Wall-to-Wall Mapping of Forest Canopy Height using ICESat-2 Data and Multi-source Remote Sensing Images in a Machine Learning Framework
Forest Canopy Height (FCH) is one of the key variables for understanding forest structure distribution and growth. Remotely sensed data such as the NASA Ice, Cloud and Land Elevation Satellite-2 (ICESat-2) ATL08 provides accurate FCH measurements; however, its point-based nature limits spatial continuity. This study addresses the challenge by generating a continuous FCH map over the West Usambara
