Floods Data Pathfinder - Find Data

Floods are one of the most costly natural disasters. NASA provides many datasets and tools that can aid with decisions regarding flood response and mitigation.

Being aware of conditions that can make an area more susceptible to flooding is a critical first step in preparing for and mitigating these events.

Common Precipitation Data at a Glance

Flooding can occur in any location where precipitation occurs. Measuring rainfall helps advance our understanding of Earth's water cycle, improving forecasts of extreme events such as flooding.

Relevant datasets are from sensors shown in the table below. This is not intended to be an exhaustive list of all sensors or missions producing data relevant to this Data Pathfinder. An asterisk (*) by an entry indicates that near real-time (NRT) data products are available through NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE). LANCE data products are available within three hours of a satellite observation. If low-latency is not a primary concern, users are encouraged to use standard science products, which are produced using the best available calibration, ancillary, and ephemeris information. To learn more about the difference between NRT and Standard Science Products, see Near Real Time versus Standard Products.

Spatial Resolution Spatial Coverage Temporal Resolution Temporal Coverage Spectral Resolution Name (Sensor, Model, etc.) Satellite/ Platform Observation, Model, or Reanalysis File Format
15 km Global 2-Day 2012-Near Present 16 channels ranging in frequency from 6.925 GHz to 89 GHz       *AMSR2 SHIZUKU (GCOM-W1) Observation HDF5
25 km Global 12 hours 2002-present 2,378 infrared channels in the 3.74 to 15.4 micron spectral range *AIRS Aqua Observation HDF-EOS
0.5° Global Daily 1983-2021 Varies Varies GPCP Observation netCDF
0.1° Global 30-Minute, Daily, Monthly 2000-Present Varies Varies GPM IMERG Observation HDF, netCDF, or GeoTIFF
5 km 50° N to 50° S, 180° W to 180° E 5-Day, 10-Day, 15-Day 2000-Present N/A CHIRPS-GEFS N/A Model GeoTIFF 
1 km North America, Hawaii, Puerto Rico Daily North America, Hawaii: 1980-Present
Puerto Rico: 1950-Present
N/A Daymet N/A Model netCDF, Cloud Optimized GeoTIFF (COG)
0.01°, 0.1°, 0.125°, 0.25°, 1° Global Hourly, 3-Hour, Daily, Monthly 2000-2022 N/A LDAS N/A Model netCDF
0.5° x 0.625° Global Hourly, Daily, Monthly 1980-Present N/A MERRA-2 N/A Reanalysis netCDF
0.25º x 0.312° Global 15-Minutes, Hourly Near-real time assimilation (DAS), 10-day forecast at 00z, and 5-day forecast at 12z N/A GEOS-5 FP N/A Model netCDF
0.25° Global Daily 1950-2100 N/A NEX-GDDP-CMIP6 N/A Model/Downscaled Model Outputs Cloud-Optimized GeoTIFF (COG)

Use the Precipitation Data

Use Cases and Articles
Tutorials
Data Visualizations
GIS-Ready Tools and Tutorials
Data Access Tools
  • Users may access and visualize data directly through ClimateSERV. Datasets include IMERG, Evaporative Stress Index, SMAP Soil Moisture, Rainfall, and NDVI
  • The Data Rods Explorer (DRE) interface enables the visualization and downloading of NASA observation retrievals and land surface model (LSM) outputs by space, time, and variable
Data Customizing Tools
Programming Tools

Earth Observation Data by Sensor

AIRS

The Atmospheric Infrared Sounder (AIRS) is a grating spectrometer aboard NASA's Aqua satellite. In combination with the Advanced Microwave Sounding Unit (AMSU) and the Humidity Sounder for Brazil (HSB), AIRS constitutes an innovative atmospheric sounding group of visible, infrared, and microwave sensors. 

The AIRS Precipitation Estimate is an estimate of daily precipitation measured in millimeters using cloud-related parameters of cloud-top pressure, fractional cloud cover, and cloud-layer relative humidity. The precipitation algorithm is a regression between these parameters and observed precipitation data. It is an estimate from AIRS and is intended for merging into the precipitation product of the Global Precipitation Climatology Project (GPCP).

Create and share layered maps with AIRS data using the AIRS Applications Browse Tool.

Research-quality data products can be accessed using Earthdata Search:

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AMSR2

The Advanced Microwave Scanning Radiometer 2 (AMSR2) instrument collects data that indicate the rate at which precipitation is falling on the ocean surface in millimeters per hour (mm/hr). 

Data can be accessed and interactively explored using NASA Worldview:

Create and share layered maps with AMSR2 data using the AIRS Applications Browse Tool.

Research-quality data products can be accessed using Earthdata Search:

Near real-time (NRT) Surface Precipitation products are generated within three hours by the Land, Atmosphere Near real-time Capability for EOS (LANCE). The NRT products are generated in HDF-EOS-5 augmented with netCDF-4/CF metadata and are available via HTTPS. If data latency is not a primary concern, please use science quality products, which are an internally consistent, well-calibrated record of Earth's geophysical properties to support science. AMSR2 NRT data also are available through Earthdata Search:

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GPM IMERG

NASA's Precipitation Measurement Missions (PMM) provide a continuous record of precipitation data through the Tropical Rainfall Measuring Mission (TRMM; operational 1997 to 2015) and the Global Precipitation Measurement mission (GPM; launched in 2014). GPM, the TRMM successor mission, provides more accurate measurements, improved detection of light rain and snow, and extended spatial coverage.

Data products from TRMM and GPM are available individually and have been integrated with data from a global constellation of satellites to yield precipitation estimates with improved spatial coverage and temporal resolution. The first integrated product was the TRMM Multi-satellite Precipitation Analysis (TMPA), which has been superseded by the Integrated Multi-satellitE Retrievals for GPM (IMERG). IMERG's multiple runs accommodate different user requirements for accuracy and latency (Early = 4 hours, e.g., for flash flood events; Late = 12 hours, e.g., for crop forecasting; and Final = 3 months, with the incorporation of rain gauge data, for research).

GPM data can be visualized using NASA Worldview:

The Short-term Prediction Research and Transition (SPoRT) project at NASA's Marshall Space Flight Center in Huntsville, Alabama, is a NASA- and NOAA-funded activity to transition experimental and quasi-operational satellite observations and research capabilities to the operational weather community to improve short-term weather forecasts on a regional and local scale. SPoRT offers a Near Real-Time Viewer for the following IMERG data products:

  • GPM IMERG Early
  • GPM IMERG Late
  • IMERG-Tropics

Users may access and visualize these data directly through ClimateSERV. Additional datasets include IMERG, Evaporative Stress Index, Soil Moisture Active Passive (SMAP) Soil Moisture, Rainfall, and Normalized Difference Vegetation Index (NDVI).

An online interactive tool called Giovanni enables users to map visualizations of IMERG data products. These visualizations can be downloaded as PNG images or as GeoTIFF or KMZ files; time-series data are available as CSV data files, and animations are in either webm video format or animated GIF images:

  • IMERG Final
    • Data are available from 2000-present
  • GPM
    • Includes all IMERG runs: Early, Late, and Final
  • TMPA

NASA Earthdata GIS Products:

Near-real time (NRT) data:

  • IMERG Early Run Half-Hourly 
    • The Early Run product at NASA's Global Precipitation Measurement website is generated every half hour with a 6-hour latency from the time of data acquisition

Research-quality data products can be accessed using Earthdata Search:

  • TMPA
    • Rainfall estimates at three hours, 1 day, or NRT and accumulated rainfall at 3 hours and 1 day; data are available from 1997
  • IMERG
    • Early, Late, and Final precipitation data on the half-hour or 1-day timeframe; data are available from 2000

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Model Data

Daymet

Another NASA source for precipitation data is Daymet, which can be accessed through NASA's Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC). Daymet is a collection of gridded estimates of daily weather parameters including minimum and maximum temperature, precipitation, vapor pressure, radiation, snow water equivalent, and day length at 1 km resolution over North America, Puerto Rico, and Hawaii. Daymet data are available from 1980 to present (North America and Hawaii) and from 1950 to present (Puerto Rico). Data can be retrieved in a variety of ways, including: Earthdata Search; an API available through ORNL DAAC; ORNL DAAC tools; and through the Application for Extracting and Exploring Analysis Ready Samples (AppEEARS) application. Along with daily data, annual Daymet climatologies also are available.

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GEOS-5

NASA's Goddard Earth Observing System, Version 5 (GEOS-5) is an atmospheric model used to study the physics of the atmosphere. GEOS-5 has a series of weather maps that can be used to predict parameters such as wind speed up to 240 hours out, which can be used to forecast the movement of a smoke plume over time.

  • GEOS-5 Weather Maps
    • Within the viewer, select the parameter or field of interest, the area of interest, and indicate the forecast time and the forecast lead hour. Selecting "Animate" shows the forecast for the given parameter over the time period indicated (it may take time to load the images to animate). For wind speed near the surface, select 850 as your level (850 hPa is approximately 5,000 ft/1,500 m above sea level)

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NEX-GDDP-CMIP6

The NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset is comprised of high-resolution, bias-corrected global downscaled climate projections derived from the General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 6 (CMIP6) and across all four “Tier 1” greenhouse gas emissions scenarios known as Shared Socioeconomic Pathways (SSPs). 

This dataset provides a set of global, high resolution, bias-corrected climate change projections that can be used to evaluate climate change impacts on processes that are sensitive to finer-scale climate gradients and the effects of local topography on climate conditions. Uses include: air temperature, precipitation volume, humidity, stellar radiation, and atmospheric wind speed.

NEX-GDDP-CMIP6 data are available through the NASA Center for Climate Simulation (NCCS):

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CHIRPS-GEFS

SERVIR (a joint initiative of NASA, USAID, and geospatial organizations in Asia, Africa, and Latin America) and the Climate Hazards Group (CHG) at University of California at Santa Barbara have developed an improved rainfall forecast dataset that merges two highly recognized datasets: Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) and the NCEP’s Global Ensemble Forecasting System (GEFS). GEFS is a weather forecast system that provides daily forecasts out to 16 days at 1º x 1º resolution at six-hour intervals.The combined CHIRPS-GEFS dataset uses the higher spatial resolution of CHIRPS and the advanced forecasting ability of GEFS to provide up to a 16-day forecast updated every five days at a global spatial resolution of 5 km.

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GPCP

The Global Precipitation Climatology Project (GPCP) is the precipitation component of an internationally coordinated set that combines observations and satellite precipitation data. 

Using an online interactive tool called Giovanni, users can map visualizations of GPCP Precipitation data products and download these visualizations as PNG images or as GeoTIFF or KMZ files; time-series data are available as CSV data files, and animations are in either webm video format or animated GIF images:

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LDAS

The Land Data Assimilation System (LDAS) includes a global collection (GLDAS), a North American collection (NLDAS), National Climate Assessment-Land Data Assimilation System (NCA-LDAS), and a Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS). LDAS uses measurements including air temperature, precipitation, soil texture, and topography. GLDAS modeled data are available from January 1948 to present. NLDAS modeled datasets are available from January 1979 to present. FLDAS modeled datasets are available from January 1982 to present.

