
GEDI data products are designed to answer key science questions on the role of ecosystem structure now and in the future.
GEDI science data products include footprint and gridded data sets that describe the 3D features of the Earth. These data products are assigned different levels, which indicate the amount of processing that the data has undergone after collection. All products are publicly available, with the lower level products (L1 & L2) from NASA’s Land Processes Distributed Active Archive Center (LPDAAC) and the higher level (L3 & L4) from the ORNL DAAC. Data are initially transferred to the GEDI Mission Operations Center (MOC) at the Goddard Space Flight Center that deploys acquisition planning on a weekly basis, and then processed through the Science Operations Center (SOC) to distribute science data products to the above DAACs.
The physical theories, mathematical procedures and model assumptions that are used in the creation of these data products are described in the Algorithm Theoretical Basis Documents (ATBDs). These can be found here.
Level 1 - Geolocated waveforms
The raw GEDI waveforms as collected by the GEDI system are geolocated by our science team.
Level 2 - Footprint level canopy height and profile metrics
The waveforms are processed to provide canopy height and profile metrics. These are values calculated directly from the waveform return for each footprint such as terrain elevation, canopy height, RH metrics and Leaf Area Index (LAI). These metrics provide easy-to-use and interpret information about the vertical distribution of the canopy material.
Level 3 - Gridded canopy height metrics and variability
Level 3 products are gridded by spatially interpolating Level 2 footprint estimates of canopy cover, canopy height, LAI, vertical foliage profile and their uncertainties.
Level 4A and 4B - Footprint and Gridded Aboveground Biomass Estimates
Level 4 products are the highest level of GEDI product and represent the output of models. Footprint metrics derived from the L2 data products are converted to footprint estimates of aboveground biomass density using calibration equations. Subsequently, these footprints are used to produce mean biomass and its uncertainty in cells of 1 km using statistical theory.