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Agricultural and Water Resources Data Pathfinder: Land Data

Farms rise from a floodplain where the Mojave nation meets Arizona, Nevada, and California. Astronaut photo ISS051-E-13172 was acquired on April 14, 2017 aboard the International Space Station. I
Farms rise from a floodplain where the Mojave nation meets Arizona, Nevada, and California.

Land is a key component of the overall Earth system. Changes in the land surface can impact climate, terrestrial ecosystems, and hydrology, which is how water moves on land. The land surface, including land cover types, land surface temperature, and topography, are critical to monitoring agricultural practices and water resource availability and providing interventions when necessary.

To read about the data or benefits and limitations of using remote sensing data, view the Agriculture and Water Resources Data Pathfinder page.

Land Surface Reflectance

Land Surface Reflectance
September 10, 2009, Landsat image of farmland across northwest Minnesota

September 10, 2009, Landsat image of farmland across northwest Minnesota. Image: NASA Earth Observatory.

Land 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. It is useful for measuring the greenness of vegetation, which can then be used to determine phenological transition dates including the start of the growing season, the period of peak growth, and the end of the growing season. Agricultural production estimates must be restricted to crop-specific areas to avoid confusion with other crops, natural vegetation, and areas of no vegetation. This allows specific crops to be followed through time with continued observations using sustained land imaging and multi-spectral high-resolution imagery.

The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument aboard NASA's Terra satellite is a high-resolution instrument that acquires visible and near-infrared (VNIR) reflectance data at 15 m spatial resolution and short wave infrared (SWIR) reflectance data at 30 m spatial resolution. A cooperative effort between NASA and Japan's Ministry of Economy Trade and Industry (METI), ASTER data are distributed by NASA's Land Processes Distributed Active Archive Center (LP DAAC). 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. ASTER surface reflectance products are processed on-demand and can be requested through Earthdata Search (note that there is a limit of 2,000 granules per order):

The Enhanced Thematic Mapper (ETM+) sensor and the Operational Land Imager (OLI) instruments aboard the joint NASA/USGS Landsat 7 (ETM+) spacecraft and Landsat 8 (OLI) spacecraft acquire VNIR data at 30 m spatial resolution every 16 days (less days as you move away from the equator). Landsat 9 is scheduled for launch in September 2021 and carries two instruments: the OLI-2 (which is a copy of the Landsat 8 OLI) and the Thermal Infrared Sensor-2 (TIRS-2, which measures land surface temperature in two thermal infrared bands). Landsat satellite operations and data archiving are coordinated at the USGS Earth Resources Observation and Science (EROS) Center, which also is the location of LP DAAC.

Research quality land surface reflectance data products can be accessed directly using Earthdata Search (note: you will need a USGS Earth Explorer login—which is separate from the NASA Earthdata Login—to download Landsat data):

Multi-temporal Enhanced Vegetation Index-2 information from HLS for an area of irrigated cropland of Central California (near Los Banos). The colors represent mean EVI2 for three periods of the 2018 growing season: Red areas peak early in the season, Green areas peak in the middle, and Blue areas peak late.

Multi-temporal Enhanced Vegetation Index-2 (EVI2) information from HLS for an area of irrigated cropland of Central California (near Los Banos), USA. The colors represent mean EVI2 for three periods of the 2018 growing season: Red areas peak early in the season, Green areas peak in the middle, and Blue areas peak late. For more information on this work, see Using NASA's HLS Product to Give Farmers Real-Time Crop Health Information on the NASA Landsat Science website. Image: Landsat/Sulla-Menashe, et al.

Another high-resolution land surface reflectance imagery option is Harmonized Landsat and Sentinel-2 (HLS) imagery. HLS imagery provides consistent surface reflectance and top of atmosphere brightness data from the Landsat 8 OLI 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. HLS data are currently provisional and not considered standard data products. A science quality HLS dataset is expected to be released in fall 2021.