Data can be accessed and interactively explored using NASA Worldview:

Using an online interactive tool called Giovanni, data products can be visualized as a time-averaged map, an animation, seasonal maps, scatter plots, or a time series, as well as downloaded in .CSV format:

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Reanalysis Data

MERRA-2

The Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) provides data beginning in 1980. Due to the amount of historical data available, MERRA-2 data can be used to look for trends and patterns as well as anomalies. There are several options available: 1-hourly, 3-hourly, 6-hourly, daily, and monthly. These options provide information on precipitation.

Data can be accessed and interactively explored using NASA Worldview:

Using an online interactive tool called Giovanni, map visualizations of MERRA-2 Precipitation data products can be downloaded as PNG images or as GeoTIFF or KMZ files; time-series data are available as CSV data files, and animations are in either webm video format or animated GIF images:

Geographic Information Systems (GIS) products using MERRA-2 reanalysis data are produced by NASA's Prediction of Worldwide Energy Resources (POWER) project:

Research-quality air surface temperature data products can be accessed using Earthdata Search:

The NASA POWER Data Access Viewer provides MERRA-2 meteorological parameters through a web mapping application with the capability for data subsetting, charting, and visualizing. The data are also available via API as well as via OPeNDAP:

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Soil moisture is an important factor in flood prediction, mitigation, and preparedness efforts since soil moisture content is critical in determining the susceptibility of an area to flooding. Areas with high soil moisture levels reduce the soil's capacity to absorb additional water, increasing the risk of flooding during heavy rainfall events. Satellite data can provide a global view of soil moisture. Although ground-based measurements provide data at a higher resolution, these data are often sparse and have limited coverage. 

Common Soil Moisture Data at a Glance

Relevant datasets are from sensors shown in the table below. This is not intended to be an exhaustive list of all sensors or missions producing data relevant to this Data Pathfinder. An asterisk (*) by an entry indicates that near real-time (NRT) data products are available through NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE). LANCE data products are available within three hours of a satellite observation. If low-latency is not a primary concern, users are encouraged to use standard science products, which are produced using the best available calibration, ancillary, and ephemeris information. To learn more about the difference between NRT and Standard Science Products, see Near Real Time versus Standard Products.

Spatial Resolution Spatial Coverage Temporal Resolution Temporal Coverage Name (Sensor, Model, etc.) Satellite/ Platform Observation, Model, or Reanalysis File Format
9 km to 40 km Near global Daily, 3-Day 2015-Present Radar (active; no longer functional)
*Microwave radiometer (passive)
SMAP Observation and Model HDF5
25 km Global 50 min 2012-Near Present *AMSR2 SHIZUKU (GCOM-W1) Observation HDF5
0.01°, 0.1°, 0.125°, 0.25°, 1° Global Hourly, 3-Hour, Daily, Monthly 1948-Present LDAS N/A Model netCDF
3 km Continental U.S., Alaska, Puerto Rico Daily 2003-2021 SPoRT-LiS N/A Model GRIB
9 km Global 3-Hour 2015-Present GMAO SMAP N/A Model HDF5
0.5° x 0.625° Global Hourly, Daily, Monthly 1980-Present MERRA-2 N/A Reanalysis netCDF
0.125° North America 7-Day 2002-Present GRACE-DA-DM N/A Model netCDF

Use the Soil Moisture Data

Tutorials
GIS-Ready Tools and Tutorials
Data Access Tools
  • Users can visualize data directly through ClimateSERV. Additional datasets include IMERG, Evaporative Stress Index, Rainfall, and NDVI
  • SMAP Soil Moisture Level 3, 9 km Day and Night Data are available through the State of the Ocean (SOTO) Visualization Tool
  • Soil Moisture Visualizer Guide
  • Data Rods Explorer (DRE) enables the visualization and downloading of NASA observation retrievals and land surface model (LSM) outputs by space, time, and variable. The key variables are precipitation, wind, temperature, surface downward radiation flux, heat flux, humidity, soil moisture, groundwater, runoff, and evapotranspiration. These variables describe the main components of the water cycle over land masses
  • SMAP Data Access Tool
  • Programmatic Data Access Guide (SMAP)
Data Customizing Tools
  • Soil Moisture Visualizer integrates a variety of North American soil moisture datasets. For more information on the available datasets and use of the visualizer, view the Soil Moisture Visualizer Guide
  • AppEEARS enables users to subset data by defining specific point(s) or area(s) of interest; output data can be downloaded in CSV (point), GeoTIFF (area), or NetCDF4 (area) formats
  • MODIS/VIIRS Subsetting Tools Suite
    • Global Subset Tool: Request a subset for any location as a GeoTiff and in text format, including interactive time-series plots
    • Fixed Sites Subsets Tool: Download pre-processed subsets for more than 3,000 field and flux tower sites for validation of models and remote sensing products
    • Web Service: Retrieve subset data (in real-time) for any location, time period, and area programmatically using a REST web service; web service clients and libraries are available in multiple programming languages, allowing integration of subsets into a workflow
  • For more information on a suite of NASA data tools for searching and ordering, data handing, subsetting and filtering, geolocating, reprojecting, and mapping, as well as visualizing and analyzing data, visit the NASA Earthdata Data Tools Page
Programming Tools

Earth Observation Data by Sensor

SMAP

NASA's Soil Moisture Active Passive satellite (SMAP), launched in 2015, measures the moisture in the top 5 cm of soil globally daily and every two to three days at a resolution of 9 to 36 km. 

Near real-time SMAP imagery can be interactively explored using NASA Worldview:

  • SMAP
    • includes root zone and surface soil moisture values

The Soil Moisture Visualizer, available at NASA's Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC), integrates ground-based, SMAP, and other soil moisture data into a visualization and data distribution tool.

Research quality data products can be accessed using Earthdata Search:

Near real-time (NRT) SMAP data are available through NASA’s LANCE within 60 to 125 minutes after a satellite observation:

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AMSR2

The Advanced Microwave Scanning Radiometer (AMSR) for EOS (AMSR-E) and the AMSR2 instruments provide volumetric soil moisture data. AMSR2 provides global passive microwave measurements of Surface Soil Moisture. Near real-time (NRT) products are generated within 3 hours of the last observations in the file.

Data can be visualized using NASA Worldview:

Data products can be visualized as a time-averaged map, an animation, seasonal maps, scatter plots, or a time series using a NASA interactive tool called Giovanni:

Near-real time data:

  • AMSR2 NRT data are available through LANCE (global data from 2018 to present)

Research-quality data products can be accessed using Earthdata Search:

Back to the Table

Model Data

SPoRT-LiS

The Short-term Prediction Research and Transition (SPoRT) project at NASA's Marshall Space Flight Center in Huntsville, Alabama, is a NASA- and NOAA-funded activity to transition experimental and quasi-operational satellite observations and research capabilities to the operational weather community to improve short-term weather forecasts on a regional and local scale.

The SPoRT-Land Information System (SPoRT-LiS) provides real-time 3 km LiS data on the following parameters: volumetric soil moisture, relative soil moisture, column-integrated relative soil moisture, and green vegetation fraction.

SPoRT offers a Near Real-Time Viewer that includes SMAP datasets for the following regions:

  • Enhanced Alaska (9 km)
  • Enhanced Continental U.S. (CONUS) (9 km)
  • Enhanced East Africa (9 km)
  • Level 2 CONUS
  • Level 2 East Africa

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LDAS

NASA, in collaboration with other agencies, has developed models of soil moisture content that incorporate satellite information with ground-based data (when ground-based data are available). These models are part of the Land Data Assimilation System (LDAS), which includes a global collection (GLDAS) and a North American collection (NLDAS). The Famine Early Warning Systems Network (FEWS NET) LDAS (FLDAS) datasets offer global monthly data with a 0.1º x 0.1º spatial resolution covering the period from January 1982 to present. FLDAS Soil Moisture data are available from the surface to the depth of 10 cm and 100 cm, and re-expressed as volumetric water content percent. LDAS takes inputs of measurements like precipitation, soil texture, topography, and leaf area index and uses these inputs to model output estimates of soil moisture and evapotranspiration.

FLDAS datasets also are available on the Early Warning eXplorer (EWX): Next Generation Viewer.

LDAS data are available through NASA Worldview:

The NLDAS experimental drought monitor is derived from near real-time soil moisture output model data: 

Soil MERGE (SMERGE) is a root-zone soil moisture product developed by merging NLDAS land surface model output with surface satellite retrievals from the ESA (European Space Agency) Climate Change Initiative. This data product contains root-zone soil moisture of 0-40 cm layer, Climate Change Initiative (CCI)-derived soil moisture anomalies of 0-40 cm layer, and a soil moisture data estimation flag:

NLDAS, GLDAS, and SMERGE data products can be visualized as a time-averaged map, an animation, seasonally-averaged maps, scatter plots, or a time series using a NASA interactive data analysis tool called Giovanni:

LDAS Soil Moisture data from GLDAS, NLDAS and FLDAS are available in Earthdata Search:

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GRACE-DA-DM

Weekly soil moisture and groundwater drought indicators are available each week based on terrestrial water storage observations derived from GRACE satellite data and integrated with other observations, using a sophisticated numerical model of land surface water and energy processes, referred to as GRACE Data Assimilation for Drought Monitoring (GRACE-DA-DM). GRACE-DA-DM data are available through Earthdata Search:

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GMAO SMAP

NASA’S Global Modeling And Assimilation Office (GMAO), in collaboration with The University of Montana and NASA's Jet Propulsion Laboratory, provides value-added Level 4 data products. These Level 4 datasets rely on the merger of SMAP observations into physically-based numerical models of the land surface water, energy, and carbon cycles. Available Level 4 data include global, 9-km, 3-hourly estimates of surface and root zone soil moisture, surface and soil temperature, and land surface fluxes, along with algorithm diagnostics from the ensemble-based data assimilation system. Level 4 data also include global, 9-km, daily estimates of net ecosystem carbon dioxide (CO2) exchange, component carbon stocks and fluxes, and sub-grid information broken down by plant functional types.

Near real-time SMAP imagery can be interactively explored using NASA Worldview:

These data products are available from Earthdata Search:

Back to the Table

Reanalysis Data

MERRA-2

The Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) provides data beginning in 1980. Due to the amount of historical data available, MERRA-2 data can be used to look for trends and patterns, as well as anomalies. Hourly and monthly data options are available.

