[an error occurred while processing this directive] 世界地质 2018, 37(4) 1265-1273 DOI:   10.3969/j.issn.1004-5589.2018.04.027  ISSN: 1004-5589 CN: 22-1111/P

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LiDAR
分类
滤波
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孙嘉悦
张旭晴
牛雪峰
PubMed
Article by Sun J
Article by Zhang X
Article by Niu X
基于LiDAR点云数据的低矮植被分类方法
孙嘉悦, 张旭晴, 牛雪峰
吉林大学地球探测科学与技术学院, 长春 130026
摘要: 基于LiDAR点云数据进行小区域低矮植被分类方法的研究,利用渐进加密三角网算法分离地面点与低矮植被点,通过分析调整阈值对分离效果的影响验证该算法的适用程度。本文研究表明渐进加密三角网算法适用于低矮植被分布多的地势平坦地区,不适用于地形起伏较大的山区与城市地区。
关键词 LiDAR   分类   滤波  
Low vegetation classification based on LiDAR point cloud data
SUN Jia-yue, ZHANG Xu-qing, NIU Xue-feng
College of Geo-exploration Science and Technology, Jilin University, Changchun 130026, China
Abstract: Based on the LiDAR point cloud data, the research on the method of low-level vegetation isolation in small area is carried out. The ground points and the low vegetation points are separated using the progressive cryptographic triangulation algorithm. The application of the algorithm is verified by analyzing the effect of adjusting the threshold on the separation effect. The result shows that the progressive cryptographic triangulation algorithm is suitable for flat areas with wide distribution of low vegetation but not suitable for mountainous areas and urban areas with large terrain fluctuations.
Keywords: LiDAR   classification   filtering  
收稿日期 2018-01-22 修回日期 2018-09-30 网络版发布日期  
DOI: 10.3969/j.issn.1004-5589.2018.04.027
基金项目:

国家自然科学基金面上项目(41472243).

通讯作者: 牛雪峰(1970-),男,教授,硕士生导师,主要从事测量学,摄影测量学方面的研究工作.E-mail:niuxf@jlu.edu.cn
作者简介:
作者Email: niuxf@jlu.edu.cn

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