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Stem and branch volume estimation using terrestrial laser scanning data

  • role： First author第一作者
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Beijing Normal University, Beijing 100875, China

  • Email：jinshuangna@mail.bnu.edu.cn
  • Introduction：靳双娜，研究方向为激光雷达林业应用。E-mail： jinshuangna@mail.bnu.edu.cn
JIN Shuangna1,  
  • role： Corresponding author通信作者
  • Affiliation：

    School of Geospatial Engineering and Science, Sun Yat-sen University, Zhuhai 519082, China

    Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519080, China

  • Email：zhangwm25@mail.sysu.edu.cn
  • Introduction：张吴明，研究方向为激光雷达（LiDAR）点云处理、三维信息数字化、多传感器信息融合及遥感信息处理及遥感反演。E-mail： zhangwm25@mail.sysu.edu.cn
ZHANG Wuming23*,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Beijing Normal University, Beijing 100875, China

CAI Shangshu1,  
  • Affiliation：

    School of Geospatial Engineering and Science, Sun Yat-sen University, Zhuhai 519082, China

SHAO Jie2,  
  • Affiliation：

    Saihanba Mechanical Forest Farm, Chengde 068466, China

CHENG Shun4,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Beijing Normal University, Beijing 100875, China

XIE Donghui1,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Beijing Normal University, Beijing 100875, China

YAN Guangjian1

Resümee

Tree volume is an important parameter in forest inventory. The reconstruction of the Quantitative Structure Model of Trees (TreeQSM) method based on ground-based LiDAR point clouds can achieve nondestructive acquisition of forest volume. It can also solve the time-consuming and labor-intensive problem of traditional forest in situ investigation. However, the reference volume of the felled timber is difficult to obtain. Thus, the ability of the TreeQSM volume estimation has not been studied at the stem and different branch orders. Moreover, TreeQSM is only applied to the ground-based LiDAR point cloud collected at the tree level but not at the plot level. Therefore, this study proposes to assess the stem and branch volume estimation of TreeQSM from the point cloud collected from the tree and plot levels.In this study, we evaluate the stem and branch volume estimated by TreeQSM using TLS point cloud at the tree and plot levels:(1) Estimating the volume of stem and branch at different orders based on TLS scanning at the tree-level.(2) Estimating and comparing the volume of stem and branch at different orders based on TLS point cloud at the tree and plot levels.(3) Exploring the influence of stand density on the estimation of stem and branch volumes using the TLS point cloud at the plot level.The experimental results showed that the stem and first-order branch volume can be effectively estimated from the point cloud collected from the tree and plot levels. However, the volume estimation of the secondary branch has obvious deviations. At the plot level, the accuracy of the stem and whole tree volume is equivalent to that of the tree level. The deviations are approximately 5% and 10%. However, the first-order branch volume estimation deviation is slightly large, approximately 10% and 15% at the tree and plot levels, respectively. In addition, the stand density is negatively correlated with the accuracy of volume estimation at the plot level. In the low forest density (425, 625, and 925 plants/ha), the stem volume estimation error is within 5%, and the first-order branch volume estimation error is approximately 15%. In addition, the estimation deviations of the total volume in the plot are affected by the partial neutralization effect of the underestimation of the stem and the first-order branch volume and the overestimation of the secondary branch volume. These deviations are all approximately 10%. Thus, it can well estimate the tree stem, first-order branch, and whole tree volumes at the plot level in forests with a low stand density.

Schlüsselwort

volume;Stem and branch volume;Quantitative Structure Model (QSM);TLS;plot level

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