GEDI-Guided Deep Learning for Forest Canopy Height Completion Using Sentinel-2 Imagery, Sparse LiDAR Observations, and Gradient-Based Reconstruction
GEDI-Guided Sentinel Network (GSen-Net), a deep learning framework for dense canopy height completion from Sentinel-2 multispectral imagery and sparse GEDI RH98 observations is proposed, which reformulates canopy height estimation as a gradient-based completion problem, in which spatial height gradients are predicted a...