文献类型：期刊文献

英文题名：A framework for precisely thinning planning in a managed pure Chinese fir forest based on UAV remote sensing

作者：Zhou, Pan[1,2,3] Sun, Zhibin[4] Zhang, Xiongqing[5] Wang, Yixiang[1,2,3,6]

第一作者：Zhou, Pan

通信作者：Wang, YX[1]

机构：[1]Zhejiang A&F Univ, State Key Lab Subtrop Silviculture, Hangzhou 311300, Zhejiang, Peoples R China;[2]Zhejiang A&F Univ, Key Lab Carbon Cycling Forest Ecosyst & Carbon Seq, Hangzhou 311300, Zhejiang, Peoples R China;[3]Zhejiang A&F Univ, Coll Environm & Resource Sci, Hangzhou 311300, Zhejiang, Peoples R China;[4]Nanjing Normal Univ, Sch Math Sci, Jiangsu Key Lab Numer Simulat Large Scale Complex, Nanjing 210046, Jiangsu, Peoples R China;[5]Chinese Acad Forestry, Res Inst Forestry, Beijing 100091, Peoples R China;[6]Zhejiang A&F Univ, Coll Environm & Resource Sci, Hangzhou 311300, Peoples R China

年份：2023

卷号：860

外文期刊名：SCIENCE OF THE TOTAL ENVIRONMENT

收录：;EI(收录号：20224913215749);Scopus(收录号：2-s2.0-85143275420);WOS:【SCI-EXPANDED(收录号:WOS:000919426900001)】；

基金：This research was supported by the National Key Research and Develop- ment Program of China (2021YFD2201304) , the Key Research and Develop- ment Program of Zhejiang Province (2021C02005) and the Overseas Expertise Introduction Project for Discipline Innovation (111 Project D18008) .

语种：英文

外文关键词：Thinning; Unmanned aerial vehicle; Remote sensing; Individual tree; Forest management

摘要：Where and how many trees should be thinned in a pure managed forest to improve forest quality and increase ecolog-ical benefits are important forest questions. In this study we address such challenges by providing a novel framework for planning thinning operations through Unmanned Aerial Vehicle (UAV) remote sensing techniques, which can not only obtain forest attributes of its entire stand with spatial properties, but also optimize the selection of thinning areas, thinning intensities and cut-trees. This study helps to reduce the costs of time-consuming and laborious ground inves-tigations. The framework was demonstrated by applying it into a subtropical Chinese fir plantation in southeastern China. Results showed that RGB images acquired by a low-cost UAV have great potential in depicting forest structure. The overall accuracy of the individual tree detection in the case study was 85.19 % +/- 0.48 %. The overall accuracy and the intersection over union of the non-crown area extraction were 94.94 % and 82.65 %, respectively. For the two determined thinning areas, 19.5 % and 14.3 % crown density were required to thin in the primary and secondary re-gions, respectively. In addition, the top-down perspective of UAV remote sensing makes up for the limitations of the bottom-up perspective of traditional forestry. The framework can act as a basic model for forest managers to modify and expand for customizing detailed thinning guidelines.