Science of Remote Sensing (Jun 2023)
Using simulated GEDI waveforms to evaluate the effects of beam sensitivity and terrain slope on GEDI L2A relative height metrics over the Brazilian Amazon Forest
Abstract
The vertical structure of forests provides important parameters for estimating aboveground biomass (AGB) and it can be measured by lidar sensors. The Global Ecosystem Dynamics Investigation (GEDI) full-waveform lidar sensor collects data systematically over the Earth's surface from the International Space Station. Since GEDI became operational, it has collected billions of ∼25-m diameter footprints. This massive dataset has been used to create higher level gridded and non-grided products. However, GEDI's ∼25-m footprints can be subject to errors associated with effects of geolocation, terrain slope, and beam sensitivity, among others, which are likely transferred to the downstream products. This study aims to (1) evaluate the effect of beam sensitivity and terrain slope on the accuracy of relative heights (RH) of GEDI product L2A version 2 through comparison with discrete-return airborne lidar data collected over transects in the Brazilian Amazon Forest biome, (2) assess GEDI's geolocation uncertainty and investigate its combined effects with beam sensitivity and terrain slope, and (3) re-evaluate beam sensitivity and terrain slope effects on the GEDI L2A RHs using footprints that were geolocation-adjusted through a simple novel approach. The analysis separates GEDI footprints by acquisition time, i.e., daytime, nighttime, and combined (all-data). The discrete-return airborne lidar point clouds are used to derive terrain slope within the GEDI footprints and to simulate GEDI waveforms and derive RHs comparable to the GEDI L2A product. Results indicate that terrain slope only causes significant effects on GEDI data collected during daytime because solar radiation affects waveform signal-to-noise ratio. Beam sensitivity causes significant effects on nighttime and all-data GEDI L2A RHs. If geolocation uncertainty is considered, the effects of beam sensitivity and terrain slope have just minor changes. Geolocation-adjusted data continue showing significant effects on nighttime and all-data RH differences caused by beam sensitivity but produce unbiased results. This study improves the understanding of how beam sensitivity, terrain slope, and their combined effect with geolocation uncertainty may affect the GEDI L2A RH collected over the Brazilian Amazon forest during daytime and nighttime.
