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.
This Data Pathfinder is designed to help guide you through the process of selecting and using datasets applicable to floods, with guidance on resolutions and direct links to the data sources.
Getting Started with this Data Pathfinder
Who is the intended audience for this Data Pathfinder?
This Data Pathfinder is primarily intended for:
Users with some experience using remote sensing data or who are experienced data science professionals
Geographic Information Systems (GIS) users interested in locating data (for workflows, web services, maps, and similar resources, see the GIS Data Pathfinder)
Python or R programmers interested in locating data
Join our community of NASA data users
While NASA data are openly available without restriction, an Earthdata Login is required to download data and to use some tools (such as Giovanni) with full functionality.
Benefits of having an Earthdata Login include:
Provides users a single sign-on, meaning that the user only has to enter their username and password once, to gain access to multiple (different) applications
Saves users’ preferences
Offers ability to receive news/notifications on data and services
Serves greater support for customizable interfaces
Gives supplemental information about data resources
If you have specific questions about how to use data, tools, or resources mentioned in this Data Pathfinder, please visit the Earthdata Forum. Here, you can interact with other data users and NASA subject matter experts on a variety of Earth science research and applications topics.
Earthdata Search is a tool for data discovery of Earth Observation data collections from NASA's Earth Observing System Data and Information System (EOSDIS), as well as U.S and international agencies across the Earth science disciplines. Users (including those without specific knowledge of the data) can search for and read about data collections, search for data files by date and spatial area, preview browse images, and download or submit requests for data files, with customization for select data collections.
In the project area, for some datasets, you can customize your granule. You can reformat the data and output as HDF, NetCDF, ASCII, KML, or a GeoTIFF. You can also choose from a variety of projection options. Lastly, you can subset the data, obtaining only the bands that are needed.
The NASA Worldview satellite imagery exploration tool provides the capability to interactively browse over 1,000 global, full-resolution satellite imagery layers and then download the underlying data. Many of the available imagery layers are updated within three hours of observation, essentially showing the entire Earth as it looks "right now." This supports time-critical application areas such as wildfire management, air quality measurements, and flood monitoring. Imagery in Worldview is provided by NASA's Global Imagery Browse Services (GIBS). Worldview also includes geostationary imagery layers from the GOES-East, GOES-West, and Himawari-8 satellites available at 10-minute increments for the last 30 days. These layers include Red Visible, which can be used for analyzing daytime clouds, fog, insolation, and winds; Clean Infrared, which provides cloud top temperature and information about precipitation; and Air Mass RGB, which enables the visualization of the differentiation between air mass types (e.g., dry air, moist air, etc.). These full disk hemispheric views allow for almost real-time viewing of changes occurring around most of the world.
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This GeoColor image from NASA Worldview shows Hurricane Ian approaching Florida on September 28, 2022. This image was acquired by the Advanced Baseline Imager (ABI) instrument aboard the joint NASA/NOAA GOES-East satellite. Click on image to view an animation created in Worldview of the hurricane's motion. Credit: NASA Worldview.Back to the Top of Tools
DisasterAWARE
DisasterAWARE 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.
DisasterAWARE Pro shows flood severity warnings at a sub-watershed level generated using NASA’s Model of Models (MoM) for the Congo Basin region of Africa in October 2022. Credit: Pacific Disaster Center, NASA
This tool provides near real-time, current, and past flood event mapping along with analysis on current flood events multiple data sources, including media reports.
The HYDrologic Remote Sensing Analysis for Floods (HYDRAFloods) publicly available, Python based application developed by NASA SERVIR that uses satellite imagery to produce flood water maps. HYDRAFloods was designed to provide near real-time flood monitoring which can assist with response to flood disasters. HYDRAFloods leverages the most recently available remotely sensed data acquired by multiple satellite platforms to automate the creation of daily flood maps. Through combining multiple satellite sources, including optical, microwave, and synthetic aperture radar datasets, near real-time flood maps with reduced cloud impact and increased satellite observations can be generated for use by disaster managers.
HDF and NetCDF files can be viewed in Panoply, a cross-platform application that plots geo-referenced and other arrays. Panoply offers additional functionality, such as slicing and plotting arrays, combining arrays, and exporting plots and animations.
Giovanni is an online environment for the display and analysis of geophysical parameters. There are many options for analysis, including:
Time-averaged maps to observe the variability of data values over a region of interest
Map animations to observe spatial patterns and detect unusual events over time
Area-averaged time series to display the value of a data variable that has been averaged from all the data values acquired for a selected region for each time step
Histogram plots to display the distribution of values of a data variable in a selected region and time interval
Data recipe for downloading a Giovanni map as NetCDF and converting its data to quantifiable map data in the form of latitude-longitude-data value ASCII text.
