Spatial Structure Evaluation of Chinese Fir Plantation in Hilly Area of Southern China Based on UAV and Cloud Model

Abstract

Chinese fir, as a crucial fast-growing tree species in the hilly regions of southern China, exhibits spatial structure characteristics that directly influence both the ecological functionality and productivity of its stands. This study focused on Chinese fir plantations in the Yangkou State-Owned Forest Farm, Fujian Province. Using UAV-LiDAR point cloud data, individual tree parameters such as height and crown width were extracted, and a DBH inversion model was constructed by integrating machine learning algorithms. Spatial structure parameters were quantified through weighted Voronoi diagrams. A comprehensive evaluation system was established based on the combined weighting method and fuzzy evaluation model to systematically analyze spatial structure characteristics and their evolutionary patterns across different age classes. The results demonstrated that growth environment indicators (openness and openness ratio) progressively declined with the stand’s age, reflecting deteriorating light conditions due to increasing canopy closure. Growth superiority (size ratio and angle competition index) exhibited a “V”-shaped trend, with the most intense competition occurring in the middle-aged stands before stabilizing in the over-mature stage. The resource utilization efficiency (uniform angle and forest layer index) showed continuous optimization, reaching optimal spatial configuration in over-mature stands. This study developed a spatial structure evaluation system for Chinese fir plantations by combining UAV data and cloud modeling, elucidating structural characteristics and developmental patterns across different growth stages, thereby providing theoretical foundations and technical support for close-to-nature management and the precision quality improvement of Chinese fir plantations.