WHAT IS GEDI?
GEDI is a full-waveform lidar instrument that makes detailed measurements of the 3D structure of the Earth’s surface. Lidar is an active remote sensing technology (the laser version of radar) which uses pulses of laser light to measure 3D structure. The light is reflected by the ground, vegetation and any clouds and is then collected by GEDI’s telescope. These photons are then directed towards detectors, converting the brightness of the light to an electronic voltage which is then recorded as a function of time in 1 ns (15 cm) intervals. Time is converted to range (a distance) by multiplying by the speed of light. The recorded voltage as a function of range is the full-waveform.
WHAT DOES GEDI MEASURE?
Lidar waveforms quantify the vertical distribution of vegetation by recording the amount of laser energy reflected by plant material (stems, branches, and leaves) at different heights above the ground. From GEDI waveforms, four types of structure information can be extracted: surface topography, canopy height metrics, canopy cover metrics, and vertical structure metrics.
GEDI data products
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 CARBON 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.