文献类型：会议论文

英文题名：INDIVIDUAL TREE CROWN SEGMENTATION IN SUBTROPICAL BROADLEAF FORESTS USING UAV-BASED ULTRAHIGH-RESOLUTION RGB DATA

作者：Zhu, Ruoning[1] Chai, Guoqi[2] Tian, Xin[3]

第一作者：Zhu, Ruoning

通信作者：Zhu, RN[1]

机构：[1]China Construct First Grp, Construct CO LTD 3, Beijing 100161, Peoples R China;[2]Beijing Forestry Univ, Coll Forestry, Beijing 100083, Peoples R China;[3]Chinese Acad Forestry, Inst Forest Resource Informat Tech, Beijing 100091, Peoples R China

会议论文集：IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

会议日期：JUL 07-12, 2024

会议地点：Athens, GREECE

语种：英文

外文关键词：tree crown segmentation; subtropical broadleaf forests; watershed segmentation; normalized cut

年份：2024

摘要：Rapid and accurate extraction of individual tree crown information is the basis for fine investigation and scientific management of forest resources. However, in subtropical broad-leaved forests, the crown contains multiple tree apexes, and the commonly used watershed segmentation algorithms have different degrees of over-segmentation. In this study, we propose an individual-tree segmentation method with watershed segmentation combined with spectral-texture-intensity-controlled normalized cutting, which directly utilizes the DSM and DOM data generated from the high-resolution images of unmanned aerial vehicles (UAVs). The effectiveness of our method for individual-tree crown segmentation was verified in a subtropical broadleaf forest in southern China (F=0.87, R=0.93, P=0.82). The results show that our method can reduce the over-segmentation of watershed segmentation and provide an efficient and low-cost new method for crown information extraction in complex forest environments.