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Surface rainfall accumulations (mm) estimated from the NASA IMERG satellite precipitation product from 10 to 17 May 2020 in association with the passage of Typhoon Vongfong. Image from NASA GSFC using IMERG data archived at https://giovanni.gsfc.nasa.gov/giovanni/. This image was produced with the Giovanni online data system, developed and maintained by the NASA GES DISC.Back to the Top of Tools
AppEEARS
The Application for Extracting and Exploring Analysis Ready Samples (AppEEARS), available through NASA's Land Processes Distributed Active Archive Center (LP DAAC), offers a simple and efficient way to access and transform geospatial data from a variety of federal data archives. AppEEARS enables users to subset geospatial datasets using spatial, temporal, and band/layer parameters. Two types of sample requests are available: point samples for geographic coordinates and area samples for spatial areas via vector polygons.
Performing Area Extractions
After choosing to request an area extraction, you will be taken to the Extract Area Sample page where you will specify a series of parameters that are used to extract data for your area(s) of interest.
Spatial Subsetting
Define your region of interest in one of these three ways:
Upload a vector polygon file in shapefile format (you can upload a single file with multiple features or multipart single features). The .shp, .shx, .dbf, or .prj files must be zipped into a file folder to upload
Upload a vector polygon file in GeoJSON format (can upload a single file with multiple features or multipart single features)
Draw a polygon on the map by clicking on the Bounding box or Polygon icons (single feature only)
Select the date range for your time period of interest.
Specify the range of dates for which you wish to extract data by entering a start and end date (MM-DD-YYYY) or by clicking on the Calendar icon and selecting dates a start and end date in the calendar.
Adding Data Layers
Enter the product short name (e.g., MOD09A1, ECO3ETPTJPL), keywords from the product long name, a spatial resolution, a temporal extent, or a temporal resolution into the search bar. A list of available products matching your query will be generated. Select the layer(s) of interest to add to the Selected layers list. Layers from multiple products can be added to a single request. Be sure to read the list of available products available through AppEEARS.
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Selecting Output Options
Two output file formats are available:
GeoTIFF
NetCDF-4
If GeoTIFF is selected, one GeoTIFF will be created for each feature in the input vector polygon file for each layer by observation. If NetCDF-4 is selected, outputs will be grouped into .nc files by product and by feature.
Interacting with Results
Once your request is completed, from the Explore Requests page, click the View icon in order to view and interact with your results. This will take you to the View Area Sample page.
The Layer Stats plot provides time series boxplots for all of the sample data for a given feature, data layer, and observation. Each input feature is renamed with a unique AppEEARS ID (AID). If your feature contains attribute table information, you can view the feature attribute table data by clicking on the Information icon to the right of the Feature dropdown. To view statistics from different features or layers, select a different AID from the Feature dropdown and/or a different layer of interest from the Layer dropdown.
Be sure to check out the AppEEARS documentation to learn more about downloading the output GeoTIFF or NetCDF-4 files.
NASA's Oak Ridge National Laboratory DAAC (ORNL DAAC) has developed a Soil Moisture Visualizer tool (read about it at Soil Moisture Data Sets Become Fertile Ground for Applications) that integrates a variety of different soil moisture datasets over North America. The visualization tool incorporates in situ, airborne, and remote sensing data into one easy-to-use platform. This integration helps to validate and calibrate the data, and provides spatial and temporal data continuity. It also facilitates exploratory analysis and data discovery for different groups of users. The Soil Moisture Visualizer offers the capability to geographically subset and download time series data in .csv format. For more information on the available datasets and use of the visualizer, see the Soil Moisture Visualizer User Guide.
To use the visualizer, select a dataset of interest under Data. Depending on the dataset chosen, the visualizer provides the included latitude/longitude or an actual site location name and relative time frames of data collection. Upon selection of the parameter, the tool displays a time series with available datasets. All measurements are volumetric soil moisture. Surface soil moisture is the daily average of measurements at 0-5 cm depth, and root zone soil moisture (RZSM) is the daily average of measurements at 0-100 cm depth. Lastly it provides data sources for download.
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The Soil Moisture Visualizer allows users to compare soil moisture measurements from multiple sources (figure legends, top left and bottom right) at the same location. In this screenshot, Level 4 Root Zone Soil Moisture (L4 RZSM) data from NASA’s Soil Moisture Active Passive (SMAP) Observatory are shown with data from in situ sensors across the 9-kilometer Equal-Area Scalable Earth (EASE) grid cell encompassing the Tonzi Ranch Fluxnet site in the Sierra Nevada foothills of California. Daily precipitation values for the site (purple spikes) are also provided for reference. Credit: NASA's ORNL DAAC.Back to the Top of Tools
With the Global Subset Tool, you can request a subset for any location, provided as GeoTIFF and in text format, including interactive time-series plots and more
With the Fixed Subsets Tool, you can download pre-processed subsets for more than 3,000 field and flux tower sites for validation of models and remote sensing products
With the Web Service, you can retrieve subset data (in real-time) for any location(s), time period, and area programmatically using a REST web service
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Series of screenshots showing options available in the MODIS/VIIRS Subsetting Tools. Credit: NASA's ORNL DAAC.Back to the Top of Tools
Spatial Data Access Tool (SDAT)
ORNL DAAC's SDAT is an Open Geospatial Consortium standards-based web application to visualize and download spatial data in various user-selected spatial/temporal extents, file formats, and projections. Several datasets including land cover, biophysical properties, elevation, and selected ORNL DAAC archived data are available through SDAT. KMZ files are also provided for data visualization in Google Earth.
