Digital Surface Model of Tree Canopy Structure from Lidar Data through Implicit Surface Reconstruction

Tree canopy structure is an important factor in forest fire, plant physiology, and tree competition. Quantifying the tree canopy structures is difficult due to the irregular shapes and spacing of the trees. Our method for estimating the canopy structure is based on Light Detection and Ranging (LIDAR) data. LIDAR has three-dimensional point distribution which allows us to ascertain the shape of objects on the ground. Our method consists of three steps. First, we partition the LIDAR points into subsets corresponding to individual trees using level set methods. Second, for each tree we select a subset of points near the crown surface. Finally, we use an isosurface method with radial basis functions to reconstruct the crown surface of each tree from the selected points. The resulting surface provides more precise information about crown base height, which was difficult to measure from discrete points in previous studies. Our approach improves the spatial accuracy of tree level parameters and provides 3D images of crown shapes.