FitTree: Robust 3D tree mesh reconstruction from point clouds

The implementation of this work would not have been possible without the contributions of numerous researchers who have shared their open-source code. We would like to extend special thanks to Liu Zhihao and colleagues for releasing a series of outstanding algorithms for tree point cloud reconstruction. The tree skeleton generation and refinement presented in this paper build upon their optimized and visualized code, available at: https://github.com/RyuZhihao123/Point-cloud-3D-tree-reconstruction. In addition, the main trunk cylinder fitting was further improved and optimized based on the open-source code by Du Shenglan and collaborators, accessible at: https://github.com/tudelft3d/AdTree.<br><br>High-fidelity 3D tree mesh models have broad applications in virtual geographic environments, forest ecology, and digital entertainment. Although laser point clouds provide precise data, existing point cloud-based methods struggle with accuracy and completeness due to tree structural complexity, leaf occlusion, and data gaps. To address these challenges, we propose a novel framework that integrates data-driven and morphology-knowledge-driven techniques for generating high-quality tree mesh models with accurate trunk and overall crown morphology.Article DOI：10.1080/17538947.2026.2633848 ; Journal Title：International Journal of Digital Eart<br><br>