Collection Overview


The Community collection includes land data products derived from one or more of the National Aeronautics and Space Administration (NASA) Earth Observing System (EOS) missions. These Community data products are generated by selected scientists and are not considered to be part of the EOS mission's standard data products.

Airborne Hyperspectral Reflectance Mosaic

Principal Investigators: John Gamon, Ran Wang, Hamed Gholizadeh, Jeannine Cavender-Bares, Christopher J. Helzer

Airborne Hyperspectral Reflectance datasets were acquired over various plots and sites: Cedar Creek Ecosystem Science Reserve (CCESR), Minnesota; Tallgrass Prairie Preserve, Oklahoma; Wood River, Nebraska; and Indian Cave State Park, Nebraska. These fine resolution mosaics can be used to better understand the optical diversity-biodiversity relationship and to investigate the spatial sensitivity of the optical diversity-biodiversity relationship at local scales.

Airborne Hyperspectral Reflectance Mosaic Products Table


Principal Investigator: Glynn Hulley, Jet Propulsion Laboratory (JPL)

Using data from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) on NASA's Terra spacecraft, NASA/JPL derived the most detailed global emissivity map of the Earth, termed the ASTER Global Emissivity Database (GED).

ASTER GED Products Table


Principal Investigator:  Prasad Thenkabail, Itiya P. Aneece, Isabella Mariotto

The Global Hyperspectral Imaging Spectral-library of Agricultural crops (GHISA) is a comprehensive hyperspectral library of the world’s major agricultural crops (e.g., wheat, rice, barley, corn, soybeans, cotton, sugarcane, potatoes, chickpeas, lentils, and pigeon peas). Hyperspectral data for GHISA were acquired from spaceborne, airborne, and ground-based platforms.

GHISA Products Table


Principal Investigator: Bruce Cook

Goddard’s Light Detection and Ranging (LiDAR), Hyperspectral, and Thermal Imager (G-LiHT) was developed to simultaneously derive information about the composition, structure, and function of terrestrial ecosystems using a combination of airborne LiDAR, imaging spectroscopy, and thermal measurements.

G-LiHT Products Table

Headwall Hyperspectral Reflectance Mosaic

Principal Investigator: John Gamon, Ran Wang

An imaging spectrometer on an airborne tram system collected images at 1-millimeter spatial resolution for 33 selected plots at the biodiversity (BioDIV) experiment at the CCESR LTER, Minnesota. The hyperspectral range and fine resolution of the data will assist researchers in studying biodiversity in this area. These findings can be used to guide future airborne studies in developing more effective large-scale biodiversity sampling methods.

Headwall Hyperspectral Reflectance Mosaic Products Table


Principal Investigator: Prasad Thenkabail

The Global Food Security-support Analysis Data (GFSAD) project provides the highest-known spatial-resolution Landsat-derived Global Rainfed and Irrigated area Product (LGRIP) at 30 meter spatial resolution for the nominal year 2015. The LGRIP product maps agricultural lands, calculates irrigated and rainfed areas, and performs accuracy assessment of the product.

LGRIP30 Products Table


Principal Investigator: Mark Friedl

NASA’s Multi-Source Land Imaging (MuSLI) Land Surface Phenology (LSP) (MSLSP) provides a 30 m spatial resolution data product containing phenology timing metrics for North America. These data are useful for a wide range of applications including: ecosystem and agro-ecosystem modeling, monitoring of terrestrial ecosystems and their response to climate change and extreme events, as well as mapping land cover, land use, and land cover change.

MuSLI Products Table

FUTURE Community


Principal Investigator: Josh Gray

NASA’s Indicator of National Climate Assessment (INCA) will provide a 500 meter spatial resolution, yearly data product that spans from January 2001 to December 2016; it will contain global phenology metrics based on Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) data. This data product will provide a remote sensing-based land surface phenology climate indicator (LSP-CI) that supports the National Climate Assessment’s need for national scale, long-term monitoring of climate change impacts on ecosystems.