From Wood–Foliar Semantics to 3D Fuel Characterization: Transferable Deep Learning for Terrestrial LiDAR Across Global Forest Ecosystems
Terrestrial Light Detection and Ranging (LiDAR) provides detailed three-dimensional (3D) observations of forest structure, yet transferable wood–foliar semantic segmentation remains challenging because of forest structural heterogeneity, occlusion, and variability across forest ecosystems and terrestrial LiDAR platform...