Integrating Spaceborne Lidar Nasa’s Gedi With Imaging Sensors To Map Aboveground Biomass In Fragmented Tropical Forests

Human induced forest degradation can reduce aboveground biomass (AGB) and carbon stock of forest fragments. Developing approaches to assess these effects in highly-degraded tropical forests is necessary, especially at large scales. In this study, we developed a framework to upscale NASA’s GEDI spaceborne lidar AGB products using data from imaging sensors in the Brazilian Atlantic Forest – one of the most degraded and fragmented ecosystems in the world. A Random Forest model was trained using GEDI footprint level AGB as response and vegetation indices from Landsat 8/OLI and ALOS/PALSAR-2 images as predictors. The models were used to map and assess the AGB at the core and edge of 8783 fragments. The model had r = 0.83 and RMSE = 34.06 Mg/ha. The AGB in the fragments’ edges were significantly lower than in the fragments’ cores. The results demonstrated the potential of the developed framework to assess fragmentation effects on highly degraded tropical forest ecosystems.