Background: Skeletons extracted from point clouds of woody materials present canopy structural features (e.g., the inclination angle of branches) for simulating canopy interception and understory solar radiation distribution. However, existing methods cannot easily capture structure-lossless skeletons of woody organs from tree point-cloud data. To fulfill this goal, we proposed a distance-weighted method, named the TreeSke method, to iteratively contract the point cloud of canopy woody materials to their median-axis skeleton. After heuristically searching the local point set, we pointwise-extracted the tightened weights to obtain the coarse skeleton. Then, we thinned the skeleton of woody organs and optimized it by a noise filtering and re-centering process. Results: The proposed method was verified on six simulated tree models that have reference skeletons and two field-collected datasets at the plot level. The results show that the TreeSke-extracted skeletons were with higher location accuracy than using the other two tested methods. The mean offset distance, the RMSE of the offset distance, and the Hausdorff distance between the extracted and reference skeletons were less than 0.04 m, less than 0.06 m, and less than 0.11 m, respectively. Conclusions: The extracted skeletons by the TreeSke method could nearly integrally depict the structural features of woody materials. The proposed method showed robust for noisy points and outliers, while missing data would reduce the skeleton integrity and cause deformation errors. From the extracted skeletons, users can extract the inclination-angle features of canopy woody materials, which are useful for simulating most eco-hydrological processes.

No abstract