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A hierarchical approach to the segmentation of single dominant and dominated trees in forest areas by using high-density LiDAR data

机译:使用高密度LiDAR数据的森林区域中单个优势树和优势树的分层方法

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In this paper we present a hierarchical approach to the segmentation of high-density LiDAR data which aims to automatically detect and delineate the single tree crowns of both the dominant and the dominated layers of the forest. First, we detect the dominant tree crowns by using both the image derived from the LiDAR data and the LiDAR point cloud. Hence, the detected crowns are delineated directly in the LiDAR point cloud by means of a radial angular analysis. Second, the dominated crowns are detected by analyzing the vertical profile of the dominant trees. Finally, we extract the dominated trees, thus reconstructing the structure of the forest. Experiments carried out in a forest area located in the Southern Italian Alps by using very high density LiDAR data (up to 50 points/m) point out the effectiveness of the proposed approach.
机译:在本文中,我们提出了一种分层方法来分配高密度LIDAR数据的分割,旨在自动检测和描绘森林的主导层和主导层的单树冠。首先,我们通过使用源自激光雷达数据和激光雷云的图像来检测主导树冠。因此,通过径向角度分析,检测到的冠部直接在激光脉点云中描绘。其次,通过分析显性树木的垂直轮廓来检测主导的冠。最后,我们提取主导的树木,从而重建森林的结构。通过使用非常高密度的LIDAR数据(最多50分)指出所提出的方法的有效性,在位于意大利南部阿尔卑斯山南部的森林区域进行实验。

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