Abstract: To capture information about the 3D geometric structures of trees more effectively and address the challenge of high-precision, high-fidelity tree reconstruction, this study proposed a method for 3D modeling of trees based on terrestrial LiDAR point cloud. To overcome the occlusion caused by leaf gaps in TLS, this method fully considered the aggregation of leaves, as well as the morphological characteristics of both leaves and branches. By conducting the model fitting and reconstruction of tree leaves and branches using Delaunay triangulation and Alpha-shape algorithm, respectively, the proposed method effectively addressed previous issues such as unrealistic tree structures and imprecise organ modeling, thus achieving the 3D reconstruction of individual tree leaves and small branches efficiently. This study holds great significance for determining forest structural parameters and managing resources, while also offering a valuable reference for component-level real scene 3D modeling of typical trees.