Within SDAT, select a dataset of interest. Upon selection, the map service will open displaying the various measurements, with the associated granule, and a visualization of the selected granule.
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Canopy Height, Kalimantan Forests, Indonesia, 2014 from the Spatial Data Access Tool. Credit: NASA's ORNL DAAC.
You can then select your spatial extent, projection, and output format for downloading.
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Canopy Height, Kalimantan Forests, Indonesia, 2014 from the Spatial Data Access Tool with various output options. Credit: NASA's ORNL DAAC.Back to the Top of Tools
Sentinel Toolbox
The ESA (European Space Agency) Sentinel-1 Mission comprises two satellites: Sentinel-1A and Sentinel-1B (Sentinel-1C is scheduled for launch in 2014). The satellites carry Synthetic Aperture Radar (SAR) instruments operating at a C-Band frequency and orbit 180° apart, together imaging the entire Earth every six days. SAR is an active sensor that can penetrate cloud cover and vegetation canopy, and also observe at night. Therefore, it is ideal for flood inundation mapping. It also provides useful information to detect landscape movement after an earthquake, volcanic eruption, or landslide. ESA has developed a Sentinel-1 Toolbox to aid with processing and analysis of Sentinel-1 data. For more information about using SAR for flood inundation mapping, see ASF DAAC's flood inundation recipes for QGIS or ArcGIS.
Connection of Sustainable Development Goals to Floods
The Sustainable Development Goals (SDGs) are a collection of 17 interlinked global goals designed to be a blueprint for a sustainable future for all of Earth’s inhabitants. The SDGs are part of the 2030 Agenda for Sustainable Development, an international plan signed by all United Nations (UN) member states in 2015 and underpinned by the foundational components of People, Planet, and Prosperity.
The 17 SDGs in the Agenda are made up of 169 objectives that include specific social, economic, and environmental targets. These targets provide a blueprint for developing a more sustainable global future.
Data acquired remotely by sensors aboard satellites and aircraft or installed on the ground play a unique role in tracking the progress toward achieving the SDGs. These remotely sensed Earth observations provide consistent and continuous information on the state of Earth processes and their change over time. These data also are integral components of socioeconomic metrics that provide a measure of how humans co-exist with the environment and the stresses they encounter through natural and human-caused changes to the environment.
NASA Earth observation data are available without restriction to all data users, a policy that is being adopted by other international space agencies and one that reduces the cost of monitoring the SDGs and provides developing countries a means to acquire and utilize these data for other policy-making purposes.
NASA’s datasets are organized by topics that help users to locate, access, and apply relevant and complementary datasets for each SDG. The Floods Data Pathfinder addresses (but is not limited to) the following SDGs:
SDG
SDG Goals Relevant to Floods
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Goal 1. End poverty in all its forms everywhere
Target 1.5: Build the resilience of the poor and those in vulnerable situations and reduce their exposure and vulnerability to climate-related extreme events and other economic, social, and environmental shocks and disasters
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Goal 2. End hunger, achieve food security and improved nutrition, and promote sustainable agriculture
Target 2.4: Ensure sustainable food production systems and implement resilient agricultural practices that increase productivity and production; that help maintain ecosystems; that strengthen capacity for adaptation to climate change, extreme weather, drought, flooding, and other disasters; and that progressively improve land and soil quality
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Goal 11. Make cities and human settlements inclusive, safe, resilient, and sustainable
Target 11.5: Significantly reduce the number of deaths and the number of people affected and substantially decrease the direct economic losses relative to global gross domestic product caused by disasters, including water-related disasters, with a focus on protecting the poor and people in vulnerable situations
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Goal 13. Take urgent action to combat climate change and its impacts
Target 13.1: Strengthen resilience and adaptive capacity to climate-related hazards and natural disasters in all countries
Target 13.2: Integrate climate change measures into national policies, strategies, and planning
Target 13.3: Improve education, awareness-raising, and human and institutional capacity on climate change mitigation, adaptation, impact reduction, and early warning
The opportunities to connect NASA data to the SDGs are infinite; therefore, the datasets included in specific Data Pathfinders are not intended to be comprehensive. Additionally, NASA datasets are not official indicators for SDG monitoring and decision-making but are complementary.