MERRA -2 Soil Moisture data products can be visualized as a time-averaged map, an animation, seasonally-averaged maps, scatter plots, or a time series using a NASA interactive data analysis tool called Giovanni:

MERRA-2 Soil Moisture data in Earthdata Search:

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Soil moisture is important in forecasting fire events as the dryness of the soil contributes to fire potential. Satellite data can provide a global view of soil moisture. Although ground-based measurements provide data at a higher resolution, these data are often sparse and have limited coverage. The preferred measurement (satellite vs. ground-based) should be chosen based upon your needs.

Common Measurements at a Glance

Relevant datasets are from sensors shown in the table below. This is not intended to be an exhaustive list of all sensors or missions producing data relevant to wildfires. An asterisk (*) by an entry indicates that near real-time (NRT) data products are available through NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE). LANCE data products are available within three hours of a satellite observation. If low-latency is not a primary concern, users are encouraged to use standard science products, which are produced using the best available calibration, ancillary, and ephemeris information. To learn more about the difference between NRT and Standard Science Products, see Near Real Time versus Standard Products.

Spatial Resolution Spatial Coverage Temporal Resolution Temporal Coverage Name (Sensor, Model, etc.) Satellite/ Platform Observation, Model, or Reanalysis
9 km to 40 km Near global Daily, 3-Day 2015-Present Radar (active; no longer functional)
*Microwave radiometer (passive)
SMAP Observation and Model
25 km Global 50 min 2012-Near Present *AMSR-2 SHIZUKU (GCOM-W1) Observation
0.01°, 0.1°, 0.125°, 0.25°, 1° Global Hourly, 3-Hour, Daily, Monthly 1948-Present LDAS N/A Model
3 km Continental U.S., Alaska, Puerto Rico Daily 2003-2021 SPoRT-LiS N/A Model
9 km Global 3-Hour 2015-Present GMAO SMAP N/A Model
0.5° x 0.625° Global Hourly, Daily, Monthly 1980-Present MERRA-2 N/A Reanalysis
0.125° North America 7-Day 2002-Present GRACE-DA-DM N/A Model

Earth Observation Data by Sensor

SMAP

NASA's Soil Moisture Active Passive satellite (SMAP), launched in 2015, measures the moisture in the top 5 cm of soil globally daily and every 2 to 3 days at a resolution of 9 to 36 km. 

Near real-time SMAP imagery can be interactively explored using NASA Worldview:

  • SMAP
    • includes root zone and surface soil moisture values

The Soil Moisture Visualizer, available at NASA's Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC), integrates ground-based, SMAP, and other soil moisture data into a visualization and data distribution tool.

Research quality data products can be accessed using Earthdata Search:

Near real-time (NRT) SMAP data are available through NASA’s LANCE within 60 to 125 minutes after a satellite observation:

AMSR-2

The Advanced Microwave Scanning Radiometer (AMSR) for EOS (AMSR-E) and the AMSR-2 instruments provide volumetric soil moisture data. AMSR2 provides global passive microwave measurements of Surface Soil Moisture. Near real-time (NRT) products are generated within 3 hours of the last observations in the file.

Data can be visualized using NASA Worldview:

Data products can be visualized as a time-averaged map, an animation, seasonal maps, scatter plots, or a time series using a NASA interactive tool called Giovanni:

Near-real time data:

  • AMSR-2 NRT data are available through LANCE (global data from 2018 to present)

Research-quality data products can be accessed using Earthdata Search:


Model Data

SPoRT-LiS

The Short-term Prediction Research and Transition (SPoRT) project at NASA's Marshall Space Flight Center in Huntsville, Alabama, is a NASA- and NOAA-funded activity to transition experimental and quasi-operational satellite observations and research capabilities to the operational weather community to improve short-term weather forecasts on a regional and local scale.

The SPoRT-Land Information System (SPoRT-LiS) provides real-time 3 km LiS data on the following parameters: volumetric soil moisture, relative soil moisture, column-integrated relative soil moisture, and green vegetation fraction.

SPoRT offers a Near Real-Time Viewer that includes SMAP datasets for the following regions:

  • Enhanced Alaska (9 km)
  • Enhanced Continental U.S. (CONUS) (9 km)
  • Enhanced East Africa (9 km)
  • Level 2 CONUS
  • Level 2 East Africa

LDAS

NASA, in collaboration with other agencies, has developed models of soil moisture content that incorporate satellite information with ground-based data (when ground-based data are available). These models are part of the Land Data Assimilation System (LDAS), which includes a global collection (GLDAS) and a North American collection (NLDAS). The Famine Early Warning Systems Network (FEWS NET) LDAS (FLDAS) datasets offer global monthly data with a 0.1º x 0.1º spatial resolution covering the period from January 1982 to present. FLDAS Soil Moisture data are available from the surface to the depth of 10 cm and 100 cm, and re-expressed as volumetric water content percent. LDAS takes inputs of measurements like precipitation, soil texture, topography, and leaf area index and uses these inputs to model output estimates of soil moisture and evapotranspiration.

FLDAS datasets also are available on the Early Warning eXplorer (EWX): Next Generation Viewer.

LDAS data are available through NASA Worldview:

The NLDAS experimental drought monitor is derived from near real-time soil moisture output model data: 

Soil MERGE (SMERGE) is a root-zone soil moisture product developed by merging NLDAS land surface model output with surface satellite retrievals from the ESA (European Space Agency) Climate Change Initiative. This data product contains root-zone soil moisture of 0-40 cm layer, Climate Change Initiative (CCI)-derived soil moisture anomalies of 0-40 cm layer, and a soil moisture data estimation flag:

NLDAS, GLDAS, and SMERGE data products can be visualized as a time-averaged map, an animation, seasonally-averaged maps, scatter plots, or a time series using a NASA interactive data analysis tool called Giovanni:

LDAS Soil Moisture data from GLDAS, NLDAS and FLDAS are available in Earthdata Search:

GRACE-DA-DM

Weekly soil moisture and groundwater drought indicators are available each week based on terrestrial water storage observations derived from GRACE satellite data and integrated with other observations, using a sophisticated numerical model of land surface water and energy processes, referred to as GRACE Data Assimilation for Drought Monitoring (GRACE-DA-DM). GRACE-DA-DM data are available through Earthdata Search:

GMAO SMAP

NASA’S Global Modeling And Assimilation Office (GMAO), in collaboration with The University of Montana and NASA's Jet Propulsion Laboratory, provides value-added Level 4 data products. These Level 4 datasets rely on the merger of Soil Moisture Active Passive (SMAP) observations into physically-based numerical models of the land surface water, energy, and carbon cycles. Available Level 4 data include global, 9-km, 3-hourly estimates of surface and root zone soil moisture, surface and soil temperature, and land surface fluxes, along with algorithm diagnostics from the ensemble-based data assimilation system. Level 4 data also include global, 9-km, daily estimates of net ecosystem carbon dioxide (CO2) exchange, component carbon stocks and fluxes, and sub-grid information broken down by plant functional types.

Near real-time SMAP imagery can be interactively explored using NASA Worldview:

These data products are available from Earthdata Search:


Reanalysis Data

MERRA-2

The Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) provides data beginning in 1980. Due to the amount of historical data available, MERRA-2 data can be used to look for trends and patterns, as well as anomalies. Hourly and monthly data options are available.

MERRA -2 Soil Moisture data products can be visualized as a time-averaged map, an animation, seasonally-averaged maps, scatter plots, or a time series using a NASA interactive data analysis tool called Giovanni:

MERRA-2 Soil Moisture data in Earthdata Search:

Seasonal water runoff from snowpack and glaciers, when combined with rainfall, can affect the timing and magnitude of river flows and significantly impact the risk of flooding events. Snow Water Equivalent (SWE) is the amount of water contained in snowpack. It is analogous to melting the snow and measuring the depth of the resulting pool of water. SWE measurements are useful for assessing both the potential surface runoff from snowmelt and the water availability for regions in lower elevations. Snow cover and SWE are critical variables for flood prediction and mitigation efforts in these regions.

Common Snow Cover/SWE Data at a Glance

Relevant datasets are from sensors shown in the table below. This is not intended to be an exhaustive list of all sensors or missions producing data relevant to this Data Pathfinder. An asterisk (*) by an entry indicates that near real-time (NRT) data products are available through NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE). LANCE data products are available within three hours of a satellite observation. If low-latency is not a primary concern, users are encouraged to use standard science products, which are produced using the best available calibration, ancillary, and ephemeris information. To learn more about the difference between NRT and Standard Science Products, see Near Real Time versus Standard Products.

Spatial Resolution Spatial Coverage Temporal Resolution Temporal Coverage Spectral Resolution Satellite/ Platform Sensor(s)/ Model Name Observation, Model, or Reanalysis File Format
500 m, 1 km, 0.05° Global 1-2 days,
8 Days,
Monthly
2000-Present 36 bands ranging from 0.4 µm to 14.4 µm Terra and Aqua *MODIS Observation HDF-EOS
15 km Global 2 Days 2012-Near Present 16 channels ranging in frequency from 6.925 GHz to 89 GHz SHIZUKU (GCOM-W1) *AMSR2 Observation HDF5
3 m, 50 m California, Colorado Varies 2013-2019 0.38 µm to 1.05 µm N/A ASO Observation GeoTIFF
1 km North America, Hawaii, Puerto Rico Daily North America, Hawaii: 1980-Present

Puerto Rico: 1950-Present
N/A N/A Daymet Model netCDF, Cloud Optimized GeoTIFF (COG) 
0.01°, 0.1°, 0.125°, 0.25°, 1° Global Hourly, 3-Hourly, Daily, Monthly 1948-Present N/A N/A LDAS Model netCDF
0.5° x 0.625° Global Hourly, Daily, Monthly 1980-Present N/A N/A MERRA-2 Reanalysis netCDF

Use the Snow Cover/SWE Data

Tutorials
Data Visualizations
GIS-Ready Tools and Tutorials
Data Access Tools
  • Snow Today, available through the National Snow and Ice Data Center (NSIDC), is a NASA-supported scientific analysis website that provides a snapshot and interpretation of snow conditions in near real-time across the Western U.S. Snow Today updates daily images on snow conditions and relevant data and also provides monthly scientific analyses from January to May, or more frequently as conditions warrant
Data Customizing Tools
  • Daymet Single Pixel Data Extraction—Web Services 
  • AppEEARS offers a simple and effective way to extract, transform, visualize, and download Snow cover data products and allows users to subset data by defining specific point(s) or area(s) of interest; output data can be downloaded in CSV (point), GeoTIFF (area), or NetCDF4 (area) formats
  • MODIS/VIIRS Subsetting Tools Suite
  • For more information on a suite of NASA data tools for searching and ordering, data handing, subsetting and filtering, geolocating, reprojecting, and mapping, as well as visualizing and analyzing data, visit the NASA Earthdata Data Tools Page
Programming Tools

Earth Observation Data by Sensor

MODIS

Near real-time snow cover data can be interactively explored using NASA Worldview:

Research quality data products can be accessed using Earthdata Search:

  • MODIS Snow Cover
    • Data are available daily, 8-day, or monthly at various resolutions; datasets are also customizable to GeoTIFF

Near real-time (NRT) MODIS snow cover data are available through LANCE 60 to 125 minutes after a satellite observation. 

