Integrating terrestrial laser scanning and unmanned aerial vehicle photogrammetry to estimate individual tree attributes in managed coniferous forests in Japan

编号 030033603

推送时间 20220328

研究领域 森林经理 

年份 2022 

类型 期刊 

语种 英语

标题 Integrating terrestrial laser scanning and unmanned aerial vehicle photogrammetry to estimate individual tree attributes in managed coniferous forests in Japan

来源期刊 INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION

期 第336期

发表时间 20211221

关键词 Structure from Motion;  Planted forestIntegration;  UAV; 

摘要 The accurate estimation of tree attributes is essential for sustainable forest management. Terrestrial Laser Scanning (TLS) is a viable remote sensing technology suitable for estimating under canopy structure. However, TLS measurements generally underestimate tree height in taller trees, which leads to the underestimation of other tree attributes (e.g., stem volume). The integration of information derived from TLS and Unmanned Aerial Vehicle (UAV) photogrammetry could potentially improve tree height estimation. This study investigated the applicability of integrating TLS and UAV photogrammetry to estimate individual tree attributes in managed coniferous forests of Japan. Diameter at breast height (DBH), tree height, and stem volume were estimated by (1) TLS data only, (2) integrating TLS and UAV data with TLS tree locations, and (3) integrating TLS and UAV data with treetop detections of the tree canopy. The TLS data only approach achieved high accuracy for DBH estimations with a root mean squared error (RMSE) of 2.36 cm (RMSE% 5.6%); however, tree height was greatly underestimated, with an RMSE of 8.87 m (28.9%) and a bias of -8.39 m. Integrating TLS and UAV photogrammetric data improved tree height estimation accuracy for both the TLS tree location (RMSE of 1.89 m and a bias of -0.46 m) and the treetop detection (RMSE of 1.77 m and a bias of 0.36 m) approaches. Integrating TLS and UAV photogrammetric data also improved the accuracy of the stem volume estimations with RMSEs of 0.21 m(3) (10.8%) and 0.21 m(3) (10.5%) for the TLS tree location and treetop detection approaches, respectively. Although the tree height of suppressed trees tended to be overestimated by TLS and UAV photogrammetric data integration, a good performance was obtained for dominant trees. The results of this study indicate that the integration of TLS and UAV photogrammetry is beneficial for the accurate estimation of tree attributes in coniferous forests.

服务人员 付贺龙

服务院士 唐守正

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