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A method to obtain orange crop geometry information using a mobile terrestrial laser scanner and 3D modeling

机译:一种使用移动地面激光扫描仪和3D建模获得橙色作物几何信息的方法

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摘要

LiDAR (Light Detection and Ranging) technology has been used to obtain geometrical attributes of tree crops in small field plots, sometimes using manual steps in data processing. The objective of this study was to develop a method for estimating canopy volume and height based on a mobile terrestrial laser scanner suited for large commercial orange groves. A 2D LiDAR sensor and a GNSS (Global Navigation Satellite System) receiver were mounted on a vehicle for data acquisition. A georeferenced point cloud representing the laser beam impacts on the crop was created and later classified into transversal sections along the row or into individual trees. The convex-hull and the alpha-shape reconstruction algorithms were used to reproduce the shape of the tree crowns. Maps of canopy volume and height were generated for a 25 ha orange grove. The different options of data processing resulted in different values of canopy volume. The alpha-shape algorithm was considered a good option to represent individual trees whereas the convex-hull was better when representing transversal sections of the row. Nevertheless, the canopy volume and height maps produced by those two methods were similar. The proposed system is useful for site-specific management in orange groves.
机译:LiDAR(光检测和测距)技术已被用于获取小田地中树木作物的几何属性,有时在数据处理中使用手动步骤。这项研究的目的是开发一种适用于大型商业橘园的基于地面移动激光扫描仪的冠层体积和高度估算方法。将2D LiDAR传感器和GNSS(全球导航卫星系统)接收器安装在车辆上以进行数据采集。创建了代表激光束对农作物的撞击的地理参考点云,随后将其分类为沿行的横向部分或单个树。凸包和alpha形状重建算法用于复制树冠的形状。绘制了一个25公顷的橘树林的冠层体积和高度图。数据处理的不同选项导致冠层体积的值不同。 alpha形状算法被认为是表示单个树的好选择,而凸包在表示行的横向部分时更好。但是,通过这两种方法生成的树冠体积和高度图是相似的。所提出的系统对于橘园的特定地点管理非常有用。

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