GIS layer displaying water states (ice, snow, water, etc.):

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AMSR2

The Advanced Microwave Scanning Radiometer (AMSR) for EOS (AMSR-E) instrument and the AMSR2 instrument provide SWE data.

Near real-time data can be interactively explored using NASA Worldview:

Research quality data products can be accessed using Earthdata Search:

  • AMSR-E SWE
    • Data are available from 2002 to 2011 in daily, 5-day, and monthly timeframes; datasets are also customizable to GeoTIFF
  • AMSR2 SWE
    • Data are available from February 2018

Near real-time (NRT) AMSR2 snow water equivalent data are available through LANCE 60 to 125 minutes after a satellite observation. 

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Model Data

ASO

NASA's Airborne Snow Observatory (ASO) mission collects data on snowmelt flowing out of major water basins in the Western U.S. The mission began in April 2013 as a collaboration between NASA's Jet Propulsion Laboratory (JPL) and the California Department of Water Resources, with weekly flights over the Tuolumne River Basin in California and monthly flights over the Uncompahgre River Basin in Colorado during the snowmelt season. Current data collection is undertaken by Airborne Snow Observatories, Inc., a private company working in partnership with Esri and the Weather Research and Forecasting Model Hydrological modeling system (WRF-Hydro) team of the National Center for Atmospheric Research.

Image
Image showing Airborne Snow Observatory (ASO) lidar coverage of the Kings River basins in central California, USA. This image was acquired during snow surveys of the Tuolumne, Kings, Merced, and Kaweah river basins undertaken April 17-21, 2019. Image: NASA Jet Propulsion Laboratory.
ASO lidar coverage of the Kings River basins in central California, USA. This image was acquired during snow surveys of the Tuolumne, Kings, Merced, and Kaweah river basins undertaken April 17-21, 2019. Credit: NASA's Jet Propulsion Laboratory.

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Daymet

Another NASA source for SWE data is Daymet, which can be accessed through NASA's ORNL DAAC. Daymet is a collection of gridded estimates of daily weather parameters including minimum and maximum temperature, precipitation, vapor pressure, radiation, snow water equivalent, and day length at 1 km resolution over the North America, Puerto Rico, and Hawaii from 1980 to present (North America and Hawaii) and from 1950 to present (Puerto Rico). 

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LDAS: NLDAS, GLDAS, FLDAS

NASA, in collaboration with other agencies, has developed models of snow cover and depth that incorporate satellite information with ground-based data (when ground-based data are available). These models are part of the Land Data Assimilation System (LDAS), which includes a global collection (GLDAS) and a North American collection (NLDAS). 

Snow depth data products are are available from Giovanni. These data can be visualized as a time-averaged map, an animation, seasonally-averaged maps, scatter plots, or a time series using an online interactive data analysis tool called Giovanni:

  • Snow Depth
    • NLDAS (North American), 0.125° from 1975 to current at monthly and hourly resolutions
    • GLDAS (Global), 0.25° and 1° from 1948 to 2022 at monthly, daily, and 3-hourly temporal resolutions
    • FLDAS, 0.1° and 0.01° from about 1982 - current in daily and monthly temporal resolutions
  • Snow Water Equivalent
    • NLDAS (North American), 0.125° from 1975 to present at monthly and hourly resolutions
    • GLDAS (Global), 0.25° and 1° from 1948 to 2022 at monthly, daily, and 3-hourly temporal resolutions

GLDAS model data are available from NASA's GES DISC:

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Reanalysis Data

MERRA-2

The Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) provides data beginning in 1980. Due to the amount of historical data available, MERRA-2 data can be used to look for trends and patterns, as well as anomalies. There are several options available: hourly and monthly from 1980.

MERRA -2 Snow data products can be visualized as a time-averaged map, an animation, seasonally-averaged maps, scatter plots, or a time series using a NASA interactive data analysis tool called Giovanni:

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Surface runoff is the volume of available surface water after a precipitation event that has been partitioned into evapotranspiration (ET) and stored as soil moisture. Droughts are indicated by lower surface runoff anomaly values showing that water reservoirs have received less than normal amounts of surface runoff, while elevated total runoff anomaly values may indicate flooding events. 

Common Runoff Data at a Glance

Relevant datasets are from sensors shown in the table below. This is not intended to be an exhaustive list of all sensors or missions producing data relevant to this Data Pathfinder. 

Spatial Resolution Spatial Coverage Temporal Resolution Temporal Coverage Spectral Resolution Satellite/
Platform
Sensor(s)/ Model Name Model or Reanalysis File Format
0.01°, 0.1°, 0.125°, 0.25°, 1° Global Hourly, 3-Hourly, Daily, Monthly 1948-Present N/A N/A LDAS Model netCDF
0.5° x 0.625° Global Hourly, Daily, Monthly 1980-Present N/A N/A MERRA-2 Reanalysis netCDF
0.25º Global Daily 1950-2100 N/A N/A NEX-GDDP-CMIP6 Model/Downscaled Model Outputs Cloud-Optimized GeoTIFF (COG)

Use the Runoff Data

GIS-Ready Tools and Tutorials
Data Access Tools
  • Data Rods Explorer (DRE) is a web client app that enables users to browse several NASA-hosted datasets
  • AppEEARS offers a simple and effective way to extract, transform, visualize, and download data products; output data can be downloaded in CSV (point), GeoTIFF (area), or NetCDF4 (area) formats
  • For more information on a suite of NASA data tools for searching and ordering, data handing, subsetting and filtering, geolocating, reprojecting, and mapping, as well as visualizing and analyzing data, visit the NASA Earthdata Data Tools Page
Programming Tools

Model Data

LDAS

Runoff potential is important data for water resources and agricultural management, especially after storm events and wildfires. Runoff can impact water quality as chemicals from fertilizers and stormwater runoff, debris, and waste products enter water bodies. Satellites cannot measure runoff directly; however, information that can be used to predict runoff can be measured remotely. These data are then input, along with ground-based data, into land surface models to estimate runoff. 

NASA's Land Data Assimilation System (LDAS), of which there is a global collection (GLDAS) and a North American collection (NLDAS), takes inputs of measurements like precipitation, soil texture, topography, and leaf area index and then uses those inputs to model output estimates of runoff and evapotranspiration:

Research quality LDAS Total Runoff data are available in Earthdata Search:

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Reanalysis Data

MERRA-2

Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) is the latest version of global atmospheric reanalysis for the satellite era produced by NASA Global Modeling and Assimilation Office (GMAO) using the Goddard Earth Observing System Model (GEOS) version. The dataset covers the period of 1980-present with the latency of approximately three weeks after the end of a month:

  • MERRA-2 Runoff Data in Giovanni
    • Data are in multiple temporal resolutions and multiple temporal coverages; be sure to note the starting and end date to ensure you access the desired dataset

Research quality MERRA-2 Total Runoff datasets are available in Earthdata Search:

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NEX-GDDP-CMIP6

The NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset is comprised of high-resolution, bias-corrected global downscaled climate projections derived from the General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 6 (CMIP6) and across all four “Tier 1” greenhouse gas emissions scenarios known as Shared Socioeconomic Pathways (SSPs). 

This dataset provides a set of global, high resolution, bias-corrected climate change projections that can be used to evaluate climate change impacts on processes that are sensitive to finer-scale climate gradients and the effects of local topography on climate conditions. Uses include: air temperature, precipitation volume, humidity, stellar radiation, and atmospheric wind speed.

NEX-GDDP-CMIP6 data are available through the NASA Center for Climate Simulation (NCCS):

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An understanding of topography is essential when assessing an area's runoff potential and vulnerability to potential flooding events, especially in lower-lying areas. These data are common tools for researchers, watershed managers, and other professionals for identifying floodplains, analyzing watersheds, developing elevation profiles, assessing flood risk potential, and building and testing hydraulic models. 

Common Topography/Elevation Data at a Glance

Relevant datasets are from sensors shown in the table below. This is not intended to be an exhaustive list of all sensors or missions producing data relevant to this Data Pathfinder. 

Spatial Resolution Spatial Coverage Temporal Resolution Temporal Coverage Spectral Resolution Satellite/
Platform
Sensor(s)/ Model Name Observation or Model File Format
U.S. = 30 m; Global = 60 m, 90 m, 1 km Global One-Time estimate 2000 N/A SRTM N/A Observation HGT, netCDF4
30 m Global Multi-Year 2000-2013 14 bands ranging from 0.52 µm to 11.65 µm Terra ASTER Observation HDF-EOS or GeoTIFF
25 m Diameter 51.6° N and 51.6° S One-Time Estimate 2019-2022 Laser wavelength: 1.064 µm International Space Station GEDI Observation and Model HDF5
Dependent on measurement: 20 m, 60 m, 280 m, 1 degree, 2 degrees, 25 km Global 91 days 2018-present 532 nm ICESat-2 ATLAS Observation HDF5
Use Cases and Articles
Tutorials
GIS-Ready Tools and Tutorials
Data Access Tools
  • EarthExplorer connects users with USGS satellite, aircraft, and other remote sensing inventories through interactive and textual-based query capabilities
  • ICESat-2 Data Access Tool: Filter files before downloading based on date, spatial area, or file name. Choose from various download options, such as Python script. Export bounding boxes as a GeoJSON.
  • Sentinel Hub EO Browser provides a complete archive of Sentinel-1, Sentinel-2, Sentinel-3, Sentinel-5P, ESA’s archive of Landsat 5, 7 and 8, global coverage of Landsat 8, Envisat Meris, MODIS, Proba-V and GIBS products in one place
Data Customizing Tools
Programming Tools

Earth Observation Data by Sensor

SRTM

A digital elevation model (DEM) created from Shuttle Radar Topography Mission (SRTM) data provides detailed topography for all land between 60° north and 56° south latitude, which encompasses about 80% of Earth's landmass. 

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ASTER

The Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Digital Elevation Model provides a global DEM of land areas on Earth at a spatial resolution of 1 arc second (approximately 30 meter horizontal posting at the equator).

DEM data accuracy is typically very sensitive to vegetation cover; however, data from the ASTER instrument tend to perform better over specific landcover types. Applications include identifying crop stress, mapping surface temperatures of soils and geology, and measuring surface heat balance.

The NASADEM data product was released in February 2020 and provides 1 arc-second resolution. NASADEM extends the legacy of the SRTM by improving the DEM height accuracy and data coverage as well as providing additional SRTM radar-related data products.

