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.
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).
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.
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.
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.
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.
Principal Investigator: Bryce Currey
The LPJ-PROSAIL global simulated imaging spectroscopy products are being developed to provide data analogs for the development of future spaceborne global imaging spectroscopy missions including NASA’s Surface Biology and Geology (SBG). The data products consist of simulated imaging spectroscopy data produced by the LPJ-PROSAIL model. The LPJ-PROSAIL model was developed by coupling LPJ, a dynamic global vegetation model, with PROSAIL, a canopy radiative transfer model. LPJ-PROSAIL will consist of multiple products containing dynamic surface reflectance, dynamic top-of-atmosphere radiance, and vegetation traits. The reflectance and radiance products will have a spectral range of 400 to 2500 nanometers (nm) with a spectral resolution of 10 nm at approximately 50 kilometer spatial resolution. Data will be available for each year from 2000 to present. Data availability within that timeframe will vary by product. Each granule will contain a full year of simulated monthly data. For more information visit the LPJ-PROSAIL website.
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.
INCA
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.