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首页> 外文期刊>IEEE Geoscience and Remote Sensing Letters >Three-Dimensional LiDAR Data Classifying to Extract Road Point in Urban Area
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Three-Dimensional LiDAR Data Classifying to Extract Road Point in Urban Area

机译:三维LiDAR数据分类提取市区道路点

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The Light Detection and Ranging (LiDAR) system is one of the best ways to accurately and effectively gather 3-D terrain information. However, it is complicated to process the LiDAR cloud data due to its irregularity and large number of collected data points. This letter proposes a novel method to automatically extract urban road network from 3-D LiDAR data. This method uses height and reflectance of LiDAR data, and clustered road point information. Geometric information of general roads is also applied to correctly extract road points group. The proposed method has been tested on various urban areas which contain complicated road networks. The results demonstrate that the integration of height, reflectance, and geometric information of roads is a crucial factor that distinguishes the proposed method in its ability to reliably and correctly classify road points.
机译:光检测和测距(LiDAR)系统是准确有效地收集3D地形信息的最佳方法之一。但是,由于LiDAR云数据的不规则性和大量收集的数据点,因此处理起来很复杂。这封信提出了一种从3-D LiDAR数据中自动提取城市道路网的新颖方法。该方法使用LiDAR数据的高度和反射率以及聚集的道路点信息。普通道路的几何信息也可用于正确提取道路点组。所提出的方法已经在包含复杂道路网络的各种城市区域进行了测试。结果表明,道路的高度,反射率和几何信息的集成是区分所提出的方法对道路点进行可靠和正确分类的能力的关键因素。

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