Imagery can be interactively explored using NASA Worldview:

Research quality topography data products are available from Earthdata Search:

  • SRTM
    • These data were acquired in 2000 and are in raw format (with the ".hgt" file extension), and can be opened in most Geographic Information Systems (GIS), such as ArcGIS or QGIS; data are also customizable to GeoTIFF
  • ASTER Digital Elevation Model V003
  • NASADEM

In addition to Earthdata Search, SRTM and ASTER data can be accessed through AppEEARS.

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GEDI

The Global Ecosystem Dynamics Investigation (GEDI) Level 3 Land Surface Metrics dataset provides gridded mean canopy height, standard deviation of canopy height, mean ground elevation, standard deviation of ground elevation, and counts of laser footprints per 1 km x 1 km grid cells within 52° north and south latitude. Data are available from April 2019 through 2022. Level 3 gridded products can be used to create digital elevation models, characterize important carbon and water cycling processes, and more. 

Users may download customized subsets (Level 3 and Level 4) of GEDI data using the Spatial Data Access Tool through the at The Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC).

GEDI L3 Gridded Land Surface Metrics data can be visualized and interactively explored using NASA Worldview:

Research quality data can be accessed using Earthdata Search:

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ATLAS

The Advanced Topographic Laser Altimeter System (ATLAS) is a laser altimeter aboard NASA's Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2). The instrument has three primary tasks: Send pulses of laser light to the ground, collect the returning packets of electromagnetic radiation (called photons), and record the photon travel time. The instrument measures height about every 2.3 feet along the satellite’s path and can measure surface height to a precision of approximately one inch (about the length of a standard paperclip). While the primary intent of ATLAS is to measure cryospheric elevation, the instrument is able to measure elevation in temperate regions, including measurements of forest cover and vegetation, and is even able to detect water features such as coral reefs and ocean waves.

Research-quality ATLAS/ICESat-2 L3A Land and Vegetation Height, Version 6 provides terrain elevation data.  

  • This data set (ATL08) contains along-track heights above the WGS84 ellipsoid (ITRF2014 reference frame) for the ground and canopy surfaces. The canopy and ground surfaces are processed in fixed 100 m data segments, which typically contain more than 100 signal photons. The data were acquired by the Advanced Topographic Laser Altimeter System (ATLAS) instrument on board the Ice, Cloud and land Elevation Satellite-2 (ICESat-2) observatory.

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Flood events can have drastic economic and social losses to communities. NASA measurements can be used to map flood inundation and to understand vulnerability and exposure of communities to aid with disaster relief efforts.

Aboveground biomass density (AGBD) includes living and dead plant mass per unit area located above Earth's surface. Incorporating and maintaining healthy vegetation in flood-prone areas and considering aboveground biomass in land use planning can help reduce the impact of flooding events. These benefits may include but not limited to reducing surface runoff, promoting infiltration, stabilizing soil, and regulating water flow. 

Common Aboveground Biomass Data at a Glance

Relevant datasets are from sensors shown in the table below. This is not intended to be an exhaustive list of all sensors or missions producing data relevant to this Data Pathfinder. 

Spatial Resolution Spatial Coverage Temporal Resolution Temporal Coverage Spectral Resolution Satellite/ Platform Sensor(s)/ Model Name Observation or Model File Format
25 m diameter, 1 km grid 52° N to 52° S latitude One-time estimate 2019-2022 Laser wavelength: 1.064 µm International Space Station GEDI Observation and Model GeoTIFF

Use the Aboveground Biomass Density Data

Use Cases and Articles
Tutorials
Data Visualization
GIS-Ready Tools and Tutorials
Data Access Tools
Data Customizing Tools
  • AppEEARS allows users to subset data by defining specific point(s) or area(s) of interest; output data can be downloaded in CSV (point), GeoTIFF (area), or NetCDF4 (area) formats
  • MODIS/VIIRS Subsetting Tools Suite
    • Global Subset Tool: Request a subset for any location as a GeoTiff and in text format, including interactive time-series plots
    • Fixed Sites Subsets Tool: Download pre-processed subsets for more than 3,000 field and flux tower sites for validation of models and remote sensing products
    • Web Service: Retrieve subset data (in real-time) for any location, time period, and area programmatically using a REST web service. Web service clients and libraries are available in multiple programming languages, allowing integration of subsets into a workflow
  • ORNL DAAC Subsetting Tools
  • For more information on a suite of NASA data tools for searching and ordering, data handling, subsetting and filtering, geolocating, reprojecting, and mapping, as well as visualizing and analyzing data, visit the NASA Earthdata Data Tools Page
Programming Tools

Earth Observation Data by Sensor

GEDI

The Global Ecosystem Dynamics Investigation (GEDI) is a joint mission between NASA and the University of Maryland, with the instrument installed on the International Space Station. Data acquired using the instrument’s three lasers are used to construct detailed 3D maps of forest canopy height and the distribution of branches and leaves. GEDI data play an important role in understanding the amounts of biomass and carbon forests store and how much they lose when disturbed. GEDI data also can be used to study plant and animal habitats and biodiversity along with how these change over time. 

Research quality Level 3 data can be accessed using Earthdata Search:

Model Data

GEDI

GEDI Level 4B data provide gridded 1km x 1km estimates of mean aboveground biomass density (AGBD). This dataset provides gridded estimates of aboveground biomass density at a greater accuracy and resolution than previously available.

Model GEDI AGBD data can be accessed using Earthdata Search:

Land cover plays an important role in influencing flooding events and their impacts. To effectively manage and mitigate these events, it is important to consider how changes in land cover impact local hydrology and incorporate these considerations into land use planning, urban design, and water management strategies. 

Common Land Cover Data at a Glance

Relevant datasets are from sensors shown in the table below. This is not intended to be an exhaustive list of all sensors or missions producing data relevant to this Data Pathfinder. 

Spatial Resolution Spatial Coverage Temporal Resolution Temporal Coverage Spectral Resolution Satellite/
Platform
Sensor(s)/ Model Name Observation or Model File Format
500 m Global 1-2 Days

2001-2021

36 bands ranging from 0.4 µm to 14.4 µm Terra and Aqua MODIS Observation HDF-EOS
30 m Global Yearly 2001-2019 Varies Derived from Landsat data GLanCE Observation GeoTIFF
30 m U.S. only Yearly 2001-2019 Varies Derived from Landsat data NLCD Observation GeoTIFF

Use the Land Cover Data

Use Cases and Articles
Tutorials
Data Visualizations
GIS-Ready Tools and Tutorials
Data Access Tools
Data Customizing Tools
  • AppEEARS allows users to subset data by defining specific point(s) or area(s) of interest. Output data can be downloaded in CSV (point), GeoTIFF (area), or NetCDF4 (area) formats
  • MODIS/VIIRS Subsetting Tools Suite
    • Global Subset Tool: Request a subset for any location as a GeoTiff and in text format, including interactive time-series plots
    • Fixed Sites Subsets Tool: Download pre-processed subsets for more than 3,000 field and flux tower sites for validation of models and remote sensing products
    • Web Service: Retrieve subset data (in real-time) for any location, time period, and area programmatically using a REST web service; web service clients and libraries are available in multiple programming languages, allowing integration of subsets into a workflow
  • For more information on a suite of NASA data tools for searching and ordering, data handling, subsetting and filtering, geolocating, reprojecting, and mapping, as well as visualizing and analyzing data, visit the NASA Earthdata Data Tools Page
Programming Tools

Earth Observation Data by Sensor

MODIS

The Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua Land Cover Type data product (MCD12Q1) provides global land cover types at yearly intervals. This product is derived using supervised classifications of MODIS surface reflectance data. The supervised classifications then undergo additional post-processing that incorporates prior knowledge and ancillary information to further refine specific land type classes.

These data can be accessed and downloaded several ways:

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GLanCE

NASA’s Making Earth System Data Records for Use in Research Environments (MEaSUREs) Global Land Cover Mapping and Estimation (GLanCE) annual 30m Version 1 data product provides global land cover and land cover change data derived from Landsat TM, ETM+, and OLI data. These maps provide the user community with land cover type, land cover change, metrics characterizing the magnitude and seasonality of greenness of each pixel, and the magnitude of change. This dataset is useful for a wide range of applications, including ecosystem, climate, and hydrologic modeling; monitoring the response of terrestrial ecosystems to climate change; carbon accounting; and land management. 

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NLCD

The National Land Cover Database (NLCD) is a comprehensive land cover database that utilizes 30-meter resolution Landsat satellite imagery. It covers eight different time periods, or epochs, spanning from 2001 to 2019. This product was created out of the Multi-Resolution Land Characteristics (MRLC) project to provide multi-resolution land cover data of the conterminous United States from local to regional scales. A major component of MRLC is an objective to develop a national 30-meter land cover characteristics data base using Landsat thematic mapper (TM) data. This is a cooperative effort among six programs within four U.S. Government agencies, including the U.S. Environmental Protection Agency's (EPA) Environmental Monitoring and Assessment Program; the U.S. Geological Survey's (USGS) National Water Quality Assessment Program; the National Biological Service's Gap Analysis Program; the USGS' Earth Resources Observation Systems (EROS) Center; the National Oceanic and Atmospheric Administration's Coastal Change Analysis Program; and the EPA's North American Landscape Characterization project.

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Leaf Area Index (LAI) is the ratio of leaf surface area to ground surface area. Understanding the role of LAI in land use planning and water management strategies helps managers maintain areas with dense, healthy vegetation with the goal of reducing the risk of flooding in various environments by reducing runoff, boosting soil infiltration, stabilizing soil, and balancing the hydrologic cycle. 

Common Leaf Area Index Data at a Glance

Relevant datasets are from sensors shown in the table below. This is not intended to be an exhaustive list of all sensors or missions producing data relevant to this Data Pathfinder. 

Spatial Resolution Spatial Coverage Temporal Resolution Temporal Coverage Spectral Resolution Satellite/ Platform Sensor(s)/ Model Name Observation or Reanalysis File Format
275 m at all off-nadir angles Global Monthly, seasonal 2007-Present 0.446 µm to 0.867 µm Terra MISR Observation netCDF4
500 m Global 1-2 Days 2000-Present 36 bands ranging from 0.4 µm to 14.4 µm Terra and Aqua MODIS Observation HDF-EOS
500 m Global 1-2 Days 2012-Present 22 bands ranging from 0.41 µm to 12.01 μm Suomi NPP VIIRS Observation HDF-EOS5
0.5° x 0.625° Global Monthly 1980-Present N/A N/A MERRA-2 Reanalysis netCDF

Use the Leaf Area Index Data

Use Cases and Articles
Tutorials
GIS-Ready Tools and Tutorials
Data Access Tools
Data Customizing Tools
  • AppEEARS allows users to subset data by defining specific point(s) or area(s) of interest; output data can be downloaded in CSV (point), GeoTIFF (area), or NetCDF4 (area) formats
  • MODIS/VIIRS Subsetting Tools Suite
    • Global Subset Tool: Request a subset for any location as a GeoTiff and in text format, including interactive time-series plots
    • Fixed Sites Subsets Tool: Download pre-processed subsets for more than 3,000 field and flux tower sites for validation of models and remote sensing products
    • Web Service: Retrieve subset data (in real-time) for any location, time period, and area programmatically using a REST web service. Web service clients and libraries are available in multiple programming languages, allowing integration of subsets into a workflow
  • For more information on a suite of NASA data tools for searching and ordering, data handing, subsetting and filtering, geolocating, reprojecting, and mapping, as well as visualizing and analyzing data, visit the NASA Earthdata Data Tools Page
Programming Tools

Earth Observation Data by Sensor

MISR

The Multi-angle Imaging SpectroRadiometer (MISR) Level 3 FIRSTLOOK Global Land product in netCDF format features LAI. This data product is a global summary of the Level 2 land/surface parameters of interest averaged over a month and reported on a geographic grid.

