Improvement of Treetop Displacement Detection by UAV-LiDAR Point Cloud Normalization: A Novel Method and A Case Study

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成果类型：

期刊论文

作者：

Ma, Kaisen;Li, Chaokui;Jiang, Fugen;Xu, Liangliang;Yi, Jing;...

通讯作者：

Hua Sun

作者机构：

[Xu, Liangliang; Ma, Kaisen; Jiang, Fugen; Yi, Jing; Sun, Hua] Cent South Univ Forestry & Technol, Res Ctr Forestry Remote Sensing & Informat Engn, Changsha 410004, Peoples R China.

[Xu, Liangliang; Ma, Kaisen; Jiang, Fugen; Yi, Jing; Sun, Hua] Key Lab Forestry Remote Sensing Based Big Data & E, Changsha 410004, Peoples R China.

[Xu, Liangliang; Ma, Kaisen; Jiang, Fugen; Yi, Jing; Sun, Hua] Key Lab Natl Forestry & Grassland Adm Forest Resou, Changsha 410004, Peoples R China.

[Li, Chaokui] Hunan Univ Sci & Technol, Natl Local Joint Engn Lab Geo Spatial Informat Tec, Xiangtan 411100, Peoples R China.

[Huang, Heqin] Hunan Software Vocat & Tech Univ, Architectural Engn Inst, Xiangtan 411100, Peoples R China.

通讯机构：

[Hua Sun] R

Research Center of Forestry Remote Sensing & Information Engineering, Central South University of Forestry and Technology, Changsha 410004, China<&wdkj&>Key Laboratory of National Forestry & Grassland Administration on Forest Resources Management and Monitoring in Southern Area, Changsha 410004, China<&wdkj&>Key Laboratory of Forestry Remote Sensing Based Big Data & Ecological Security for Hunan Province, Changsha 410004, China<&wdkj&>Author to whom correspondence should be addressed.

语种：

英文

关键词：

UAV-LiDAR;forest remote sensing;normalized point cloud;individual tree detection;treetop displacement

期刊：

Drones

ISSN：

2504-446X

年：

2023

卷：

期：

页码：

262-

DOI：

10.3390/drones7040262

基金类别：

Conceptualization and methodology, H.S. and K.M.; validation, K.M. and F.J.; formal analysis, K.M.; investigation, K.M., F.J., L.X., J.Y., H.H. and H.S.; draft, K.M., C.L. and H.S.; supervision, C.L. and H.S.; review, editing, and revision, K.M., C.L. and H.S.; funding acquisition, K.M., C.L and H.S. All authors have read and agreed to the published version of the manuscript. This research is supported by the Hunan Provincial Natural Science Foundation of China (2020JJ1003 and 2022JJ30078) and the Natural Science Foundation of China (31971578 and 42171418).

机构署名：

本校为第一机构

院系归属：

林学院

摘要：

Normalized point clouds (NPCs) derived from unmanned aerial vehicle-light detection and ranging (UAV-LiDAR) data have been applied to extract relevant forest inventory information. However, detecting treetops from topographically normalized LiDAR points is challenging if the trees are located in steep terrain areas. In this study, a novel point cloud normalization method based on the imitated terrain (NPCIT) method was proposed to reduce the effect of vegetation point cloud normalization on crown deformation in regions with high slope gradients, and the ability of the treetop detection displac...

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Improvement of Treetop Displacement Detection by UAV-LiDAR Point Cloud Normalization: A Novel Method and A Case Study

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