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| 基于背包式激光雷达的单木地上生物量估算 |
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萨如拉1, 塔娜1, 张昊1, 王雨峰1, 郝帅1,2, 翟凯涛1, 滑永春1, 张欣1
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1.内蒙古农业大学 林学院，内蒙古 呼和浩特 010019;2.内蒙古大兴安岭森林生态系统国家野外科学观测研究站，内蒙古 根河 022350
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| 摘要: |
| 【 目的】探索背包式激光雷达与树木定量结构模型（accurate and detailed quantitative qtructure model，AdQSM）在森林结构参数提取及单木地上生物量（aboveground biomass，AGB）无损估测中的应用，为森林资源调查与碳储量评估提供科学依据。【 方法】以内蒙古大兴安岭白桦天然次生林中的优势树种兴安落叶松（Larix gmelinii）与白桦（Betula platyphylla）为研究对象，采用背包式激光雷达获取点云数据，对点云进行单木分割，以野外实测数据为参考值评估其分割精度及胸径、树高的提取精度。基于AdQSM模型对单木点云进行三维重建，通过参数优化确定最佳建模参数分割高度（height segmentation，HS），将提取的胸径、树高、树干材积及树枝材积分别采用转换因子法与生物量模型法估算单木各器官生物量和 AGB，并从不同树种、不同径阶、不同树高及不同林分密度等多个维度，利用决定系数（R2）和均方根误差（RMSE）对两种方法的估算精度进行评价。【 结果】①单木分割总体精度F=0.96。背包式激光雷达提取的胸径精度较高，决定系数（R2）平均值为0.98，均方根误差（RMSE）平均值为0.60 cm，而树高的提取精度较低，R2平均值为0.60，RMSE平均值为2.22 m；②兴安落叶松和白桦AdQSM模型重建的最优参数HS=0.4 m；③生物量模型法估算各器官生物量的精度优于转换因子法。其中树干生物量估算精度较高（白桦R2=0.96，RMSE=8.13 kg/株；兴安落叶松R2=0.94，RMSE=14.54 kg/株），树枝生物量估算精度较低（白桦R2=0.94，RMSE=3.29 kg/株；兴安落叶松R2=0.93，RMSE=2.47 kg/株）。两种方法均能准确估算兴安落叶松和白桦单木 AGB（R2均大于等于0.92，RMSE介于13.14~18.47 kg/株）。大径阶（≥15 cm）、高大样木（≥11 m）和两种不同密度（低密度和高密度）样地采用两种方法均能获取准确的AGB估算结果（R2最高达0.94），而小径阶（<15 cm）、低矮木（<11 m）使用转换因子法更优。【 结论】背包式激光雷达可以有效获取单木结构参数，基于点云数据构建的AdQSM模型可以实现单木AGB的无损、高效估算，可为森林资源调查和碳储量研究提供参考。 |
| 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 |
| DOI：10. 13207/j. jnwafu. 2026. 09. 002 |
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| 基金项目:国家自然科学基金项目（32460388）；内蒙古自治区自然科学基金面上项目（2023MS03051） |
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| Estimation of individual tree aboveground biomass based on backpack LiDAR |
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SA Rula1, TA Na1, ZHANG Hao1, WANG Yufeng1, HAO Shuai1,2, ZHAI Kaitao1, HUA Yongchun1, ZHANG Xin1
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1.Forestry College，Inner Mongolia Agricultural University，Hohhot，Inner Mongolia 010019，China;2.National Field Scientific Observation and Research Station of Forest Ecosystem in Greater Khingan Mountains，Genhe，Inner Mongolia 022350，China
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| 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 platyphylla 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 dimensions-different tree species，diameter classes，tree height，and stand density.【Result】①The overall accuracy 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 average R2 of 0. 60 and an average RMSE of 2. 22 m. ②The optimal parameter for the AdQSM model reconstruction of both L. gmelinii and B.platyphylla was HS=0.4 m. ③ The biomass model method demon?strated superior 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 estimated 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 parameters. The AdQSM model based on the point cloud data enables non-destructive and efficient estimation of individual tree above-ground biomass（AGB），providing a valuable reference for forest resource surveys and carbon stock research. |
| Key words: individual tree biomass estimation backpack-LiDAR accurate and detailed quantitative struc⁃ture model Larix gmelinii Betula platyphylla |