Global MISR LAI data are available to browse, visualize, and download through the MISR Level 3 Data Browser.

Research quality data are available through Earthdata Search:

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Model Data

MODIS

MODIS LAI data can be visualized and interactively explored using NASA Worldview:

MODIS LAI Level 4 data are available starting in 2000 through Earthdata Search:

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VIIRS

VIIRS LAI Level 4 data are available starting in 2012 through Earthdata Search:

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Reanalysis Data

MERRA-2

LAI data products can be visualized as a time-averaged map, an animation, seasonal maps, scatter plots, or a time series through Giovanni:

MERRA-2 data are available for download in Earthdata Search:

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Satellite observations and model data enable managers and emergency responders to rapidly assess flooding across large areas.

Common Flood & Surface Water Data at a Glance

Relevant datasets are from sensors shown in the table below. This is not intended to be an exhaustive list of all sensors or missions producing data relevant to this Data Pathfinder. An asterisk (*) by an entry indicates that near real-time (NRT) data products are available through NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE). LANCE data products are available within three hours of a satellite observation. If low-latency is not a primary concern, users are encouraged to use standard science products, which are produced using the best available calibration, ancillary, and ephemeris information. To learn more about the difference between NRT and Standard Science Products, see Near Real Time versus Standard Products.

Spatial Resolution Spatial Coverage Temporal Resolution Temporal Coverage Spectral Resolution Satellite/ Platform Sensor(s)/ Model Name Observation or Model File Format
250 m Near Global 1, 2, 3 Days 2021-Present 36 spectral bands ranging in wavelength from 0.4 µm to 14.4 µm Terra/Aqua *MODIS Observation HDF, GeoTIFF
0.01°, 0.1°, 0.125°, 0.25°, 1° Global Hourly, 3-Hourly, Daily, Monthly 1948-Present N/A N/A LDAS Model netCDF
30 m Near Global Daily, Weekly 2023 0.43-1.6, 2.1-2.3 µm; 13 bands: 442.3 nm - 2202.4 nm LANDSAT-8;
Sentinel-2A / Sentinel-2; 
Sentinel-2B / Sentinel-2
*OPERA
(OLI, MSI)
Observation Cloud Optimized GeoTIFF
Varies Global 91 Day 2023- Present 532 nm ICESat-2 ATLAS Observation HDF5
Varies Global 12 days (Global); Global coverage of 6 days over the equator when using data from both satellites 2014-Present 5.405 GHz Sentinel-1A & B C-SAR Observation GeoTIFF, netCDF

Use the Flood & Surface Water Data

Use Cases and Articles
Tutorials
Data Visualization
  • DisasterAWARE: This All-hazard Warnings, Analysis, and Risk Evaluation) is an online platform that offers a single source of global information on floods (and other disasters).  This all-hazard warning and decision support tool assists disaster managers and those who provide assistance during times of humanitarian unrest. This tool provides early warnings and supplemental analytical assets in advance of the disaster to help evaluate potential impacts.  Users must request access and create a log-in.
  • DFO Flood Observatory: This tool provides near real-time, current, and past flood event mapping based on MODIS reflectance–same as MODIS NRT, as well as Landsat 8, EO-1, and ASTER images–uses COSMO-SkyMed and Sentinel-1 synthetic aperture radar (SAR) (when available). This resource provides analysis on current flood events multiple data sources, including media reports
  • Global Disaster Alert and Coordination System (GDACS): Provides Up-to-date and accessible information is essential to providing an effective, coordinated response to disasters, such as floods, earthquakes, and tropical storms
  • HYDrologic Remote Sensing Analysis for Floods (HYDRAFloods): The publicly available, web-based service delivers near real-time information for improved flood monitoring. It is designed to provide information on flood location and extent to assist with flood preparedness, emergency response and relief efforts
  • Global Flood Monitoring System (GFMS): Provides global maps, time series, and animations (50°S-50°N) of:–instantaneous rain rate every 3 hrs–accumulated rain over 24, 72, and 168 hrs–streamflow rates and flood intensity at one-eighth degree (~12 km) and 1 km
  • Advanced Rapid Imaging and Analysis (ARIA): The ARIA Project, a joint effort of the California Institute of Technology and NASA's Jet Propulsion Laboratory, is developing the infrastructure to generate imaging products in near real-time that can improve situational awareness for disaster response. This tool is focused primarily on ground deformation change measurements, also includes flood damage proxy maps. Products are in folders based on the date of the event and the location. Data products that have been generated for event response are made available on the ARIA Share site, which does not require a login
  • GeoGateway
  • SARViews
  • Panoply Data Viewer: Visualize georeferenced arrays in NetCDF, HDF and GRIB formats
  • Federal Emergency Management Agency (FEMA) Resources:
    • Flood Risk Maps (U.S. Only)
      • FEMA provides flood maps to communities to set minimum floodplain standards
GIS-Ready Tools and Tutorials
Data Access Tools
Data Customizing Tools
Programming Tools

Earth Observation Data by Sensor

MODIS

The Moderate Resolution Imaging Spectroradiometer (MODIS) instrument provides observations 1-2 times per day using specific spectral bands to indicate water on previously dry surfaces (i.e., Band 1: 620-670 nm; Band 2: 841-876 nm; Band 7: 2105-2155 nm). Flood assessments based on remote sensing requires a variety of observations and models. MODIS is an optical sensor and cannot sense flooded surfaces in the presence of clouds; for this reason Synthetic Aperture Radar (SAR), a microwave sensor, is a useful complement to optical sensors. However, SAR data have limited temporal coverage. 

Interactively explore MODIS NRT Global Flood Products in NASA Worldview:

  • MODIS Near Real-Time (NRT) Global Flood Product (2 Day Window)
  • MODIS Near Real-Time (NRT) Global Flood Product (3 Day Window)

Flood Dashboard:The Flood Dashboard brings together multiple NASA soil moisture and flood products with products from the National Weather Service and USGS to give a more complete picture of potential flooding in the United States. 

  • MODIS Flood Maps: Zoom in on the MODIS 1 day, 2 day, or 3 day flood maps to see where potential flood water (shown in red) has been detected. The 1 day product shows flooding detected in the last day, 2 day shows the last 2 days, and 3 day in the last 3 days. Cloudy conditions may hide flooding from the MODIS sensor so the 2 and 3 day products are typically less impacted by clouds
  • Soil Moisture Map: The soil moisture map shows soil that is likely very saturated (dark green and blue) and may be more susceptible to flooding
  • USGS Stream Gauges: The orange, red, and purple stream gauges show areas likely experiencing flooding as detected by the USGS. The yellow gauges marked action stage are considered near flood

MODIS Flood Detection GIS maps from NASA Disasters Program: 

MODIS Flood Inundation Maps: Based on MODIS reflectance at 250 m resolution composited on 2, 3, and 14 days, these maps are available on 10°x10° tiles. Imagery features near real-time permanent and surface flood imagery since Jan 2013. Note: Cloud or terrain shadows can be misinterpreted as surface water. 

MODIS Flood data products are used in the DisasterAWARE online platform to determine flood severity in near real-time based on potential inundation. This all-hazard warning and decision support tool assists disaster managers and those who provide assistance during times of humanitarian unrest. DisasterAWARE provides early warnings and supplemental analytical assets in advance of the disaster to help evaluate potential impacts. Users must request access and create a log-in.

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OPERA

Dynamic Surface Water Extent from Harmonized Landsat Sentinel-2 provisional product (Version 1) is part of the Observational Products for End-Users from Remote Sensing Analysis (OPERA) DSWX product suite that has a near global scope (Land masses excluding Antarctica) and is comprised of four individual products derived from Optical and SAR sensors. HLS products provide surface reflectance (SR) data from the Operational Land Imager (OLI) aboard the Landsat 8 satellite and the MultiSpectral Instrument (MSI) aboard the Sentinel-2A/B satellite. 

Interactively explore OPERA Dynamic Surface Water Extent Provisional in NASA Worldview:

  • OPERA Dynamic Surface Water Extent Provisional: The OPERA Dynamic Surface Water Extent Provisional imagery layer is a Level 3 product that maps surface water every few days. The resolution is 30 m and the layer has five classifications: Not Water, Open Water, Partial Surface Water, Snow/Ice, and Cloud/Cloud Shadow. The input dataset for generating each product is the Harmonized Landsat Sentinel-2 (HLS) dataset

Access Research-level OPERA Dynamic Surface Water Extent in NASA Earthdata Search:

  • OPERA Dynamic Surface Water Extent
    • The data are provisional surface water extent observations beginning April 2023. Each product is distributed as a set of 10 GeoTIFF (Geographic Tagged Image File Format) files including water classification, associated confidence, land cover classification, terrain shadow layer, cloud/cloud-shadow classification, Digital elevation model (DEM), and Diagnostic layer

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ATLAS

The ATL13 data product contains along-track surface water products for inland water bodies. Inland water bodies include lakes, reservoirs, rivers, bays, estuaries and a 7 km near-shore buffer. Principal data products include the along-track water surface height and standard deviation, subsurface signal (532 nm) attenuation, significant wave height, wind speed, and coarse depth to bottom topography (where data permit).

Research-quality ATLAS Surface Water Quick Look data are available from Earthdata Search:

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SAR

Understanding and mapping flood inundation is critical to assessing the scope of the disaster, where the damage is greatest, and where to respond with relief efforts. During a storm, Synthetic Aperture Radar (SAR) may provide a better "view" of the ground than optical sensors. SAR is a type of active data technology where a sensor produces its own energy and then records the amount of that energy reflected back. SAR imagery can be used to assess post-storm flood and storm-surge damage along with shoreline changes.

Sentinel-1 A and B:

The Sentinels are a fleet of European Space Agency (ESA) satellites designed to acquire measurements from multiple sensor types that will provide information necessary to meet Europe’s Copernicus program objectives. The first mission in the series, the Sentinel-1 constellation, includes twin satellites that each carry C-band synthetic aperture radar (SAR) which together provide all-weather, day-and-night imagery of Earth’s surface. The Sentinel-1 constellation benefits numerous services, such as monitoring of Arctic sea-ice extent, routine sea-ice mapping, and surveillance of the marine environment. Applications include oil-spill monitoring and ship detection for maritime security; monitoring land-surface for motion risks; mapping for forest, water, and soil management; and mapping to support humanitarian aid and crisis situations.

