林业科学2026，Vol.62Issue(8)：11-20,10.DOI:10.11707/j.1001-7488.LYKX20250679
基于UAV-LiDAR的长白落叶松人工林单木断面积生长量估测模型研建
Development of a Basal Area Growth Estimation Model for Individual Trees of Larix olgensis Plantations based on UAV-LiDAR Data
摘要
Abstract
[Objective]This study aims to construct a breast height basal area increment(BAI)estimation model for individual trees of Larix olgensis plantations by using high-density UAV-LiDAR data,in order to evaluate the application potential of UAV-LiDAR in individual tree growth modeling.[Method]The study was conducted in L.olgensis plantations with various ages,densities,and site conditions in Mengjiagang Forest Farm in Heilongjiang Province.The crown structure and competition indices derived from UAV-LiDAR data served as primary variables,integrated with BAI data obtained from 147 stem-analyzed trees.A modeling method based on correlation analysis,forward stepwise regression,collinearity diagnostics,and mixed-effects model was employed to develop an UAV-LiDAR-based individual tree growth model.A field-measurement-based model was also constructed for comparison.Predictive accuracy of the two models was evaluated and compared using 10-fold cross-validation.[Result]There were significant correlations between the UAV-LiDAR-derived canopy competition and crown structure variables and BAI.Among them,the light competition index(LCI)and exposed crown surface area(ECA)were the highest correlated variables of competition and canopy structure,respectively,outperforming traditional field-measured diameter at breast height and competition indices.The UAV-LiDAR-based individual BAI estimation model achieved a satisfactory goodness-of-fit,with adjusted coefficient of determination(R2a)of 0.846 and a root mean square error(RMSE)of 1.35 cm2·a-1.The results of cross validation showed that the UAV-LiDAR-based model possessed good robustness and predictive capability,yielding a mean absolute error(MAE)of 1.26 cm2·a-1 and a mean absolute percentage error(MAPE)of 25.7%,which were lower than those of the field-measurement-based model.[Conclusion]The uni-temporal UAV-LiDAR data has shown great potential in accurately predicting individual tree growth.Variables entirely derived from UAV-LiDAR can effectively quantify the crown structure and competition mechanisms driving tree growth.The developed model provides a theoretical foundation and technical support for individual tree-level growth prediction and forest management decision-making.关键词
无人机激光雷达/冠层竞争/树冠结构/单木生长量估测模型/长白落叶松人工林Key words
unmanned aerial vehicle light detection and ranging(UAV-LiDAR)/canopy competition/crown structure/individual tree growth model/Larix olgensis plantation分类
农业科技引用本文复制引用
刘鑫,郝元朔,董利虎,赵颖慧,李凤日..基于UAV-LiDAR的长白落叶松人工林单木断面积生长量估测模型研建[J].林业科学,2026,62(8):11-20,10.基金项目
"十四五"国家重点研发计划课题(2023YFD2200802). （2023YFD2200802）
