G-LiHT Hyperspectral Radiance V001

Goddard’s LiDAR, Hyperspectral, and Thermal Imager (G-LiHT) mission is a portable, airborne imaging system that aims to simultaneously map the composition, structure, and function of terrestrial ecosystems. G-LiHT primarily focuses on a broad diversity of forest communities and ecoregions in North America, mapping aerial swaths over the Conterminous United States (CONUS), Alaska, Puerto Rico, and Mexico. The purpose of G-LiHT’s Hyperspectral Reflectance data product (GLREFL) is to provide high-resolution reflectance data, ranging in wavelength from 418 to 920 nanometers across 114 spectral ranges. Reflectance data is computed as the ratio between observed upwelling radiance and downwelling hemispheric irradiance and corrected for differences in cross-track illumination and Bidirectional Reflectance Distribution Function (BRDF) using an empirically derived multiplier. At a nominal flying height of 335 m above ground level (AGL), the at-sensor reflectance is a close approximation of surface reflectance. GLREFL data are processed as a zipped raster data product (GeoTIFF) with associated header file (.hdr) at 1 meter spatial resolution over locally defined areas. A low-resolution browse is also provided with a color map applied in PNG format.

Goddard’s LiDAR, Hyperspectral, and Thermal Imager (G-LiHT) mission is a portable, airborne imaging system that aims to simultaneously map the composition, structure, and function of terrestrial ecosystems. G-LiHT primarily focuses on a broad diversity of forest communities and ecoregions in North America, mapping aerial swaths over the Conterminous United States (CONUS), Alaska, Puerto Rico, and Mexico. The purpose of G-LiHT’s Hyperspectral Ancillary data product (GLHYANC) is to provide information related to aircraft attitude and altitude, view and solar angles, and other ancillary reflectance and radiance data. GLHYANC data are processed as a zipped raster data product (GeoTIFF) with associated header file (.hdr) at 1 meter spatial resolution over locally defined areas. Some data files may be in ENVI format.

Goddard’s LiDAR, Hyperspectral, and Thermal Imagery (G-LiHT) mission is a portable, airborne imaging system that aims to simultaneously map the composition, structure, and function of terrestrial ecosystems. G-LiHT primarily focuses on a broad diversity of forest communities and ecoregions in North America, mapping aerial swaths over the Conterminous United States (CONUS), Alaska, Puerto Rico, and Mexico. The purpose of G-LiHT’s Digital Surface Model data product (GLDSMT) is to provide LiDAR-derived visualizations of elevation above bare earth. GLDSMT data is offered in multiple formats, including Digital Surface Model, Mean, Aspect, Rugosity, and Slope. GLDSMT data are processed as multiple raster data products (GeoTIFFs) at a nominal 1 meter spatial resolution over locally defined areas. A low resolution browse is also provided showing the digital surface model with a color map applied in PNG format.

Goddard’s LiDAR, Hyperspectral, and Thermal Imager (G-LiHT) mission is a portable, airborne imaging system that aims to simultaneously map the composition, structure, and function of terrestrial ecosystems. G-LiHT primarily focuses on a broad diversity of forest communities and ecoregions in North America, mapping aerial swaths over the Conterminous United States (CONUS), Alaska, Puerto Rico, and Mexico. The purpose of G-LiHT’s Aerial Orthomosaic data product (GLORTHO) is to provide orthorectified high-resolution aerial photography. This data is provided as a supplement to other G-LiHT data products. GLORTHO data are processed as a raster data product (GeoTIFF) at 1 inch spatial resolution over locally defined areas. A low resolution browse is also provided with a color map applied in PNG format. Known Issues * Orthomosaics are automatically generated, and results may not be optimal.

Goddard’s LiDAR, Hyperspectral, and Thermal Imager (G-LiHT) mission is a portable, airborne imaging system that aims to simultaneously map the composition, structure, and function of terrestrial ecosystems. G-LiHT primarily focuses on a broad diversity of forest communities and ecoregions in North America, mapping aerial swaths over the Conterminous United States (CONUS), Alaska, Puerto Rico, and Mexico. The purpose of G-LiHT’s Hyperspectral Vegetative Indices data product (GLHYVI) is to provide vegetative, stress, and other index data in 44 science dataset layers. Included in the product are vegetative indices such as Normalized Difference Vegetation Index (NDVI), Triangular Vegetation Index (TVI), Renormalized Difference Vegetation Index (RDVI), Modified Triangular Vegetation Index (MTVI), and Difference Vegetation Index (DVI). Stress indices include, but are not limited to, Carter Stress, Gitelson and Merzlyac Stress, Maccioni Stress, and Vogelmann Stress. GLHYVI data are processed as a raster data product (GeoTIFF) at 1 meter spatial resolution over locally defined areas. A browse image displaying NDVI is also included. Some data files may be in ENVI format.

Goddard’s LiDAR, Hyperspectral, and Thermal Imager (G-LiHT) mission utilizes a portable, airborne imaging system that aims to simultaneously map the composition, structure, and function of terrestrial ecosystems. G-LiHT primarily focuses on a broad diversity of forest communities and ecoregions in North America, mapping aerial swaths over the Conterminous United States (CONUS), Alaska, Puerto Rico, and Mexico. The purpose of G-LiHT’s Canopy Height Model data product (GLCHMT) is to provide LiDAR-derived maximum canopy height and canopy variability information to aid in the study and analysis of biodiversity and climate change. Scientists at NASA’s Goddard Space Flight Center began collecting data over locally-defined areas in 2011 and that the collection will continue to grow as aerial campaigns are flown and processed. GLCHMT data are processed as a raster data product (GeoTIFF) at a nominal 1 meter spatial resolution over locally-defined areas. A low resolution browse is also provided showing the canopy height with a color map applied in JPEG format.