测绘通报 ›› 2017, Vol. 0 ›› Issue (9): 88-91,109.doi: 10.13474/j.cnki.11-2246.2017.0294

• 技术交流 • 上一篇    下一篇

轻型机载LiDAR在农村宅基地房屋测量中的应用

杨青山1, 汤学才1, 范彬彬1, 许正鹏2   

  1. 1. 巴音郭楞蒙古自治州国土资源勘测规划设计院, 新疆 库尔勒 841000;
    2. 新疆巴州国源测绘规划中心, 新疆 库尔勒 841000
  • 收稿日期:2017-07-06 出版日期:2017-09-25 发布日期:2017-10-12
  • 作者简介:杨青山(1970-),男,高级工程师,主要从事不动产测绘、工程测量和摄影测量方面的工作.E-mail:137268099@qq.com

The Application of Light Airborne LiDAR on Rural Homestead Building Surveying

YANG Qingshan1, TANG Xuecai1, FAN Binbin1, XU Zhengpeng2   

  1. 1. Bazhou Land Resources Surveying and Planning Institute, Korla 841000, China;
    2. Xinjiang Bazhou State Source Surveying and Mapping Planning Center, Korla 841000, China
  • Received:2017-07-06 Online:2017-09-25 Published:2017-10-12

摘要: 选择新疆焉耆县北大渠乡北大渠村房屋密集区作为研究区,通过三角翼搭载轻型机载LiDAR进行了低空(170m)交叉航线高密度点云数据采集,对点云数据进行拼接、校正、纹理信息增强,在点云上对房屋进行矢量化,并对结果进行精度检查。点云数据房角点采集率为83.3%,中误差为4.8cm。采用机载LiDAR测量房角点能够大大减少外业房角点测量的工作量。机载LiDAR的应用鲜有纹理信息的提取,本次测试通过对高密度点云数据进行有效的处理,提取了点云数据纹理信息,为机载LiDAR数据纹理信息的应用提供了参考,并对其精度有了明确的认识,可为后期相关工作的开展提供借鉴。

关键词: 机载LiDAR, 房屋测量, 纹理提取, 精度分析

Abstract: Taking a built-up area in Beidaqu village, Beidaqu township, Yanqi County, Xinjiang Uygur Autonomous Region as the study area, we acquired high density point cloud data in a cross-route way at low altitude (170 m) with the delta wing equipped with light airborne LiDAR. Then, we spliced, corrected and enhanced texture information of the point cloud data. Finally, we vectorized the housing information with the processed point cloud data and checked the vectorization results' accuracy. The results show that the collection rate of housing corner points is 83.3% with the point cloud data, and the median error is 4.8 cm. Using the airborne LiDAR, we can greatly reduce the workload of measuring the housing corner points. In view of rarely studies of texture information extracting with airborne LiDAR, this paper offers a reference for the application of it, and gives a clear understanding of its accuracy. In addition, the results can provide reference to the further related work.

Key words: airborne LiDAR, building surveying, texture, precision analysis

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