Assessing the Performance of GEDI LiDAR Data for Estimating Terrain in Densely Forested Areas

Abstract

The global ecosystem dynamics investigation (GEDI) contains a full waveform, multibeam laser altimeter, which provides vertical vegetation structure information. However, few studies have assessed the accuracy of using GEDI light detection and ranging (LiDAR) data in retrieving ground topography from dense forest environments. There has been no in-depth study assessing the accuracy of GEDI data with different kinds of elevation index in footprint samples from densely forested areas (canopy cover > 70%). To address this limitation, this study aims to assess the accuracy of ground topography estimates from dense forested terrain through the combination of airborne LiDAR data. The results show that under dense forest conditions, the mean elevation in the GEDI footprint performed more accurate than the max elevation, the min elevation, and the median elevation in the GEDI footprint. GEDI provides reasonable estimates of mean terrain height, with R2 of 0.99, root mean squared error (RMSE) of 6.08 m, and mean absolute error (MAE) of 3.92 m. In addition, dense forest ecosystems reduce the accuracy of the terrain height estimates. Overall, GEDI with its full-waveform technology represents promising spaceborne LiDAR for terrain height retrieval in dense forest environments.