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Journal of Remote Sensing. 2019, (04) Core

Fine classification of near-ground point cloud based on terrestrial laser scanning and detection of forest fallen woodChinese Full Text

MA Zhenyu;PANG Yong;LI Zengyuan;LU Hao;LIU Luxia;CHEN Bowei;Research Institute of Forest Resource Information Techniques,Chinese Academic of Foresty;

Abstract: Terrestrial Laser Scanning（TLS） can effectively describe complex forest scenes. This study aimed to classify ground point cloud within the height of 1.3 m into ground, vegetation, fallen wood, and standing trunk based on the TLS obtained from fallen wood plots in Daxing’anling. Fallen wood cloud point was segmented and merged. The optimal 3 D neighborhood of each individual point was calculated through the Shannon entropy constructed by linearity, planarity, and scattering to avoid the differenc... More
Keywords：

Terrestrial Laser Scanning（TLS）; point cloud; fallen wood; random forest classification; Random Sample Consensus（RANSAC）;

  • Series：

    (A) Mathematics/ Physics/ Mechanics/ Astronomy; (I) Electronic Technology ＆ Information Science

  • Subject：

    Physical Geography and Topography; Telecom Technology

  • Classification Code：

    TN958.98;P225.2

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