Reconstruction of Tree Crowns from Airborne Lidar for 3D Radiative Transfer Simulations

3D radiative transfer models (3D RTMs) serve as essential tools for accurately retrieving forest products from multi-source earth observation data and comprehending complex radiation signals from various forest elements, such as branches, leaves, soil and their underlying physical interactions. However, due to the extensive parameter inputs required by the 3D RTM, especially structural parameters, it has become a hindrance to the development of such processes. Although LIDAR provides precise structural information about vegetation, the construction of forest canopy geometric models from LIDAR data for the simulation of reflectance has not been thoroughly investigated. In this study, A method for constructing an explicit forest geometric structure is proposed from ALS point cloud data, and the fitted tree crown's Plant Area Density (PAD) is subsequently estimated by utilizing point cloud intensity information. The various representations of tree crowns (alphashape, voxel, ellipsoid) from ALS are analyzed and compared. Our results demonstrate that the geometric model constructed based on ALS point cloud data can robustly simulate reflectance using 3D RTMs. This approach also holds the potential for relatively high-resolution applications.