Sentinel-1A was launched on 3 April 2014, and Sentinel-1B on 25 April 2016. They orbit 180° apart, together imaging the Earth every six days. In December 2021, an anomaly in the power supply of Sentinel-1B caused the SAR sensor to stop working. Attempts to restore power to the sensor failed, and the mission officially ended on August 3, 2022. The loss of one of the Sentinel-1 satellites means that the frequency of observations and global coverage will be significantly reduced until the launch and commissioning of Sentinel-1C. This is predicted to be completed in the third quarter of 2023. Sentinel-1B will be deorbited at this time.

Research-quality Sentinel-1 SAR data are available from Earthdata Search:

SAR data from Sentinel-1 are integrated in the DisasterAWARE online platform to evaluate potential impacts of flood events. Additionally, these data help to map post-event floods, estimate flood depth, and flood severity.  This all-hazard warning and decision support tool assists disaster managers and those who provide assistance during times of humanitarian unrest. DisasterAWARE provides early warnings and supplemental analytical assets in advance of the disaster to help evaluate potential impacts.  Users must request access and create a log-in.

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Model Data

LDAS

A class of global or regional (much larger than watershed-level) models are available based on land surface processes and water balance approach. These models utilize weather information for forcing and calculate runoff at model grid points. Runoff can then be used with a routing model, like NASA's Land Information System and the HyMAP Routing Model, to diagnose stream flow in river channels.

NASA's Land Data Assimilation System (LDAS), of which there is a global collection (GLDAS) and a North American collection (NLDAS), takes inputs of measurements like precipitation, soil texture, topography, and leaf area index and then uses those inputs to model output estimates of runoff:

Research quality LDAS Total Runoff data are available in Earthdata Search:

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Surface reflectance is a measure of the fraction of incoming solar radiation reflected from Earth's surface to a satellite-borne or aircraft-borne sensor. Monitoring surface reflectance enables users to detect flood-affected regions, map flood extent, compare areas affected before and after flood events, as well as coordinate emergency response activities.

Common Surface Reflectance Data at a Glance

Relevant datasets are from sensors shown in the table below. This is not intended to be an exhaustive list of all sensors or missions producing data relevant to this Data Pathfinder. An asterisk (*) by an entry indicates that near real-time (NRT) data products are available through NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE). LANCE data products are available within three hours of a satellite observation. If low-latency is not a primary concern, users are encouraged to use standard science products, which are produced using the best available calibration, ancillary, and ephemeris information. To learn more about the difference between NRT and Standard Science Products, see Near Real Time versus Standard Products.

Spatial Resolution Spatial Coverage Temporal Resolution Temporal Coverage Spectral Resolution Satellite/ Platform Sensor(s)/ Model Name Observation or Model File Format
15 m, 30 m Global Variable 2000-Present 14 bands ranging from 0.52 µm to 11.65 µm Terra ASTER Observation HDF-EOS or GeoTIFF
500 m, 1 km, 0.05° Global 1-2 Days 2000-Present 36 bands ranging from 0.4 µm to 14.4 µm Terra and Aqua *MODIS Observation HDF, HDF-EOS2

500 m, 1 km, 5,600 m

Global 1-2 Days 2017-Present 22 bands ranging from 0.41 µm to 12.01 μm Suomi NPP *VIIRS Observation HDF5, HDF-EOS5
15 m, 30 m, 60 m Global 16 Days 1982-Present OLI/OLI-2: 9 bands ranging from 0.43 µm to 1.38 µm
ETM+: 8 bands ranging from 0.45 µm to 12.5 µm
TM: 7 bands ranging in wavelength from 0.45 µm to 2.35 µm
Landsat 4, 5, 7, 8, 9 OLI, OLI-2, ETM+, TM Observation GeoTIFF
30 m Near-Global (no Antarctic) 2-3 Days 2013-Present OLI/OLI-2: 9 bands ranging from 0.43 µm to 1.38 µm
MSI: 12 bands ranging from 0.443 µm to 2.190 µm
HLS

OLI, OLI-2, MSI

Observation Cloud Optimized GeoTIFF (COG)

Use the Surface Reflectance Data

Use Cases and Articles
Tutorials
Data Visualizations
GIS-Ready Tools and Tutorials
Data Access Tools
Data Customizing Tools
  • AppEEARS allows users to subset data by defining specific point(s) or area(s) of interest; output data can be downloaded in CSV (point), GeoTIFF (area), or NetCDF4 (area) formats
  • MODIS/VIIRS Subsetting Tools Suite
    • Global Subset Tool: Request a subset for any location as a GeoTiff and in text format, including interactive time-series plots
    • Fixed Sites Subsets Tool: Download pre-processed subsets for more than 3,000 field and flux tower sites for validation of models and remote sensing products
    • Web Service: Retrieve subset data (in real-time) for any location, time period, and area programmatically using a REST web service
Programming Tools

Earth Observation Data by Sensor

Landsat: ETM+, OLI, OLI-2, TIRS-2

The Enhanced Thematic Mapper (ETM+) and the Operational Land Imager (OLI) aboard the NASA/USGS Landsat 7 (ETM+) spacecraft and Landsat 8 (OLI) spacecraft acquire VNIR data at 30 m spatial resolution every 16 days (fewer days as you move away from the equator). Landsat 9 carries two instruments: the OLI-2 (which is a copy of the Landsat 8 OLI) and the Thermal Infrared Sensor-2 (TIRS-2). TIRS-2 measures land surface temperature in two thermal infrared bands.

Research quality surface reflectance data products can be accessed using USGS EarthExplorer:

  • Landsat 7 ETM+
  • Landsat 8 OLI
  • Landsat 9 OLI-2

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MODIS

Moderate Resolution Imaging Spectroradiometer (MODIS) Surface Reflectance products provide an estimate of the surface spectral reflectance as it would be measured at ground level in the absence of atmospheric scattering or absorption.

MODIS Surface Reflectance data can be visualized and interactively explored using NASA Worldview:

Multiple Geographic Information Systems (GIS) MODIS Surface Reflectance data layers with different band combinations are available through Esri’s ArcGIS OnLine (AGOL). NASA’s GIS data may be used with open source GIS software such as Quantum GIS or Geographic Resources Analysis Support System (GRASS) GIS at no cost:

Research quality MODIS data products can be accessed directly from Earthdata Search

  • MODIS Surface Reflectance
    • Note that a false-color image created by combining bands 7 as red, 2 as green, and 1 as blue is useful for enhancing flood conditions. In a false-color image made with this band combination, liquid water on the ground appears very dark since it absorbs in the red and the shortwave-infrared ranges. To only choose those bands, see the customization option within Earthdata Search in the Tools for Data Access and Visualization section

Near real-time (NRT) MODIS Surface Reflectance data are available through NASA’s Land, Atmosphere Near real-time Capability for EOS (LANCE) within 60 to 125 minutes after a satellite observation:

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HLS

A high-resolution land surface reflectance imagery option is Harmonized Landsat and Sentinel-2 (HLS). HLS imagery provide consistent surface reflectance and top of atmosphere brightness data from the Landsat 8 OLI, the Landsat 9 OLI-2, and the Multi-Spectral Instrument (MSI) aboard the ESA (European Space Agency) Sentinel-2A and Sentinel-2B satellites. The harmonized measurement enables global land observations every 2-3 days at 30 m spatial resolution.

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ASTER

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument acquires visible and near-infrared (VNIR) reflectance data at 15 m spatial resolution and short wave infrared (SWIR) reflectance data at 30m spatial resolution. 

ASTER data can be accessed and downloaded using NASA Worldview:

ASTER is a cooperative effort between NASA and Japan's Ministry of Economy Trade and Industry (METI). As a tasked sensor, ASTER acquires data when it is directed to do so over specific targets. This makes its temporal resolution variable depending on the requested target region of interest:

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VIIRS

The Visible Infrared Imaging Radiometer Suite (VIIRS) instrument is aboard the NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) and NOAA-20 satellites. 

VIIRS Surface Reflectance data can be visualized and interactively explored using NASA Worldview:

  • Suomi NPP VIIRS Corrected Reflectance
    Note that a false-color image created by combining bands M11 as red, I2 as green, and I1 as blue, or M3-I3-M11, is useful for enhancing flood conditions. In a false-color image made with this band combination, liquid water on the ground appears very dark since it absorbs in the red and the shortwave-infrared ranges
  • NOAA-20 VIIRS Corrected Reflectance
    Note that a false-color image created by combining bands M11 as red, I2 as green, and I1 as blue is useful for enhancing flood conditions. In a false-color image made with this band combination, liquid water on the ground appears very dark since it absorbs in the red and the shortwave-infrared ranges

Research quality VIIRS data products can be accessed directly from Earthdata Search:

Near real-time (NRT) VIIRS Surface Reflectance data are available through LANCE within 60 to 125 minutes after a satellite observation:

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Image
Floodwaters in south west Queensland, Australia due to rains from ex-tropical Cyclone Esther on 7 March 2020 (MODIS/Terra)
Rains from ex-tropical Cyclone Esther bring floodwaters to South West Queensland, Australia, March 2020.

NASA has several products that can be used to assess flooding qualitatively: Landsat, MODIS, and VIIRS. However, these sensors are impeded by cloud cover and nighttime conditions. During a storm, this is a significant drawback. Once the storm has passed, with a pre-event image and a post-event image, a more quantitative assessment of flooding extent can be made.

Research-quality (higher-level "standard") data products can be accessed via Earthdata Search or through NASA partner websites:

  • MODIS Surface Reflectance from Earthdata Search
    Note that a false-color image created by combining bands 7 as red, 2 as green, and 1 as blue is useful for enhancing flood conditions. In a false-color image made with this band combination, liquid water on the ground appears very dark since it absorbs in the red and the shortwave-infrared ranges. To only choose those bands, see the customization option within Earthdata Search in the Tools for Data Access and Visualization section.
  • Suomi NPP VIIRS Surface Reflectance from Earthdata Search
    Note that a false-color image created by combining bands M11 as red, I2 as green, and I1 as blue is useful for enhancing flood conditions. In a false-color image made with this band combination, liquid water on the ground appears very dark since it absorbs in the red and the shortwave-infrared ranges. To only choose those bands, see the customization option within Earthdata Search in the Tools for Data Access and Visualization section.
  • Suomi NPP VIIRS Corrected Reflectance in Worldview
    Note that a false-color image created by combining bands M11 as red, I2 as green, and I1 as blue, or M3-I3-M11, is useful for enhancing flood conditions. In a false-color image made with this band combination, liquid water on the ground appears very dark since it absorbs in the red and the shortwave-infrared ranges.
  • NOAA-20 VIIRS Corrected Reflectance in Worldview
    Note that a false-color image created by combining bands M11 as red, I2 as green, and I1 as blue is useful for enhancing flood conditions. In a false-color image made with this band combination, liquid water on the ground appears very dark since it absorbs in the red and the shortwave-infrared ranges.
  • Landsat Data from USGS Earth Explorer
    Landsat is a joint NASA/USGS program that provides the longest continuous space-based record of Earth's land in existence. On the Earth Explorer site specify your search criteria, then:
    1. Select "Data Sets"
    2. Select Landsat
    3. Select Landsat Collection 1 Level-1
    4. Select Landsat 7 and/or Landsat 8
    These files can be downloaded as Level-1 GeoTIFF Data Products. Note that you will need a USGS login to proceed.

