测绘与空间地理信息2024,Vol.47Issue(9) :204-206,210.

基于移动车载激光扫描技术的城市部件自动化采集

Automatic Collection of Urban Components Based on Mobile Vehicle-borne Laser Scanning Technology

肖笛 王丹阳 朱丹莉
测绘与空间地理信息2024,Vol.47Issue(9) :204-206,210.

基于移动车载激光扫描技术的城市部件自动化采集

Automatic Collection of Urban Components Based on Mobile Vehicle-borne Laser Scanning Technology

肖笛 1王丹阳 2朱丹莉2
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作者信息

  • 1. 浙江省国土勘测规划有限公司,浙江杭州 310000
  • 2. 浙江省测绘科学技术研究院,浙江杭州 310000
  • 折叠

摘要

为了提高城市部件采集效率及精度,本文结合移动车载激光扫描技术在城市道路空间三维数据采集中的优势,提出将移动车载激光扫描技术应用到城市部件提取中.首先,通过外业采集试验区点云数据及基准站坐标数据,解算得到原始点云数据;其次,通过对原始数据进行去噪、抽稀等预处理后,得到满足城市部件提取要求的高精度点云数据;最后,使用自动提取平台提取得到试验区城市部件数据.通过将GNSS-RTK测量数据与本文提取部件数据进行对比,结果表明,基于移动车载激光扫描技术的城市部件采集技术能够满足城市部件采集的精度要求,可大大提高城市部件采集效率.本文的研究可为智慧城市建设中城市部件管理提供了有益借鉴.

Abstract

In order to improve the efficiency and accuracy of urban component collection,this paper proposes to apply mobile vehicle-borne laser scanning technology to urban component extraction,combining the advantages of mobile vehicle-borne laser scanning tech-nology in urban road space three-dimensional data collection. Firstly,the original point cloud data is obtained through the field collec-tion of the point cloud data in the test area and the coordinate data of the reference stations;secondly,after preprocessing the original data,such as denoising and thinning,the high-accuracy point cloud data meeting the requirements of urban component extraction is obtained;finally,using the automatic extraction platform to extract the urban component data in the test area. By comparing the GNSS-RTK measurement data with the component data extracted in this paper,the results show that the urban component acquisition tech-nology based on mobile vehicle-borne laser scanning technology can meet the accuracy requirements of urban component acquisition,and can greatly improve the efficiency of urban component acquisition. The research in this paper can provide a useful reference for ur-ban component management in smart city construction.

关键词

车载激光扫描系统/城市部件采集/点云数据/去噪/抽稀

Key words

vehicle-borne laser scanning system/urban component collection/point cloud data/denoising/thinning

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出版年

2024
测绘与空间地理信息
黑龙江省测绘学会

测绘与空间地理信息

影响因子:0.788
ISSN:1672-5867
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