The Application for Extracting and Exploring Analysis Ready Samples (AppEEARS) tool, available through LP DAAC, offers a simple and efficient way to access, transform, and visualize geospatial data from a variety of federal data archives, including the USGS Landsat Analysis Ready Data (ARD) surface reflectance product. Landsat ARD are for Landsat Collection 1 and are available for the conterminous United States, Alaska, and Hawaii using Landsat 8 OLI/Thermal Infrared Sensor (OLI/TIRS), Landsat 7 ETM+, and Landsat 4-5 Thematic Mapper (TM) data.

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Land Surface Temperature

Land Surface Temperature

Satellite images show the relationship between the characteristics of a landscape, and day and night surface skin temperature. Heavily forested areas remain relatively cool throughout the day, while barren and arid areas can be tens of degrees warmer. These images were acquired in the early morning and afternoon of July 6, 2011.

Satellite images show the differences in land surface temperature during the day (middle image) and at night (bottom image). Top image is a natural color image. Darker colors indicate cooler temperatures. Heavily forested areas remain relatively cool throughout the day while barren and arid areas can be significantly warmer. These images were acquired over the state of Oregon, USA, in the early morning and afternoon of July 6, 2011. Image: NASA Earth Observatory.

Land Surface Temperature (LST) describes processes such as the exchange of energy and water between the land surface and Earth's atmosphere and influences the rate and timing of plant growth. LST data can improve decision-making for water use and irrigation strategies.

Research quality LST data products can be accessed directly from Earthdata Search and also are available through the Data Pool at LP DAAC. Data from the MODIS and ASTER instruments are available in HDF format; data from the VIIRS and ECOSTRESS instruments are available in HDF5 format:

To quickly extract a subset of ECOSTRESS, MODIS, or VIIRS data for a region of interest, use the AppEEARS tool available through LP DAAC or the subsetting tools available through NASA's Oak Ridge National Laboratory DAAC (ORNL DAAC). See the Tools for Data Access and Visualization section for additional information on both of these tools.

LST data can be visualized and interactively explored using NASA Worldview:

LST data also are produced as part of the joint NASA/USGS Landsat series of Earth observing missions:

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Knowing local topography is essential for professionals seeking to assess an area's runoff potential and the availability of water in lower-lying areas.

An ASTER GDEM image of Mt. Raung and the surrounding area.

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

A method for delineating topography is the 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 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.

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Runoff potential is very 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 using remote sensing. 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.

  • NLDAS (North American) Runoff Data in Giovanni
    Select a map plot (you can generate a time-averaged map, an animation, or seasonal maps), date range and region, select your variable and then plot the data. Data can be downloaded as GeoTIFF.
  • GLDAS (Global) Runoff Data in Giovanni
    Select a map plot (you can generate a time-averaged map, an animation, or seasonal maps), date range, select your variable and then plot the data (data are in multiple temporal resolutions and multiple temporal coverages, so be sure to note the starting and end date to ensure you access the desired dataset). Data can be downloaded as GeoTIFF.

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Tools for Data Access and Visualization

Tools for Data Access and Visualization

Earthdata Search | Panoply | Giovanni | Worldview | AρρEEARS | Soil Moisture Visualizer | MODIS/VIIRS Subsetting Tools Suite

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.

Screenshot of the Search Earthdata site.

In the project area, you can customize your granule. You can reformat the data and output as HDF, NetCDF, ASCII, KML, or GeoTIFF format. You can also choose from a variety of projection options. Lastly you can subset the data, obtaining only the bands that are needed.

Earthdata Search customization tools diagram.


Files in HDF and NetCDF format 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.


NASA's National Snow and Ice Data Center DAAC (NSIDC DAAC) has an HDF to GeoTIFF conversion tool (HEG), which allows you to geolocate, subset, stitch, and re-grid certain HDF-EOS datasets.


Giovanni is an online environment for the display and analysis of geophysical parameters. There are many options for analysis. The following are the more popular ones.