 

Vegetation indices can be used to measure the amount of green vegetation over a given area, which is used as an assessment of vegetation health. These indices can play a role in assessing areas inundated by floods and used to map flood extent, severity, forecast early warning signs, and more. 

Commonly used vegetation indices are the Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), and EVI2. The NDVI takes the difference between near-infrared (NIR) and red reflectance divided by their sum: NDVI = (NIR - VIS)/(NIR + VIS). Resulting values range from -1 to 1. Low values of NDVI correspond to low photosynthetic activity (e.g., unhealthy vegetation) or non-vegetated surfaces, such as areas of rock, sand, exposed soils, or snow. Higher NDVI values generally indicate greener, more lush vegetation, including forests, croplands, and wetlands. The EVI minimizes canopy-soil variations and improves sensitivity over dense vegetation. The EVI2 minimizes atmospheric effects.

Common Vegetation Greenness Data at a Glance

Relevant datasets are from sensors shown in the table below. This is not intended to be an exhaustive list of all sensors or missions producing data relevant to this Data Pathfinder. An asterisk (*) by an entry indicates that near real-time (NRT) data products are available through NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE). LANCE data products are available within three hours of a satellite observation. If low-latency is not a primary concern, users are encouraged to use standard science products, which are produced using the best available calibration, ancillary, and ephemeris information. To learn more about the difference between NRT and Standard Science Products, see Near Real Time versus Standard Products.

Spatial Resolution Spatial Coverage Temporal Resolution Temporal Coverage Spectral Resolution Satellite/
Platform
Sensor(s)/ Model Name Observation or Reanalysis File Format
250 m, 500 m, 1 km Global 1-2 Days 2000-Present 36 bands ranging from 0.4 µm to 14.4 µm Terra and Aqua *MODIS Observation HDF-EOS
500 m, 1 km, 0.05° Global 1-2 Days 2012-Present 22 bands ranging from 0.41 µm to 12.01 μm Suomi NPP VIIRS Observation HDF-EOS5, HDF-EOS
0.5° x 0.625° Global Monthly 1980-Present N/A N/A MERRA-2 Reanalysis netCDF

Use the Vegetation Greenness Data

Use Cases and Articles
Tutorials
Data Visualizations
GIS-Ready Tools and Tutorials
Data Access Tools
Data Customizing Tools
  • AppEEARS allows users to subset data by defining specific point(s) or area(s) of interest; output data can be downloaded in CSV (point), GeoTIFF (area), or NetCDF4 (area) formats
  • MODIS/VIIRS Subsetting Tools Suite
    • Global Subset Tool: Request a subset for any location as a GeoTiff and in text format, including interactive time-series plots
    • Fixed Sites Subsets Tool: Download pre-processed subsets for more than 3,000 field and flux tower sites for validation of models and remote sensing products
    • Web Service: Retrieve subset data (in real-time) for any location, time period, and area programmatically using a REST web service; web service clients and libraries are available in multiple programming languages, allowing integration of subsets into a workflow
  • For more information on a suite of NASA data tools for searching and ordering, data handing, subsetting and filtering, geolocating, reprojecting, and mapping, as well as visualizing and analyzing data, visit the NASA Earthdata Data Tools Page
Programming Tools

Earth Observations by Sensor

MODIS and VIIRS

Vegetation products created from data acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument and the Visible Infrared Imaging Radiometer Suite (VIIRS) can be accessed in several ways. 

Imagery can be interactively explored using NASA Worldview:

Note: The Terra/MODIS NDVI (rolling 8-day) and EVI (rolling 8-day) are only available in Worldview for the last 20 days; older NDVI or EVI imagery are available using use the Level 3, 16-Day, or Monthly Vegetation Index and EVI layers.

NDVI data products can be visualized as a time-averaged map, an animation, seasonally-averaged maps, scatter plots, or a time series using a NASA online interactive data analysis tool called Giovanni:

  • MODIS NDVI
    • Select a map plot, date range, and region and plot the data; data can be downloaded as GeoTIFF

Multiple Geographic Information Systems (GIS) MODIS Surface Reflectance data layers with different band combinations are available through Esri’s ArcGIS OnLine (AGOL). NASA GIS data may be used with open-source GIS software such as Quantum GIS or Geographic Resources Analysis Support System (GRASS) GIS at no cost:

Research quality vegetation indices can be accessed directly using Earthdata Search (datasets are available as in HDF format but are, in some cases, customizable to GeoTIFF):

Near real-time (NRT) MODIS vegetation data can be accessed and downloaded through NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE):

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Reanalysis Data

MERRA-2

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When combined with flood-related data, socioeconomic data provide a picture of the impact to cities and areas with vulnerable populations.

NASA's Socioeconomic Data and Applications Center (SEDAC) is the home of socioeconomic data in NASA's Earth Observing System Data and Information System (EOSDIS) collection and is hosted at Columbia University’s Center for International Earth Science Information Network (CIESIN). SEDAC synthesizes Earth science and socioeconomic data and information in ways useful to a wide range of decision makers and other applied users, and serves as an “Information Gateway” between the socioeconomic and Earth science data and information domains.

Flood Hazard: Frequency and Distribution

SEDAC provides datasets that can be viewed and interactively explored using NASA Worldview: 

Research-quality socioeconomic data products can be accessed using Earthdata Search:

Flood Hazard: Mortality Risk

SEDAC provides datasets that can be viewed and interactively explored using NASA Worldview:

Research-quality socioeconomic data products can be accessed using Earthdata Search:

Flood-Related Economic Risk Loss

SEDAC provides datasets that can be viewed and interactively explored using NASA Worldview:

Research-quality socioeconomic data products can be accessed using Earthdata Search:

Nighttime Lights

The Visible Infrared Imaging Radiometer Suite (VIIRS) instruments aboard the joint NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) and NOAA-20 satellites provide global daily measurements of nocturnal visible and near-infrared (NIR) light that are suitable for Earth system science and applications studies. Learn more in the Nighttime Lights Backgrounder

Remote sensing of nighttime light emissions offers a unique perspective for investigations into flood impacts, as well as assessments of power outages or changes in nighttime light conditions across an area caused by flooding or other events.These data are being used for flooding applications in many ways: 

  • Detecting flooded ares
  • Monitoring Urban Flooding
  • Assessing impacts to infrastructure
  • Identifying populations who are displaced by flood events
  • Assessing post-flood areas and long term flood impacts

The VIIRS nighttime imagery layer shows Earth’s surface and atmosphere using a sensor designed to capture low-light emission sources under varying illumination conditions.

Research-quality nighttime lights products can be accessed using Earthdata Search:

NASA has also developed the Black Marble, a daily calibrated, corrected, and validated product suite to enable nightlight data to be used effectively for scientific observations. Black Marble's standard science processing removes cloud-contaminated pixels and corrects for atmospheric, terrain, vegetation, snow, lunar, and stray light effects on the VIIRS DNB radiances. Black Marble data can be accessed at NASA's Level-1 and Atmosphere Archive and Distribution System DAAC (LAADS DAAC). Black Marble imagery in Worldview is an image composite that was assembled from clear, cloud-free images acquired in 2012 and 2016. 

VIIRS Black Marble imagery can be viewed and interactively explored using NASA Worldview:

Download global Black Marble Grid Reference vector layer in Shapefile format.

Research-quality VIIRS Black Marble products can be accessed using Earthdata Search: 

Climate Change Impact
Environmental Performance
Impervious Surface

Research-quality socioeconomic data products can be accessed using Earthdata Search:

Population
Poverty

SEDAC Poverty-related Data:

NASA's Earth Observing Dashboard: Economy enables users to visualize and access the following datasets:

  • Builtup areas
  • Global Gridded Relative Deprivation
  • Global Gridded Relative Deprivation
  • Global Gridded Relative Deprivation
  • Global Gridded Relative Deprivation
  • Global Gridded Relative Deprivation Index
  • Global Gridded Relative Deprivation Index
  • Global Gridded Relative Deprivation Index
  • Global Gridded Relative Deprivation Index
  • Population density (META)
  • Population density (SEDAC)

External Data, Tools, and Resources

  • First Street Foundation:
    • Risk Factor
      • Flood Factor:
        • Flood Factor is a free online tool created by the nonprofit First Street Foundation that makes it easy for residents in the U.S. to find their property’s risk of flooding and understand how flood risks are changing because of a changing environment.
    • Flood Factor - First Street U.S. Climate Flood Risk Data - Aggregate: Flood Factor by First Street is a climate-adjusted flood risk model, offering risk scores at multiple geographic levels from states to census tracts. Data are available in CSV format and include projections of flood risk changes due to climate change between 2022 and 2052
    • RAPID NRT Flood Maps
  • Environmental Justice Screen: This Environmental Protection Agency (EPA) tool features Socioeconomic Indicators, Health Disparities, and more in the United States
  • Federal Emergency Management Agency (FEMA) Resources:
    • Resilience Analysis and Planning Tool (RAPT): Offers a GIS web map that displays census data, infrastructure locations, and hazards, including real-time meteorological forecasts, as well as U.S. disasters and hazard data 
    • Flood Risk Maps (U.S. Only)
      • FEMA provides flood maps to communities to set minimum floodplain standards
  • National Environmental Public Health Tracking: The Centers for Disease Control and Prevention (CDC) offers the following measures related to Flood Vulnerability:
    • Number of Square Miles Within FEMA Designated Flood Hazard Area
    • Percent Area (square miles) Within FEMA Designated Flood Hazard Area
    • Number of Square Miles Within EPA Designated Flood Hazard Area
    • Percent Area (square miles) Within EPA Designated Flood Hazard Area
    • Number of People Within FEMA Designated Special Flood Hazard Area
    • Number of Housing Units Within FEMA Special Designated Flood Hazard Area
  • World Bank Indicators
    • World Bank DataBank: Offers an analysis and visualization tool for exploring time series data on a variety of topics related to World Development
    • Not sure where to start? Explore the collections by visiting the Featured Indicators section to explore topics ranging from Agriculture and Rural Development to Health to Trade

Learn More

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