林业科学2026，Vol.62Issue(4)：106-117,12.DOI:10.11707/j.1001-7488.LYKX20250136
点云语义引导的无人机激光雷达单木分割与参数估算
Point Cloud Semantic-Guided Individual Tree Segmentation and Parameter Estimation Using UAV Laser Scanning
摘要
Abstract
[Objective]To address crown overlap,sparse stem points,and noise interference in unmanned aerial vehicle laser scanning(ULS)point clouds for individual tree segmentation(ITS)and parameter estimation in eucalyptus plantations,a semantic-guided method for individual tree segmentation and parameter extraction was developed to improve segmentation accuracy and parameter estimation performance.[Method]Gaofeng Forest Farm in Nanning,Guangxi was selected as the study area,and a complete point-cloud processing workflow was established.A deep learning model was used to perform semantic segmentation on point clouds,the point clouds were classified into semantic categories,including stems,leaves,and ground.Subsequently,a hybrid algorithm combining density-based spatial clustering of applications with noise(DBSCAN)and K-nearest neighbors(KNN)was used for individual tree segmentation by incorporating semantic information.To counter the sparsity of ULS point clouds at the stem level,stem curve fitting was adopted for diameter at breast height(DBH)estimation,and a height pseudo-waveform method was employed for tree height estimation.The proposed method was validated across plots with varying structural complexities to assess its applicability and accuracy.[Result]Experimental results showed that high ITS accuracy was achieved in the eucalyptus plantations,with an overall recall of 0.92,precision of 0.95,and an average F-score of 0.93.For individual tree parameter estimation,tree height estimation showed a coefficient of determination(R2)of 0.98 with a root mean square error(RMSE)of 1.03 m.DBH estimation yielded an R2 of 0.81 and an RMSE of 2.96 cm.[Conclusion]The proposed method enables accurate individual tree segmentation and parameter extraction from ULS point clouds in eucalyptus plantations,indicating that semantic guidance can improve the applicability of ULS point clouds for individual-tree-level analysis.This study provides a reference for the efficient use of ULS data in forest resource monitoring.关键词
单木分割/单木参数/激光雷达/无人机/点云Key words
individual tree segmentation/individual tree parameters/light detectionand ranging(LiDAR)/unmanned aerial vehicle(UAV)/point cloud分类
农业科技引用本文复制引用
练一宁,卢昊,淮永建,徐海峰,霍朗宁,王智超..点云语义引导的无人机激光雷达单木分割与参数估算[J].林业科学,2026,62(4):106-117,12.基金项目
国家重点研发计划项目(2023YFC3304000) （2023YFC3304000）
国家自然科学基金项目(42001376). （42001376）
