Integrated Surface Data (ISD)](#noaa-integrated-surface-data-isd)\n  - [NOAA Monthly US Climate Gridded Dataset (NClimGrid)](#noaa-monthly-us-climate-gridded-dataset-nclimgrid)\n  - [NOAA National Water Model](#noaa-national-water-model)\n  - [NOAA Rapid Refresh (RAP)](#noaa-rapid-refresh-rap)\n  - [NOAA US Climate Normals](#noaa-us-climate-normals)\n  - [National Agriculture Imagery Program](#national-agriculture-imagery-program)\n  - [National Land Cover Database](#national-land-cover-database)\n  - [NatureServe Map of Biodiversity Importance (MoBI)](#natureserve-map-of-biodiversity-importance-mobi)\n  - [Ocean Observatories Initiative CamHD](#ocean-observatories-initiative-camhd)\n  - [Sentinel-1 GRD](#sentinel-1-grd)\n  - [Sentinel-2 L2A](#sentinel-2-l2a)\n  - [Sentinel-3 L2](#sentinel-3-l2)\n  - [Sentinel-5P](#sentinel-5p)\n  - [TerraClimate](#terraclimate)\n  - [UK Met Office CSSP China 20CRDS](#uk-met-office-cssp-china-20crds)\n  - [UK Met Office Global Weather Data for COVID-19 Analysis](#uk-met-office-global-weather-data-for-covid-19-analysis)\n  - [University of Miami Coupled Model for Hurricanes Ike and Sandy](#university-of-miami-coupled-model-for-hurricanes-ike-and-sandy)\n  - [USFS Forest Inventory and Analysis](#usfs-forest-inventory-and-analysis)\n  - [USGS 3DEP Seamless DEMs](#usgs-3dep-seamless-dems)\n  - [USGS Gap Land Cover](#usgs-gap-land-cover)\n- [Legal stuff](#legal-stuff)\n  - [Contributing](#contributing)\n  - [Trademarks](#trademarks)\n\n\n# Data sets\n\n## ALOS World 3D\n\nGlobal topographic information from the JAXA ALOS PRISM instrument.\n\n* [Source](https://www.eorc.jaxa.jp/ALOS/en/aw3d30/index.htm)\n* [Documentation](data/alos-dem.md)\n* [Notebook](https://nbviewer.jupyter.org/github/microsoft/AIforEarthDataSets/blob/main/data/alos-dem.ipynb)\n* [Planetary Computer collection](https://planetarycomputer.microsoft.com/dataset/alos-dem)\n\n## ASTER L1T (2000-2006)\n\nThe [ASTER](https://terra.nasa.gov/about/terra-instruments/aster) instrument, launched on-board NASA's [Terra](https://terra.nasa.gov/) satellite in 1999, provides multispectral images of the Earth at 15m-90m resolution.  This data set represents ASTER data from 2000-2006.\n\n* [Source](https://terra.nasa.gov/about/terra-instruments/aster)\n* [Documentation](data/aster.md)\n* [Notebook](https://nbviewer.jupyter.org/github/microsoft/AIforEarthDataSets/blob/main/data/aster.ipynb)\n* [Planetary Computer collection](https://planetarycomputer.microsoft.com/dataset/aster-l1t)\n\n## Copernicus DEM\n\nGlobal topographic information from the Copernicus program.\n\n* [Source](https://spacedata.copernicus.eu/explore-more/news-archive/-/asset_publisher/Ye8egYeRPLEs/blog/id/434960)\n* [Documentation](data/copernicus-dem.md)\n* [Notebook](https://nbviewer.jupyter.org/github/microsoft/AIforEarthDataSets/blob/main/data/copernicus-dem.ipynb)\n* [Planetary Computer collection](https://planetarycomputer.microsoft.com/dataset/group/copernicus-dem)\n\n## Daymet\n\nEstimates of daily weather parameters in North America on a one-kilometer grid, with monthly and annual summaries.\n\n* [Source](https://daymet.ornl.gov/)\n* [Documentation](data/daymet.md)\n* [Notebook (Zarr)](https://nbviewer.jupyter.org/github/microsoft/AIforEarthDataSets/blob/main/data/daymet-zarr.ipynb)\n* [Notebook (NetCDF)](https://nbviewer.jupyter.org/github/microsoft/AIforEarthDataSets/blob/main/data/daymet-nc.ipynb)\n* [Planetary Computer collection](https://planetarycomputer.microsoft.com/dataset/group/daymet)\n\n## Deltares Global Flood Maps\n\nGlobal estimates of coastal inundation under various sea level rise conditions and return periods at 90m, 1km, and 5km resolutions. Also includes estimated coastal inundation caused by named historical storm events going back several decades.