Floods Data Pathfinder - Find Data

Floods affect more people than any other type of natural disaster. This data pathfinder links to NASA datasets and tools that can aid with decisions regarding flood response and mitigation.
Image
Near real-time IMERG Early Run Half-Hourly Image, acquired on May 7, 2020. Credit: NASA.

NASA's Precipitation Measurement Mission (PMM) provides a continuous long-term record (over 20 years) of precipitation data through the Tropical Rainfall Measuring Mission (TRMM) and the Global Precipitation Measurement (GPM) missions. The follow-on mission, GPM, provides even more accurate measurements, improved detection of light rain and snow, and extended spatial coverage.

The products from GPM are available individually and have also been integrated with data from a global constellation of satellites to yield improved spatial/temporal precipitation estimates providing a temporal resolution of 30 minutes. The Integrated Multi-satellitE Retrievals for GPM (IMERG) mission contains multiple runs, which accommodate different user requirements for latency and accuracy (Early = 4 hours, e.g., for flooding events; Late = 12 hours, e.g., for crop forecasting; and Final = 3 months, with the incorporation of rain gauge data, for research).

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

  • IMERG from Earthdata Search
    Early, Late, and Final precipitation data on the half hour or 1-day timeframe. Data are in NetCDF or HDF format, and can be opened using Panoply. Data are available from 2000.

GIS analysis-ready datasets in GeoTIFF format can be accessed from the Precipitation Processing System website. Note that you will need to register to access the FTP site.

Data products can be visualized as a time-averaged map, an animation, seasonal maps, scatter plots, or a time series through an online interactive tool, Giovanni. Follow these steps to plot data in Giovanni: 1) Select a map plot type. 2) Select a date range. Data are in multiple temporal resolutions, so be sure to note the start and end date to ensure you access the desired dataset. 3) Check the box of the variable in the left column that you would like to include and then plot the data. For more information on choosing a type of plot, see the Giovanni User Manual.

Data can be visualized in Worldview:

Daymet is a collection of gridded estimates of daily weather parameters. It is modeled on daily meteorological observations. Weather parameters in Daymet include daily 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 can be retrieved in a variety of ways, including Earthdata Search, an Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC) API, and tools developed by ORNL DAAC, or through NASA's Land Processes DAAC (LP DAAC) Application for Extracting and Exploring Analysis Ready Samples (AppEEARS).

Soil moisture is important for surface hydrology as it controls the amount of water that can infiltrate into the ground, replenishing our aquifers or contributing to excess runoff.

Current ground measurements of soil moisture are sparse and have limited coverage; satellite data help fill in those gaps. On the other hand, satellite data are limited by their relatively coarse resolution; the preferred measurement should be chosen based upon your needs. Utilizing a combination of both ground-based and remote sensing data provides for spatial and temporal data continuity.

NASA's Soil Moisture Active Passive (SMAP) satellite measures the moisture in the top five cm of soil globally, every 2–3 days, at a resolution of 9–36 km. NASA, in collaboration with other agencies, has also developed models of soil moisture content, incorporating satellite information with ground-based data when available. These models are part of the Land Data Assimilation System (LDAS), of which there is a global collection (GLDAS) and a North American collection (NLDAS). LDAS takes inputs of measurements like precipitation, soil texture, topography, and leaf area index and then uses those inputs to model output estimates of soil moisture and evapotranspiration.

Research-quality data products can be accessed via Earthdata Search; datasets are available in HDF5 format, which are also customizable to GeoTIFF.

Image
Soil moisture as visualized using the ORNL DAAC Soil Moisture Visualizer. The map shows a flight path over Arizona in 2013. In the graph, AirMoss rootzone soil moisture data are plotted with SMAP rootzone soil moisture. Root zone soil moisture (RZSM) is the daily average of measurements at 0-100 cm depth. Image: NASA ORNL DAAC.

ORNL DAAC's Soil Moisture Visualizer integrates ground-based, SMAP, and other soil moisture data into a visualization and data distribution tool. LP DAAC's AppEEARS offers another option to simply and efficiently extract subsets, transform, and visualize SMAP data products. See Tools for Data Access and Visualization for additional information.

Data products can be visualized as a time-averaged map, an animation, seasonal maps, scatter plots, or a time series through an online interactive tool, Giovanni. Follow these steps to plot data in Giovanni: 1) Select a map plot type. 2) Select a date range. Data are in multiple temporal resolutions and multiple temporal coverages, so be sure to note the start and end date to ensure you access the desired dataset. 3) Check the box of the variable in the left column that you would like to include and then plot the data. For more information on choosing a type of plot, see the Giovanni User Manual.

Data can be visualized in Worldview:

Image
Man measuring snow bank in the mountains.

Snow cover is the presence of snow on land or bodies of water; measurements are acquired during the daytime and under cloud-clear conditions. The Moderate Resolution Imaging Spectroradiometer (MODIS) instruments aboard the Terra and Aqua satellites measure snow cover. Snow Water Equivalent (SWE) is the amount of water contained in snowpack in the Northern and Southern Hemispheres measured in millimeters (mm). 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 when the snow melts and the water availability for regions in lower elevations. The MODIS instrument measures snow cover while the Advanced Microwave Scanning Radiometer (AMSR) measures snow water equivalent.

