基于人工和激光雷达的橙树冠层体积估算方法

A. Colaço, R. Trevisan, J. Molin, J. R. Rosell-Polo, A. Escolà
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引用次数: 18

摘要

激光雷达(光探测和测距)技术是目前橘子树冠层几何估计的人工方法的替代方案。这项工作的目的是比较不同类型的橙树树冠体积估计,一些是基于人工方法,另一些是基于激光雷达传感器。使用激光扫描系统为25棵单独的树生成点云。测试了凸壳和α形曲面的重建算法。激光雷达衍生模型能够比传统方法更准确地表示橘子树。然而,结果与目前的手工方法有很大的不同。此外,不同的三维建模算法导致了不同的冠层体积估计。因此,需要制定和建立新的标准方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Orange tree canopy volume estimation by manual and LiDAR-based methods
LiDAR (Light detection and ranging) technology is an alternative to current manual methods of canopy geometry estimations in orange trees. The objective of this work was to compare different types of canopy volume estimations of orange trees, some inspired on manual methods and others based on a LiDAR sensor. A point cloud was generated for 25 individual trees using a laser scanning system. The convex-hull and the alpha-shape surface reconstruction algorithms were tested. LiDAR derived models are able to represent orange trees more accurately than traditional methods. However, results differ significantly from the current manual method. In addition, different 3D modeling algorithms resulted in different canopy volume estimations. Therefore, a new standard method should be developed and established.
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