\n\n* [Source](https://www.deltares.nl/en/)\n* [Documentation](data/deltares-floods.md)\n* [Notebook (NetCDF)](https://nbviewer.jupyter.org/github/microsoft/AIforEarthDataSets/blob/main/data/deltares-floods.ipynb)\n\n## Deltares Global Water Availability\n\nSimulations of historical daily reservoir variations for 3,236 locations across the globe for the period 1970-2020 using the distributed wflow_sbm model. The model outputs long-term daily information on reservoir volume, inflow and outflow dynamics, as well as information on upstream hydrological forcing.\n\n* [Source](https://www.deltares.nl/en/)\n* [Documentation](data/deltares-water-availability.md)\n* [Notebook (NetCDF)](https://nbviewer.jupyter.org/github/microsoft/AIforEarthDataSets/blob/main/data/deltares-water-availability.ipynb)\n\n## Esri 10m Land Cover\n\nGlobal estimates of 10-class land use/land cover (LULC) for 2020, derived from ESA Sentinel-2 imagery at 10m resolution, produced by [Impact Observatory](impactobservatory.com).\n\n* [Source](https://livingatlas.arcgis.com/landcover/)\n* [Documentation](data/io-lulc.md)\n* [Notebook](https://nbviewer.jupyter.org/github/microsoft/AIforEarthDataSets/blob/main/data/io-lulc.ipynb)\n* [Planetary Computer collection](https://planetarycomputer.microsoft.com/dataset/io-lulc)\n\n## Global Biodiversity Information Facility (GBIF)\n\nExports of global species occurrence data from the GBIF network.\n\n* [Source](https://www.gbif.org)\n* [Documentation](data/gbif.md)\n* [Notebook](https://nbviewer.jupyter.org/github/microsoft/AIforEarthDataSets/blob/main/data/gbif.ipynb)\n* [Planetary Computer collection](https://planetarycomputer.microsoft.com/dataset/gbif)\n\n## Harmonized Global Biomass\n\nGlobal maps of aboveground and belowground biomass carbon density for the year 2010 at 300m resolution.\n\n* [Source](https://www.nature.com/articles/s41597-020-0444-4)\n* [Documentation](data/hgb.md)\n* [Notebook](https://nbviewer.jupyter.org/github/microsoft/AIforEarthDataSets/blob/main/data/hgb.ipynb)\n* [Planetary Computer collection](https://planetarycomputer.microsoft.com/dataset/hgb)\n\n## Harmonized Landsat Sentinel-2\n\nSatellite imagery from the Landsat 8 and Sentinel-2 satellites, aligned to a common grid and processed to compatible color spaces.\n\n* [Source](https://hls.gsfc.nasa.gov/)\n* [Documentation](data/hls.md)\n* [Notebook](https://nbviewer.jupyter.org/github/microsoft/AIforEarthDataSets/blob/main/data/hls.ipynb)\n\n## High Resolution Electricity Access (HREA)\n\nSettlement-level measures of electricity access, reliability, and usage derived from VIIRS satellite imagery.\n\n* [Source](http://www-personal.umich.edu/~brianmin/HREA/index.html)\n* [Documentation](data/hrea.md)\n* [Notebook](https://nbviewer.jupyter.org/github/microsoft/AIforEarthDataSets/blob/main/data/hrea.ipynb)\n* [Planetary Computer collection](https://planetarycomputer.microsoft.com/dataset/hrea)\n\n## High Resolution Ocean Surface Wave Hindcast\n\nLong-term wave hindcast data for the U.S. Exclusive Economic Zone (EEZ), developed by the U.S. Department of Energy's Water Power Technologies Office.\n\n* [Source](https://github.com/openEDI/documentation/blob/main/US_Wave.md)\n* [Documentation](data/doe-wave.md)\n\n## Labeled Information Library of Alexandria: Biology and Conservation (LILA BC)\n\nAI for Earth and partners have assembled a repository of labeled information related to wildlife conservation, particularly wildlife imagery.\n\n* [lila.science](http://lila.science)\n\n## Landsat TM/MSS Collection 2\n\nGlobal optical imagery from the Landsat MSS and TM instruments, which imaged the Earth from 1972 to 2013, aboard the Landsat 1-5 satellites.