Short Name:
GEDI02_B

GEDI L2B Canopy Cover and Vertical Profile Metrics Data Global Footprint Level V002

The Global Ecosystem Dynamics Investigation (GEDI) ) mission aims to characterize ecosystem structure and dynamics to enable radically improved quantification and understanding of the Earth’s carbon cycle and biodiversity. The GEDI instrument produces high resolution laser ranging observations of the 3-dimensional structure of the Earth. GEDI is attached to the International Space Station (ISS) and collects data globally between 51.6° N and 51.6° S latitudes at the highest resolution and densest sampling of any light detection and ranging (lidar) instrument in orbit to date. Each GEDI Version 2 granule encompasses one-fourth of an ISS orbit and includes georeferenced metadata to allow for spatial querying and subsetting. The purpose of the GEDI Level 2B Canopy Cover and Vertical Profile Metrics product (GEDI02_B) is to extract biophysical metrics from each GEDI waveform. These metrics are based on the directional gap probability profile derived from the L1B waveform. Metrics provided include canopy cover, Plant Area Index (PAI), Plant Area Volume Density (PAVD), and Foliage Height Diversity (FHD). The GEDI02_B product is provided in HDF5 format and has a spatial resolution (average footprint) of 25 meters. The GEDI02_B data product contains 96 layers for each of the eight-beam ground transects (or laser footprints located on the land surface). Datasets provided include precise latitude, longitude, elevation, height, canopy cover, and vertical profile metrics. Additional information for the layers can be found in the GEDI Level 2B Data Dictionary. Improvements for Version 2 * Metadata has been updated to include spatial coordinates. * Granule size has been reduced from one full ISS orbit (~1.2 GB) to four segments per orbit (~0.3 GB). * Filename has been updated to include segment number and version number. * Improved Geolocation. * Added elevation from the SRTM digital elevation model for comparison. * Modified the method to predict an optimum algorithm setting group per laser shot. * Added additional land cover datasets related to phenology, urban infrastructure, and water persistence. * Added selected_mode_flag dataset to root beam group using selected algorithm. * Removed shots when the laser is not firing. * Modified file name.

Map of Earth