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CHEN Siyu, LIU Xianzhao, WANG Yixiang, LIANG Dan. Individual tree detection in high canopy density Larix principis-rupprechtii plantation based on airborne LiDAR[J]. Journal of Zhejiang A&F University. doi: 10.11833/j.issn.2095-0756.20210399
Citation: CHEN Siyu, LIU Xianzhao, WANG Yixiang, LIANG Dan. Individual tree detection in high canopy density Larix principis-rupprechtii plantation based on airborne LiDAR[J]. Journal of Zhejiang A&F University. doi: 10.11833/j.issn.2095-0756.20210399

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Individual tree detection in high canopy density Larix principis-rupprechtii plantation based on airborne LiDAR

doi: 10.11833/j.issn.2095-0756.20210399
  • Received Date: 2021-05-31
  • Accepted Date: 2022-03-25
  • Rev Recd Date: 2022-03-25
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

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Individual tree detection in high canopy density Larix principis-rupprechtii plantation based on airborne LiDAR

doi: 10.11833/j.issn.2095-0756.20210399

Abstract:   Objective  With low identification accuracy of individual trees in Larix principis-rupprechtii forest with high canopy density employing high resolution images, this paper is aimed to confirm the strengths of airborne Laser Detection and Ranging (LiDAR) 3D point cloud data as an alternative with a workable method proposed.   Method  Based on the preprocessing of point cloud data, an improved Mean Shift with Gaussian kernel function (MSP) position recognition method on the basis of the spatial characteristics of airborne LiDAR point cloud was proposed. The comparison is made with other three commonly used methods: regional growing segmentation algorithm based on point cloud (RGP), local maximum method based on canopy height model (LMC) and multi-scale segmentation method based on CHM (MSC).   Result  Identification accuracy of the four methods is: MSP (89.30%)>LMC (85.60%)>RGP (77.50%)>MSC (70.00%) and MSC, the proposed method, displayed high average individual tree crown extraction accuracy (90.18%) and relatively low omission error and commission error rate: 8.7% and 8.0% respectively.   Conclusion  The proposed MSP has good applicability in high crown density L. principis-rupprechtii forest and provides a new way of extracting L. principis-rupprechtii forest structure parameters accurately on the basis of airborne LiDAR point clouds. [Ch, 3 fig. 3 tab. 28 ref.]

CHEN Siyu, LIU Xianzhao, WANG Yixiang, LIANG Dan. Individual tree detection in high canopy density Larix principis-rupprechtii plantation based on airborne LiDAR[J]. Journal of Zhejiang A&F University. doi: 10.11833/j.issn.2095-0756.20210399
Citation: CHEN Siyu, LIU Xianzhao, WANG Yixiang, LIANG Dan. Individual tree detection in high canopy density Larix principis-rupprechtii plantation based on airborne LiDAR[J]. Journal of Zhejiang A&F University. doi: 10.11833/j.issn.2095-0756.20210399
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