\n\nLandsat TM/MSS data are in preview; access is granted by request.\n\n* [Source](https://landsat.gsfc.nasa.gov/)\n* [Documentation](data/landsat-tm-mss.md)\n* [Notebook](https://nbviewer.jupyter.org/github/microsoft/AIforEarthDataSets/blob/main/data/landsat-tm-mss.ipynb)\n\n## Landsat 7 Collection 2 Level-2\n\nGlobal optical imagery from the Landsat 7 satellite, which has imaged the Earth since 1999.\n\nLandsat 7 data are in preview; access is granted by request.\n\n* [Source](https://landsat.gsfc.nasa.gov/)\n* [Documentation](data/landsat-7.md)\n* [Notebook](https://nbviewer.jupyter.org/github/microsoft/AIforEarthDataSets/blob/main/data/landsat-7.ipynb)\n\n## Landsat 8 Collection 2 Level-2\n\nGlobal optical imagery from the Landsat 8 satellite, which has imaged the Earth since 2013.\n\n* [Source](https://landsat.gsfc.nasa.gov/)\n* [Documentation](data/landsat-8.md)\n* [Notebook](https://nbviewer.jupyter.org/github/microsoft/AIforEarthDataSets/blob/main/data/landsat-8.ipynb)\n* [Planetary Computer collection](https://planetarycomputer.microsoft.com/dataset/landsat-8-c2-l2)\n\n## MODIS (40 individual products)\n\nSatellite imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS).\n\n* [Source](https://modis.gsfc.nasa.gov/)\n* [Documentation](data/modis.md)\n* [Notebook](https://nbviewer.jupyter.org/github/microsoft/AIforEarthDataSets/blob/main/data/modis.ipynb)\n\n## Monitoring Trends in Burn Severity Mosaics\n\nAnnual burn severity mosaics for the continental United States and Alaska.\n\n* [Source](https://www.mtbs.gov/)\n* [Documentation](data/mtbs.md)\n* [Notebook](https://nbviewer.jupyter.org/github/microsoft/AIforEarthDataSets/blob/main/data/mtbs.ipynb)\n* [Planetary Computer collection](https://planetarycomputer.microsoft.com/dataset/mtbs)\n\n## National Solar Radiation Database\n\nHourly and half-hourly values of the three most common measurements of solar radiation – global horizontal, direct normal, and diffuse horizontal irradiance - along with meteorological data.\n\n* [Source](https://nsrdb.nrel.gov/)\n* [Documentation](data/nsrdb.md)\n* [Notebook](https://nbviewer.jupyter.org/github/microsoft/AIforEarthDataSets/blob/main/data/nsrdb.ipynb)\n\n## NASADEM\n\nGlobal topographic information from the NASADEM program.\n\n* [Source](https://earthdata.nasa.gov/esds/competitive-programs/measures/nasadem)\n* [Documentation](data/nasadem.md)\n* [Notebook (COG)](https://nbviewer.jupyter.org/github/microsoft/AIforEarthDataSets/blob/main/data/nasadem-cog.ipynb)\n* [Notebook (NetCDF)](https://nbviewer.jupyter.org/github/microsoft/AIforEarthDataSets/blob/main/data/nasadem-nc.ipynb)\n* [Planetary Computer collection](https://planetarycomputer.microsoft.com/dataset/nasadem)\n\n## NREL Puerto Rico 100 Dataset (PR100)\n\nA collection of geospasial data useful for renewable energy development in Puerto Rico. The dataset is curated by the National Renewable Energy Laboratory.\n\n* [Source](https://www.energy.gov/gdo/puerto-rico-grid-resilience-and-transitions-100-renewable-energy-study-pr100)\n* [Documentation](data/PR100.md)\n* [Notebook](https://nbviewer.jupyter.org/github/microsoft/AIforEarthDataSets/blob/main/data/PR100.ipynb)\n\n## NREL PV Rooftop Database\n\nA lidar-derived, geospatially-resolved dataset of suitable roof surfaces and their PV technical potential for 128 metropolitan regions in the United States. \n\n* [Source](https://www.nrel.gov/docs/fy16osti/65298.pdf)\n* [Documentation](data/pv_rooftop.md)\n* [Notebook](https://nbviewer.jupyter.org/github/microsoft/AIforEarthDataSets/blob/main/data/pv_rooftop.ipynb)\n\n## NOAA Climate Data Records (CDR)\n\nHistorical global climate information.