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Delineating tree crowns from airborne laser scanning point cloud data using Delaunay triangulation

机译:使用Delaunay三角剖分从机载激光扫描点云数据中描绘树冠

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摘要

Most algorithms for delineating trees from laser scanning data are pixel-based region growing methods. The algorithm presented in this letter makes use of the original laser points to avoid errors introduced by interpolation. Three different scales are used to identify the seed points or the local maxima at that scale. The seed points are considered to be the estimated tree tops, and are used for growing regions or tree crowns around the seed points. For a test dataset from a Finnish mixed forest and point density of approximately 2 points m~(-2), up to 75% of the reference trees could be identified. At the coarser scales, fewer trees were identified, but the crowns were less fragmented. Further work is required to determine how far the method is applicable in other forest conditions and data with other point densities.
机译:用于从激光扫描数据描绘树木的大多数算法是基于像素的区域生长方法。这封信中介绍的算法利用原始激光点来避免内插法引入的误差。使用三种不同的标度来标识该标度的种子点或局部最大值。种子点被认为是估计的树梢,并用于种子点周围的生长区域或树冠。对于来自芬兰混交林和点密度约为2点m〜(-2)的测试数据集,最多可以识别75%的参考树。在较粗的尺度上,识别出的树木较少,但树冠的碎片较少。需要进一步的工作来确定该方法在其他森林条件和具有其他点密度的数据中的适用范围。

著录项

  • 来源
    《International journal of remote sensing》 |2009年第14期|3843-3848|共6页
  • 作者

    CICI ALEXANDER;

  • 作者单位

    Department of Geography, University of Leicester, University Road, Leicester LE1 7RH, UK;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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