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Simulation of multi-platform LiDAR for assessing total leaf area in tree crowns

机译:用于评估树冠中总叶面积的多平台激光器的仿真

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摘要

LiDAR (Light Detection and Ranging) technology has been increasingly implemented to assess the biophysical attributes of forest canopies. However, LiDAR-based estimation of tree biophysical attributes remains difficult mainly due to the occlusion of vegetative elements in multi-layered tree crowns. In this study, we developed a new algorithm along with a multiple-scan methodology to analyse the impact of occlusion on LiDAR-based estimates of tree leaf area. We reconstructed five virtual tree models using a computer graphic-based approach based on in situ measurements from multiple tree crowns, for which the position, size, orientation and area of all leaves were measured. Multi-platform LiDAR simulations were performed on these 3D tree models through a point-line intersection algorithm. An approach based on the Delaunay triangulation algorithm with automatic adaptive threshold selection was proposed to construct the scanned leaf surface from the simulated discrete LiDAR point clouds. In addition, the leaf area covered by laser beams in each layer was assessed in combination with the ratio and number of the scanned points. Quantitative comparisons of LiDAR scanning for the occlusion effects among various scanning approaches, including fixed-position scanning, multiple terrestrial LiDAR scanning and airborne-terrestrial LiDAR cross-scanning, were assessed on different target trees. The results showed that one simulated terrestrial LiDAR scan alongside the model tree captured only 25-38% of the leafarea of the tree crown. When scanned data were acquired from three simulated terrestrial LiDAR scans around one tree, the accuracy of the leaf area recovery rate reached 60-73% depending on the leaf area index, tree crown volume and leaf area density. When a supplementary airborne LiDAR scanning was included, occlusion was reduced and the leaf area recovery rate increased to 72-90%. Our study provides an approach for the measurement of total leaf area in tree crowns from simulated multi-platform LiDARdata and enables a quantitative assessment of occlusion metrics for various tree crown attributes under different scanning strategies.
机译:LIDAR(光探测和测距)技术越来越多地实施以评估森林檐篷的生物物理属性。然而,基于激光的树木生物物理属性的估计仍然是困难的,主要是由于多层树冠中的植被元素的闭塞。在本研究中,我们开发了一种新的算法以及多扫描方法,分析了闭塞对基于LiDAR的树叶区域估计的影响。我们使用基于计算机图形的方法重建了五个虚拟树模型,该方法基于多个树冠的原位测量,测量所有叶子的位置,尺寸,方向和面积。通过点线交叉点算法对这些3D树模型进行多平台激光乐轨模拟。提出了一种基于具有自动自适应阈值选择的Delaunay三角测量算法的方法来构造模拟离散激光脉冲云的扫描叶面。另外,每层激光束覆盖的叶面积与扫描点的比例和数量组合评估。在不同的靶树上评估了各种扫描方法中的遮挡效应LIDAR扫描的定量比较,包括固定位置扫描,多个陆地激光扫描和空气传播的跨扫描。结果表明,一个模拟的地面激光雷达扫描旁边的模型树仅捕获了树冠的叶拉叶的25-38%。当从一棵树周围的三个模拟的地面激光扫描获取扫描数据时,叶面积回收率的准确性取决于叶面积指数,树冠体积和叶面积密度达到60-73%。当包括补充空气传播激光雷达扫描时,减少闭塞,叶面积回收率增加到72-90%。我们的研究提供了一种测量来自模拟多平台LIDARDATA的树冠中的总叶面积的方法,并在不同扫描策略下实现各种树冠属性的遮挡度量的定量评估。

著录项

  • 来源
    《Agricultural and Forest Meteorology》 |2019年第2019期|共10页
  • 作者

    Ting Yun; Lin Cao; Feng An;

  • 作者单位

    School of information Science and Technology Nanjing Forestry University Nanjing 210037 China;

    Co-Innovation Centre for Sustainable Forestry in Southern China Nanjing Forestry University Nanjing 210037 China;

    Danzhou Investigation and ExperimentStation of Tropical Crops Ministry of Agriculture Rubber Research Institute Chinese Academy of Tropical Agricultural Sciences Danzhou 571737 China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 农业基础科学;
  • 关键词

    Laser scanning; LiDAR; Leaf area; Occlusion effect; Computer graphics;

    机译:激光扫描;LIDAR;叶面积;闭塞效应;计算机图形;

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