\n\n* [Source](https://www.ncei.noaa.gov/products/climate-data-records)\n* [Documentation](data/noaa-cdr.md)\n\n## NOAA Climate Forecast System (CFS)\n\nModel output data from the [NOAA NCEP Climate Forecast System Version 2](https://cfs.ncep.noaa.gov/).\n\n* [Source](https://cfs.ncep.noaa.gov/)\n* [Documentation](data/noaa-cfs.md)\n\n## NOAA Digital Coast Imagery\n\nHigh resolution (1 meter or less) imagery collected by a number of sources and contributed to the NOAA Digital Coast\n\n* [Source](https://coast.noaa.gov/digitalcoast/data/highresortho.html)\n* [Documentation](data/noaa-digital-coast-imagery.md)\n\n## NOAA GFS Warm Start Initial Conditions\n\nWarm start initial conditions for the [NOAA Global Forecast System](https://www.ncdc.noaa.gov/data-access/model-data/model-datasets/global-forcast-system-gfs).\n\n* [Source](https://www.ncdc.noaa.gov/data-access/model-data/model-datasets/global-forcast-system-gfs)\n* [Documentation](data/gfs-warm-start.md)\n\n## NOAA GOES-R\n\nWeather imagery from the GOES-16, GOES-17, and GOES-18 satellites.\n\n* [Source](https://www.nesdis.noaa.gov/GOES-R-Series-Satellites)\n* [Documentation](data/goes-r.md)\n* [Notebook](https://nbviewer.jupyter.org/github/microsoft/AIforEarthDataSets/blob/main/data/goes-r-abi-l2-mcmipf.ipynb)\n* [Snow / Ice Notebook](https://nbviewer.jupyter.org/github/microsoft/AIforEarthDataSets/blob/main/data/goes-ice.ipynb)\n* [Planetary Computer collection](https://planetarycomputer.microsoft.com/dataset/goes-cmi)\n\n## NOAA Global Ensemble Forecast System (GEFS)\n\nModel output data from the [NOAA Global Ensemble Forecast System](https://www.ncei.noaa.gov/products/weather-climate-models/global-ensemble-forecast).\n\n* [Source](https://www.ncei.noaa.gov/products/weather-climate-models/global-ensemble-forecast)\n* [Documentation](data/noaa-gefs.md)\n\n## NOAA Global Forecast System (GFS)\n\nModel output data from the [NOAA Global Forecast System](https://www.ncdc.noaa.gov/data-access/model-data/model-datasets/global-forcast-system-gfs).\n\n* [Source](https://www.ncdc.noaa.gov/data-access/model-data/model-datasets/global-forcast-system-gfs)\n* [Documentation](data/noaa-gfs.md)\n\n## NOAA Global Hydro Estimator (GHE)\n\nGlobal rainfall estimates in 15-minute intervals.\n\n* [Source](https://www.ospo.noaa.gov/Products/atmosphere/ghe/)\n* [Documentation](data/ghe.md)\n* [Notebook](https://nbviewer.jupyter.org/github/microsoft/AIforEarthDataSets/blob/main/data/ghe.ipynb)\n\n## NOAA High-Resolution Rapid Refresh (HRRR)\n\nWeather forecasts for North America at 3km spatial resolution and 15 minute temporal resolution.\n\n* [Source](https://www.nco.ncep.noaa.gov/pmb/products/hrrr/)\n* [Documentation](data/noaa-hrrr.md)\n* [Notebook](https://nbviewer.jupyter.org/github/microsoft/AIforEarthDataSets/blob/main/data/noaa-hrrr.ipynb)\n\n## NOAA Integrated Surface Data (ISD)\n\nHistorical global weather information.\n\n* [Source](https://www.ncei.noaa.gov/products/land-based-station/integrated-surface-database)\n* [Documentation](data/noaa-isd.md)\n\n\n## NOAA Monthly US Climate Gridded Dataset (NClimGrid)\n\nGridded climate data for the US from 1895 to the present.\n\n* [Source](https://www.ncei.noaa.gov/access/metadata/landing-page/bin/iso?id=gov.noaa.ncdc:C00332)\n* [Documentation](data/noaa-nclimgrid.md)\n\n## NOAA National Water Model\n\nData from the National Water Model.\n\n* [Source](https://water.noaa.gov/about/nwm)\n* [Documentation](data/noaa-nwm.md)\n* [Notebook](https://nbviewer.jupyter.org/github/microsoft/AIforEarthDataSets/blob/main/data/noaa-nwm-example.ipynb)\n\n## NOAA Rapid Refresh (RAP)\n\nWeather forecasts for North America at 13km resolution.\n\n* [Source](https://www.nco.ncep.noaa.gov/pmb/products/rap/)\n* [Documentation](data/noaa-rap.md)\n\n## NOAA US Climate Normals\n\nTypical climate conditions for the United States from 1981 to the present.