GEDI AND SENTINEL-2 INTEGRATION FOR MAPPING COMPLEX WETLANDS

Wetlands serve critical functions for protecting ecosystems but are declining globally due to anthropogenic activities and environmental change. There are challenges in delineating wetlands that partially cannot be addressed using the integration of optical and SAR data. NASA's global ecosystem dynamics investigation (GEDI) data, forest height products can differentiate wetland types with different heights. However, GEDI data is only available for limited footprints. In this study, we used a random forest regression model to create a canopy height model (CHM) by merging discrete GEDI footprints with Sentinel-2 data. We calculated the R-squared and RMSE using test data (0.81 and 3.48 meters, respectively). Such an investigation might provide the basis for better wetland management.