Research-quality data products can be accessed via Earthdata Search; datasets are available in HDF format, which can be opened using Panoply.

Data can be visualized in Worldview:

LP DAAC's AppEEARS offers another option to simply and efficiently extract subsets, transform, visualize, and download MODIS Snow Cover data products.

Runoff after storm events can impact the amount of water entering a channel or water body. Satellites cannot measure runoff directly but information that can be used to assess predicted runoff can be measured using remote sensing. These data are input, along with ground-based data, into atmosphere-land models from LDAS to estimate runoff.

Data products can be visualized as a time-averaged map, an animation, seasonal maps, scatter plots, or a time series through an online interactive tool, Giovanni. Follow these steps to plot data in Giovanni: 1) Select a map plot type. 2) Select a date range. Data are in multiple temporal resolutions, so be sure to note the start and end date to ensure you access the desired dataset. 3) Check the box of the variable in the left column that you would like to include and then plot the data. For more information on choosing a type of plot, see the Giovanni User Manual.

Image
An ASTER GDEM image of Mt. Raung and the surrounding area. Image Credit: Land Processes Distributed Active Archive Center

Knowing local topography is essential for disaster managers and emergency management professionals seeking to assess an area's risk level; knowing the height at which communities sit in relation to flood waters determines the exposure.

A method for delineating topography is NASA's Shuttle Radar Topography Mission (SRTM). SRTM provides a digital elevation model of all land between 60 degrees north and 56 degrees south, about 80% of Earth's landmass. The spatial resolution is 30 m in the horizontal plane. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Model (GDEM) coverage spans from 83 degrees north latitude to 83 degrees south, encompassing 99% of Earth's landmass. The spatial resolution is 30 m in the horizontal plane.

On average, compared to geodetic points over the U.S., SRTM data has a lower root mean square error (RMSE); RMSE is a commonly used method to express vertical accuracy of elevation datasets. Digital elevation model data accuracy is typically very sensitive to vegetation cover, however. ASTER tends to perform better over certain landcover types.

February 2020, LP DAAC released a new data product, NASADEM, available at 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. The improvements were achieved by reprocessing the original SRTM radar signal data and telemetry data with updated algorithms and auxiliary data not available at the time of the original SRTM processing.

NASA's Socioeconomic Data and Applications Center (SEDAC) provides a number of datasets on population exposure and vulnerability and flood hazard potential.

 

Image
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.

During the storm, Synthetic Aperture Radar (SAR) may provide a better "view," as it is able to penetrate cloud cover and works in both day and night conditions. SAR data are more complex, requiring a certain level of processing skill. See Tools for Data Access and Visualization for information on processing Sentinel SAR data.

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.
  • 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.
Image
Map of inundation in Amazon rain forest. The color key provides the color for the number of times an area was flooded, and 18 represents constant river. Numbers less than 18 are the number of times an area floods. Credit: ASF DAAC; Includes Material © JAXA/METI 2007.

SAR is a type of active data collection where a sensor produces its own energy and then records the amount of that energy reflected back after interacting with the Earth. While optical imagery is similar to interpreting a photograph, SAR data require a different way of thinking in that the signal is instead responsive to surface characteristics like structure and moisture.

  • Sentinel-1A and Sentinel-1B SAR data from Earthdata Search
    There are several options when choosing SAR data. Polarization is the direction the signal is transmitted and/or received. Dual polarization, for example, refers to two different signal directions. Another option for SAR data is the inclusion of phase information. Level 1 data are produced as single look complex (SLC), in which the phase information is preserved, or as ground-range detected (GRD), in which the phase information is lost. Dual polarized GRD is acceptable for flood inundation mapping.
  • Sentinel-1A and Sentinel-1B SAR data from Vertex
    Vertex is NASA's Alaska Satellite Facility DAAC (ASF DAAC) search tool, which allows for the preview of numerous types of SAR data, including Sentinel-1.

To learn more about SAR and processing Level 1 data, view the SAR-related Earthdata webinars, NASA's Applied Remote Sensing Training (ARSET) Program Introduction to SAR training, or ASF DAAC's inundation data recipes.

Data (often in NRT) can be visualized in Worldview and via NASA's experimental Global Flood Mapping and Advanced Rapid Imaging and Analysis (ARIA) projects:

  • 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.
  • MODIS Flood Inundation Maps
    1-3 or 14 day composites; flood water and surface water layers can be downloaded as shapefiles, while the water product itself can be downloaded as a GeoTIFF.
  • Event Response to Floods at 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. Products are in folders based on the date of the event and the location.

NASA Disasters Flood Dashboard and Events

The dashboard contains experimental NASA products that may assist in preparing for or responding to a flood. NASA Disasters also creates products for specific events and provides other information to help interpret the data.

 

Monitoring Flood Conditions using NASA Earth Observation Data is a story map from NASA’s ArcGIS DAAC Collaboration. Satellite observations can monitor the occurrence of floods and map out areas most at risk of flooding. Datasets in the story map include precipitation, soil moisture, flood detection, and reservoirs and dams.

NASA Applied Sciences Disasters Flood Dashboard and Events

The dashboard contains experimental NASA products that may assist in preparing for or responding to a flood. NASA Disasters also creates products for specific events and provides other information to help interpret the data.

Last Updated
Oct 19, 2021