\n\n* [Source](https://www.ncei.noaa.gov/products/land-based-station/us-climate-normals)\n* [Documentation](data/noaa-climatenormals.md)\n\n## National Agriculture Imagery Program\n\nNAIP provides US-wide, high-resolution aerial imagery.  This data set includes NAIP images from 2010 to the present.\n\n* [Source](https://www.fsa.usda.gov/programs-and-services/aerial-photography/imagery-programs/naip-imagery/)\n* [Documentation](data/naip.md)\n* [Notebook](https://nbviewer.jupyter.org/github/microsoft/AIforEarthDataSets/blob/main/data/naip.ipynb)\n* [Planetary Computer collection](https://planetarycomputer.microsoft.com/dataset/naip)\n\n## National Land Cover Database\n\nUS-wide data on land cover and land cover change at a 30m resolution with a 16-class legend.\n\n* [Source](https://www.mrlc.gov/)\n* [Documentation](data/nlcd.md)\n* [Notebook](https://nbviewer.jupyter.org/github/microsoft/AIforEarthDataSets/blob/main/data/nlcd.ipynb)\n\n## NatureServe Map of Biodiversity Importance (MoBI)\n\nHabitat information for 2,216 imperiled species occurring in the conterminous United States.\n\n* [Source](https://www.natureserve.org/conservation-tools/projects/map-biodiversity-importance)\n* [Documentation](data/mobi.md)\n* [Notebook](https://nbviewer.jupyter.org/github/microsoft/AIforEarthDataSets/blob/main/data/mobi.ipynb)\n* [Planetary Computer collection](https://planetarycomputer.microsoft.com/dataset/mobi)\n\n## Ocean Observatories Initiative CamHD\n\nVideo data from the [Ocean Observatories Initiative](https://oceanobservatories.org/) seafloor camera deployed at [Axial Volcano](https://en.wikipedia.org/wiki/Axial_Seamount) on the Juan de Fuca Ridge.\n\n* [Source](https://oceanobservatories.org/instrument-class/camhd/)\n* [Documentation](data/ooi-camhd.md)\n* [Notebook](https://nbviewer.jupyter.org/github/microsoft/AIforEarthDataSets/blob/main/data/ooi-camhd.ipynb)\n\n## Sentinel-1 GRD\n\nGlobal synthetic aperture radar (SAR) data from 2017-present, projected to ground range.\n\nSentinel-1 GRD data are in preview; access is granted by request.\n\n* [Source](https://sentinel.esa.int/web/sentinel/technical-guides/sentinel-1-sar/products-algorithms/level-1-algorithms/ground-range-detected)\n* [Documentation](data/sentinel-1-grd.md)\n* [Notebook](https://nbviewer.jupyter.org/github/microsoft/AIforEarthDataSets/blob/main/data/sentinel-1-grd.ipynb)\n\n## Sentinel-2 L2A\n\nGlobal optical imagery at 10m resolution from 2016-present.\n\n* [Source](https://sentinel.esa.int/web/sentinel/missions/sentinel-2)\n* [Documentation](data/sentinel-2.md)\n* [Notebook](https://nbviewer.jupyter.org/github/microsoft/AIforEarthDataSets/blob/main/data/sentinel-2.ipynb)\n* [Planetary Computer collection](https://planetarycomputer.microsoft.com/dataset/sentinel-2-l2a)\n\n## Sentinel-3 L2\n\nGlobal multispectral imagery at 300m resolution, with a revisit rate of less than two days, from 2016-present.\n\nSentinel-3 data are in preview; access is granted by request.\n\n* [Source](https://sentinel.esa.int/web/sentinel/missions/sentinel-3)\n* [Documentation](data/sentinel-3.md)\n* [Notebook](https://nbviewer.jupyter.org/github/microsoft/AIforEarthDataSets/blob/main/data/sentinel-3.ipynb)\n\n## Sentinel-5P\n\nGlobal atmospheric data from 2018-present.\n\nSentinel-5P data are in preview; access is granted by request.\n\n* [Source](https://sentinel.esa.int/web/sentinel/missions/sentinel-5p)\n* [Documentation](data/sentinel-5p.md)\n* [Notebook](https://nbviewer.jupyter.org/github/microsoft/AIforEarthDataSets/blob/main/data/sentinel-5p.ipynb)\n\n## TerraClimate\n\nMonthly climate and climatic water balance for global terrestrial surfaces from 1958-2019.