Estimation of Aboveground Biomass of Individual Trees by Backpack LiDAR Based on Parameter-Optimized Quantitative Structural Models (AdQSM)
文献类型： 外文期刊
作者： Ruhan, A. 1 ; Du, Wala 3 ; Ying, Hong 1 ; Wei, Baocheng 1 ; Shan, Yu 1 ; Dai, Haiyan 5 ;
作者机构： 1.Inner Mongolia Normal Univ, Coll Geog Sci, Hohhot 010022, Peoples R China
2.Inner Mongolia Normal Univ, Inner Mongolia Key Lab Remote Sensing & Geog Infor, Hohhot 010022, Peoples R China
3.Chinese Acad Agr Sci, Grassland Res Inst, Hohhot 010022, Peoples R China
4.Res Stn Inner Mongolia Autonomous Reg, Arshan Forest & Grassland Disaster Prevent & Mitig, Arshan 137400, Peoples R China
5.Inner Mongolia Ecol & Agr Meteorol Ctr, Hohhot 010051, Peoples R China
关键词： backpack LiDAR; aboveground biomass; quantitative structure models; nondestructive estimation
期刊名称：FORESTS （ 影响因子：2.9； 五年影响因子：3.0 ）
ISSN：
年卷期： 2023 年 14 卷 3 期
页码：
收录情况： SCI
摘要： Forest aboveground biomass (AGB) plays a key role in assessing forest productivity. In this study, we extracted individual tree structural parameters using backpack LiDAR, assessed their accuracy using terrestrial laser scanning (TLS) data and field measurements as reference values, and reconstructed 3D models of trees based on parameter-optimized quantitative structural models (AdQSM). The individual tree AGB was estimated based on individual tree volumes obtained from the tree model reconstruction, combined with the basic wood density values of specific tree species. In addition, the AGB calculated using the allometric biomass models was validated to explore the feasibility of nondestructive estimation of individual tree AGB by backpack LiDAR. We found that (1) the backpack LiDAR point cloud extracted individual tree diameter at breast height (DBH) with high accuracy. In contrast, the accuracy of the tree height extraction was low; (2) the optimal parameter values of the AdQSM reconstruction models for Larix gmelinii and Betula platyphylla were HS = 0.4 m and HS = 0.6 m, respectively; (3) the individual tree AGB estimated based on the backpack LiDAR and AdQSM fit well with the reference values. Our study confirms that backpack LiDAR can nondestructively estimate individual tree AGB, which can provide a reliable basis for further forest resource management and carbon stock estimation.
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