西北农林科技大学学报（自然科学版）2026，Vol.54Issue(9)：14-26,13.DOI:10.13207/j.jnwafu.2026.09.002
基于背包式激光雷达的单木地上生物量估算
Estimation of individual tree aboveground biomass based on backpack LiDAR
摘要
Abstract
[Objective]The study aims to explore the application for extracting forest structural parameters and non-destructive estimation of individual tree aboveground biomass(AGB)using backpack LiDAR and the accurate and detailed quantitative structure model(AdQSM),providing a scientific basis for forest resource sur-veys and carbon stock assessment.[Method]Using the dominant tree species Larix gmelinii and Betula platy-phylla in the natural secondary birch forests of Greater Khingan Mountains of Inner Mongolia as the research subjects,point cloud data was acquired via backpack LiDAR.Individual trees were segmented from the point clouds,and their segmentation accuracy along with the extraction accuracy of diameter at breast height(DBH)and tree height were evaluated against field measurement data as reference values.Based on the AdQSM model,three-dimensional reconstruction of individual tree point clouds was performed.Optimal modeling parameters(height segmentation HS)were determined through parameter optimization.The extracted DBH,tree height,stem volume,and branch volume were applied to estimate biomass of tree components and AGB,using conversion factor method and biomass modeling method,respectively.The estimation accuracy of the two methods was evaluated based on the coefficient of determination(R²)and root mean square error(RMSE)across multiple di-mensions-different tree species,diameter classes,tree height,and stand density.[Result]①The overall accu-racy for individual tree segmentation was F=0.96.The backpack LiDAR exhibited high accuracy in extracting diameter at breast height(DBH),with an average coefficient of determination(R²)of 0.98 and an average root mean square error(RMSE)of 0.60 cm.However,its accuracy in tree height extraction was lower,with an aver-age R² of 0.60 and an average RMSE of 2.22 m.②The optimal parameter for the AdQSM model reconstruc-tion of both L.gmelinii and B.platyphylla was HS=0.4 m.③The biomass model method demonstrated supe-rior accuracy in estimating organ biomass compared to the conversion factor method.Specifically,trunk biomass estimated with higher precision(B.platyphylla:R²=0.96,RMSE=8.13 kg/plant;L.gmelinii:R²=0.94,RMSE=14.54 kg/plant),whereas branch biomass estimation exhibited lower accuracy(B.platyphylla:R²=0.94,RMSE=3.29 kg/plant;L.gmelinii R²=0.93,RMSE=2.47 kg/plant).Both methods accurately esti-mated the aboveground biomass(AGB)of individual L.gmelinii and B.platyphylla trees(R²≥0.92 for both,RMSE ranging from 13.14 to 18.47 kg/plant).For large-diameter trees(≥15 cm),tall trees(≥11 m),and plots of the two different density(low and high),both methods yielded accurate AGB estimates(maximum R²=0.94),while the conversion factor method performed better for small-diameter(<15 cm)trees and short trees(<11 m).[Conclusion]Backpack LiDAR systems can effectively capture individual tree structural para-meters.The AdQSM model based on the point cloud data enables non-destructive and efficient estimation of in-dividual tree above-ground biomass(AGB),providing a valuable reference for forest resource surveys and car-bon stock research.关键词
单木生物量估算/背包式激光雷达/定量结构模型/兴安落叶松/白桦Key words
individual tree biomass estimation/backpack-LiDAR/accurate and detailed quantitative struc-ture model/Larix gmelinii/Betula platyphylla分类
农业科技引用本文复制引用
萨如拉,塔娜,张昊,王雨峰,郝帅,翟凯涛,滑永春,张欣..基于背包式激光雷达的单木地上生物量估算[J].西北农林科技大学学报（自然科学版）,2026,54(9):14-26,13.基金项目
国家自然科学基金项目(32460388) （32460388）
内蒙古自治区自然科学基金面上项目(2023MS03051) （2023MS03051）