\n\n* [Source](http://www.climatologylab.org/terraclimate.html)\n* [Documentation](data/terraclimate.md)\n* [Notebook](https://nbviewer.jupyter.org/github/microsoft/AIforEarthDataSets/blob/main/data/terraclimate.ipynb)\n* [Planetary Computer collection](https://planetarycomputer.microsoft.com/dataset/terraclimate)\n\n## UK Met Office CSSP China 20CRDS\n\nHistorical climate data for China, from 1851-2010.\n\n* [Source](https://www.metoffice.gov.uk/research/approach/collaboration/newton/climate-science-for-service-partnership-china)\n* [Documentation](data/uk-met-20crds.md)\n\n## UK Met Office Global Weather Data for COVID-19 Analysis\n\nData for COVID-19 researchers exploring relationships between COVID-19 and environmental factors.\n\n* [Source](https://medium.com/informatics-lab/met-office-and-partners-offer-data-and-compute-platform-for-covid-19-researchers-83848ac55f5f)\n* [Documentation](data/uk-met-covid-19.md)\n* [Notebook](https://nbviewer.jupyter.org/github/microsoft/AIforEarthDataSets/blob/main/data/uk-met-covid-19.ipynb)\n\n## University of Miami Coupled Model for Hurricanes Ike and Sandy\n\nModeled wind, wave, and current data for Hurricanes Ike and Sandy, produced by the National Renewable Energy Laboratory.\n\n* [Source](https://github.com/openEDI/documentation/blob/main/UMCM_Hurricanes.md)\n* [Documentation](data/umcm-hurricanes.md)\n\n## USFS Forest Inventory and Analysis\n\nStatus and trends on U.S. forest location, health, growth, mortality, and production, from the US Forest Service's  [Forest Inventory and Analysis](https://www.fia.fs.fed.us/) (FIA) program.\n\n* [Source](https://www.fia.fs.fed.us/)\n* [Documentation](data/forest-inventory-and-analysis.md)\n* [Notebook](https://nbviewer.jupyter.org/github/microsoft/AIforEarthDataSets/blob/main/data/forest-inventory-and-analysis.ipynb)\n* [Planetary Computer collection](https://planetarycomputer.microsoft.com/dataset/fia)\n\n## USGS 3DEP Seamless DEMs\n\n* [Source](https://www.usgs.gov/core-science-systems/ngp/3dep)\n* [Planetary Computer collection](https://planetarycomputer.microsoft.com/dataset/3dep-seamless)\n\n## USGS Gap Land Cover\n\n* [Source](https://www.usgs.gov/core-science-systems/science-analytics-and-synthesis/gap/science/land-cover-data-download)\n* [Planetary Computer collection](https://planetarycomputer.microsoft.com/dataset/gap)\n\n\n# Legal stuff\n\n## Contributing\n\nThis project welcomes contributions and suggestions.  Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.opensource.microsoft.com.\n\nWhen you submit a pull request, a CLA bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., status check, comment). Simply follow the instructions\nprovided by the bot. You will only need to do this once across all repos using our CLA.\n\nThis project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/).\nFor more information see the [Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/) or\ncontact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additional questions or comments.\n\n## Trademarks\n\nThis project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft\ntrademarks or logos is subject to and must follow\n[Microsoft's Trademark \u0026 Brand Guidelines](https://www.microsoft.com/en-us/legal/intellectualproperty/trademarks/usage/general).\nUse of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship.\nAny use of third-party trademarks or logos are subject to those third-party's policies.\n","funding_links":[],"readme_doi_urls":[],"works":{},"citation_counts":{},"total_citations":0,"keywords_from_contributors":["earth-observation","conservation","wildlife","biodiversity","3d-map","web-map","stac"],"project_url":"https://ost.ecosyste.ms/api/v1/projects/20896","html_url":"https://ost.ecosyste.ms/projects/20896"}