  • Time-averaged maps are a simple way to observe the variability of data values over a region of interest.
  • Map animations are a means to observe spatial patterns and detect unusual events over time.
  • Area-averaged time series are used 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 are used to display the distribution of values of a data variable in a selected region and time interval.

For more detailed tutorials:

  • Giovanni How-To's on GES DISC's YouTube channel.
  • 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.


NASA's EOSDIS Worldview visualization application provides the capability to interactively browse over 900 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 now includes nine geostationary imagery layers from GOES-East, GOES-West and Himawari-8 available at ten 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.

Worldview data visualization of the nighttime lights in Puerto Rico pre- and post- Hurricane Maria, which made landfall on September 20, 2017. Post-hurricane image shows widespread outages around San Juan, including key hospital and transportation infrastructure.

Worldview Suomi NPP/VIIRS nighttime lights comparison image showing power outages caused by Hurricane Irma in September 2017. The right image (acquired 1 September 2017) shows the island before Hurricane Irma. The left image (acquired 9 September 2017) shows power outages across island after Hurricane Irma. Interactively explore this image in NASA Worldview. Image: NASA Worldview.


AppEEARS, from 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

You can define your region of interest in three ways:

  • Upload a vector polygon file in shapefile format (you can upload a single file with multiple features or multipart single features). Files in .shp, .shx, .dbf, or .prj format must be zipped into a file folder to upload.
  • Upload a vector polygon file in Geographic JavaScript Object Notation (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, WELDUSMO), 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.

Extracting an area in AppEEARS

Selecting Output Options

Two output file formats are available:

  • GeoTIFF
  • NetCDF4

If GeoTIFF is selected, one GeoTIFF will be created for each feature in the input vector polygon file for each layer by observation. If NetCDF4 is selected, outputs will be grouped into .nc format files by product and by feature.

If GeoTIFF is selected, you must select a projection

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.

Interpreting Results in AppEEARS

Be sure to check out the AppEEARS documentation to learn more about downloading the output files in GeoTIFF or NetCDF4 format.

Soil Moisture Visualizer

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, view the Soil Moisture Visualizer 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.

ORNL DAAC Soil Moisture Visualizer

The Soil Moisture Visualizer allows users to compare soil moisture measurements from multiple sources at the same location. In this screenshot, Level 4 Root Zone Soil Moisture (L4 RZSM) data acquired by NASA’s Soil Moisture Active Passive (SMAP) satellite 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, USA. Daily precipitation values for the site (purple spikes) are also provided for reference. Image: NASA ORNL DAAC.

MODIS/VIIRS Subsetting Tools Suite

ORNL DAAC also has several MODIS and VIIRS Subset Tools for subsetting data.

  • With the Global Subset Tool, you can request a subset for any location on earth, provided as GeoTIFF and in text format, including interactive time-series plots and more. Users specify a site by entering the site's geographic coordinates and the area surrounding that site, from one pixel up to 201 x 201 km. From the available datasets, you can specify a date and then select from MODIS Sinusoidal Projection or Geographic Lat/Long. You will need an Earthdata Login to request data.
  • With the Fixed Subsets Tool, you can download pre-processed subsets for 2000+ field and flux tower sites for validation of models and remote sensing products. The goal of the Fixed Sites Subsets Tool is to prepare summaries of selected data products for the community to characterize field sites.
  • 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. Web service client and libraries are available in multiple programming languages, allowing integration of subsets into users' workflow.

Directions for subsetting data with the ORNL DAAC MODIS and VIIRS subset tool

Top image: The Global Subsets Tool enables users to download available products for any location on Earth. Bottom image: The Fixed Sites Subsets Tool provides spatial subsets for established field sites for site characterization and validation of models and remote sensing products. Image: NASA ORNL DAAC.

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Published November 19, 2019

Page Last Updated: Aug 24, 2021 at 1:38 PM EDT