G-LiHT Aerial Orthomosaic image, acquired over Klamath Lake, Oregon on June 30, 2018.
View full-size imageGoddard’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 0.02 m (1 inch) spatial resolution over locally defined areas. A low resolution browse is also provided with a color map applied in PNG format.
Metadata for individual flights is available as a pdf file and can be accessed through the Documentation button on this landing page. It contains information related to flight plans, acquisition details, field observations, and instrument specifications.
Characteristic | Description |
---|---|
Collection | G-LiHT |
DOI | 10.5067/Community/GLIHT/GLORTHO.001 |
File Size | ~250 MB |
Temporal Resolution | Varies |
Temporal Extent | 2017-02-21 to Present |
Spatial Extent | North America |
Coordinate System | Universal Transverse Mercator (UTM) |
Datum | World Geodetic System (WGS84) |
File Format | GeoTIFF |
Geographic Dimensions | Variable |
Characteristic | Description |
---|---|
Number of Science Dataset (SDS) Layers | 1 |
Columns/Rows | Variable |
Pixel Size | 0.02 m |
SDS Name | Description | Units | Data Type | Fill Value | No Data Value | Valid Range | Scale Factor |
---|---|---|---|---|---|---|---|
Aerial Orthomosaic | Aerial Orthomosaic | Meters | 32-bit floating point | N/A | NaN | N/A | N/A |
Once available, detailed information on quality for the GLORTHO product can be found on the G-LiHT website.
Orthomosaics are automatically generated, and results may not be optimal.