- Climate TRACE
- Dynamic World Project
- European Union (EU) Copernicus
- Federal Emergency Management Agency
- Global Land Ice Measurements from Space (GLIMS)
- India Water Resources Information System
- Resources for the Future (RFF)
- U.S. Bureau of Transportation Statistics
- U.S. Center for Disease Control and Prevention (CDC)
- U.S. Environmental Protection Agency (EPA)
- U.S. National Aeronautics and Space Administration (NASA)
- U.S. National Oceanic and Atmospheric Administration (NOAA)
- U.S. National Wildfire Coordinating Group
- United States Geological Service (USGS)
- Wildland Fire Interagency Geospatial Services
This dataset includes flooded regions computed from the Dynamic World dataset. These are regions labelled as water and outside regions marked as permanent water in the Hansen Global Forest Change dataset.
This dataset is produced for the Dynamic World Project by Google in partnership with National Geographic Society and the World Resources Institute.
ERA5 is the fifth generation ECMWF atmospheric reanalysis of the global climate. Reanalysis combines model data with weather observations from across the world into a globally complete and consistent dataset.
Land cover data from the Copernicus Land Cover viewer. Data Commons currently includes observations for US states and counties.
The National Flood Insurance Program (NFIP), managed by the Federal Emergency Management Agency (FEMA), enables homeowners, business owners and renters in participating communities to purchase federally backed flood insurance. The data includes insurance claims and amounts paid for flood damage to buildings and its contents aggregated by census-tracts, counties and states. This product uses the Federal Emergency Management Agency’s OpenFEMA API, but is not endorsed by FEMA. The Federal Government or FEMA cannot vouch for the data or analyses derived from these data after the data have been retrieved from the Agency’s website(s).
Data Commons includes relative measures of risk from the 18 natural hazards included in the study for counties and census tracts, as well as annual expected loss figures in USD from individual hazards and in aggregate. This study and associated data are released with this disclaimer.
A global inventory of glaciers, including surface areas.
The Water Resources Information System (WRIS) is a repository of water resources and related data for India at national, state and district level.
Water quality data measured at ground and surface water qualiy stations across India providing concentrations of dissolved constituents in water in terms of physical, chemical and biological parameters.
This dataset includes US forecast (till 2100) weather variability at 0.25 degree resolution, expressed as standard deviation, skewness and kurtosis for daily min/max temperature and precipitation. Additionally, it includes statistics for Heavy Precipitation Index and Consecutive Dry Days variables.
This dataset includes US county-level forecast (till 2100) weather variability expressed as standard deviation, skewness and kurtosis for daily min/max temperature and precipitation. Additionally, it includes statistics for Heavy Precipitation Index and Consecutive Dry Days variables. These were aggregated from stats at 0.25 degree resolution by Data Commons.
This dataset includes US historical weather variability at 4 KM resolution, expressed as standard deviation, skewness and kurtosis for daily min/max temperature and precipitation. Additionally, it includes statistics for Heavy Precipitation Index and Consecutive Dry Days variables.
This dataset includes US county-level historical weather variability expressed as standard deviation, skewness and kurtosis for daily min/max temperature and precipitation. Additionally, it includes statistics for Heavy Precipitation Index and Consecutive Dry Days variables. These were aggregated from stats at 4 KM resolution by RFF. This data is made available for non-commercial purposes only.
Information related to transportation characteristics for households which includes data at Census Tract level on daily personal travel, including information on household and demographic characteristics, employment status, vehicle ownership, trips taken, modal choice, and other related transportation data pertinent to U.S. households.
Data Commons has imported data on Palmer Drought Severity Index, Standardiazed Precipitation Evapotranspiration Index, Standardized Precipitation Index, Ozone, and PM2.5.
Air quality data collected from outdoor monitors on the county, CBSA, and site monitor level.
Environmental justice mapping tool based on environmental and demographic indicators.
Annual reporting of greenhouse gases from large emission sources.
The National Emissions Inventory (NEI) is a comprehensive and detailed estimate of air emissions of criteria pollutants, hazardous pollutants and greenhouse gases from 188 OnRoad air emission sources (such as Mobile Sources Highway Vehicles Electricity and Mobile Sources Border Crossing), 248 NonRoad air emissions sources (such as Mobile Sources Off-highway Vehicle Gasoline and LPG Construction Mining Equipment), 703 NonPoint air emissions sources (such as Industrial Processes Oil Gas Exploration Production and LPG Distribution) and 5818 Point air emissions sources (such as Chemical Evaporation Organic Solvent Evaporation and External Combustion Electric Generation Boilers)at US County Level.
Site contamination data, hazard scores and more.
Atmospheric variables from multiple CMIP5 climate models for the United States.
Atmospheric variables from multiple CMIP5 climate models for the entire world.
Atmospheric variables from multiple CMIP6 climate models for the entire world.
The Visible Infrared Imaging Radiometer Suite (VIIRS) aboard S-NPP satellite provides 375m resolution data for active fires. This dataset includes area under fire per level 13 S2 cell every day starting in 2012.
Historical monthly SPI calculated from data observed from German Meteorological Service(Deutscher Wetterdienst).
The IBTrACS project provides tropical cyclone best track data in a centralized location. Data Commons includes cyclone name, start date, end date, max wind speed, minimum pressure, max classification, oceanic basin, and affected places.
Historical weather data from stations reported largely from NOAA Global Historical Climate Network (GHCN).
Global daily weather forecast generated from National Centers for Environmental Prediction (NCEP) model.
Occurrence of storms and other significant weather phenomena having sufficient intensity to cause loss of life, injuries, significant property damage, and/or disruption to commerce; rare, unusual, weather phenomena that generate media attention, such as snow flurries in South Florida or the San Diego coastal area; and other significant meteorological events, such as record maximum or minimum temperatures or precipitation that occur in connection with another event.
Information related to the wildland fire management incidents and resources.
Earthquake source parameters (e.g. hypocenters, magnitudes, phase picks and amplitudes) and other products (e.g. moment tensor solutions, macroseismic information, tectonic summaries, maps) produced by contributing seismic networks. Data Commons includes date, time, location, magnitudes, magnitude errors, depth, depth error, and review status of earthquakes of magnitude 3 onwards starting from 1900.
Codes, names, coordinates, and more information for all “named physical and cultural geographic features (except roads and highways) of the United States”, maintained by GNIS. Data Commons uses this dataset to build containment relationships between places from the US Census Gazetteer dataset.
Point Locations for all reported wildland fires in the United States.
The Wildland Fire Interagency Geospatial Services (WFIGS) Group provides authoritative geospatial data products under the interagency Wildland Fire Data Program. This dataset provides perimeters for all reported wildland fires in the United States. We simplify those parameters by using Ramer-Douglas-Peucker algorithm on geoJsonCoordinates with epsilon of 0.01.