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基于网络/基站RTK移动摄影测量数据的垂向精度分析

丁锐 李环宇 张世民 姜大伟 刘睿 李安

丁锐,李环宇,张世民,姜大伟,刘睿,李安,2022. 基于网络/基站RTK移动摄影测量数据的垂向精度分析. 震灾防御技术,17(1):68−78. doi:10.11899/zzfy20220107. doi: 10.11899/zzfy20220107
引用本文: 丁锐,李环宇,张世民,姜大伟,刘睿,李安,2022. 基于网络/基站RTK移动摄影测量数据的垂向精度分析. 震灾防御技术,17(1):68−78. doi:10.11899/zzfy20220107. doi: 10.11899/zzfy20220107
Ding Rui, Li Huanyu, Zhang Shimin, Jiang Dawei, Liu Rui, Li An. Analysis of Vertical Accuracy Based on Network/Base Station RTK-SfM Data[J]. Technology for Earthquake Disaster Prevention, 2022, 17(1): 68-78. doi: 10.11899/zzfy20220107
Citation: Ding Rui, Li Huanyu, Zhang Shimin, Jiang Dawei, Liu Rui, Li An. Analysis of Vertical Accuracy Based on Network/Base Station RTK-SfM Data[J]. Technology for Earthquake Disaster Prevention, 2022, 17(1): 68-78. doi: 10.11899/zzfy20220107

基于网络/基站RTK移动摄影测量数据的垂向精度分析

doi: 10.11899/zzfy20220107
基金项目: 国家重点研发计划(2018YFC1504201);科研院所基本科研业务专项(ZDJ2018-22、ZDJ2017-24、ZDJ2020-12)
详细信息
    作者简介:

    丁锐,男,生于1982年。助理研究员。主要从事活动构造、构造地貌学研究。E-mail:ruiding@ninhm.ac.cn

  • 2 CloudCompare user manual(Version 2.6.1),2015.

Analysis of Vertical Accuracy Based on Network/Base Station RTK-SfM Data

  • 摘要: 移动摄影测量技术SfM(Structure from Motion)的发展使活动构造研究中快速获得野外中小区域内高精度DEM数据更便捷,DEM数据精度是目前活动构造与测量领域较关注的问题。本文通过对比非RTK模式无人机摄影测量并结合地面控制点(GCPs)生成的SfM DEM数据与基于RTK移动摄影测量技术获取的RTK-SfM DEM数据差异,重点分析搭载RTK模块的移动摄影测量技术获取的DEM数据在垂向上的精度。数据采集、处理与对比结果表明:在添加地面控制点后的非RTK模式无人机摄影测量生成的DEM数据中,除测量区域边缘照片较少而产生畸变外,大部分地区畸变率较小;基于移动RTK技术摄影测量获取的高程数据畸变率更小,且与非RTK模式无人机摄影结合地面控制点生成的高程数据存在约0.85 m的系统高程误差,减去该误差后,点云对比结果表明二者95%以上的点垂向误差均<0.05 m;搭载RTK模块的移动摄影测量技术获取的DEM数据在垂向上具有更高的精度,且节省了时间与人工成本。
    1)  2 CloudCompare user manual(Version 2.6.1),2015.
  • 图  1  SfM摄影测量原理与数据处理流程

    Figure  1.  SfM principle and data processing flow chart

    图  2  测量区域及其周围构造

    Figure  2.  Schematic diagram of the survey area and its surrounding tectonics

    图  3  测量用无人机及地面控制点采集系统

    Figure  3.  UAV for surveying and ground control point acquisition system

    图  4  摄影测量数据处理及成果图

    Figure  4.  SfM data processing and results

    图  5  SfM-DEM与RTK-SfM DEM点云对比统计及误差空间分布

    Figure  5.  Point cloud comparison statistics and error spatial distribution between SFM-DEM and RTK-SFM DEM

    图  6  基于DEM分析结果与野外调查结果的阶地划分及DGPS测线分布

    Figure  6.  River terraces division and DGPS lines distribution based on DEM analysis and field investigation

    图  7  DGPS、SfM DEM、RTK-SfM DEM高程数据对比

    Figure  7.  Comparison of three elevation data of DGPS, SfM DEM and RTK-SFM DEM

    图  8  去除系统误差后DGPS数据与2种方式生成的DEM数据之间差值的正态分布

    Figure  8.  Normal distribution of the difference between DGPS data and DEM generated by the two methods after removing systematic error

    表  1  初步对比点云转换矩阵数据

    Table  1.   Preliminary comparison point cloud transformation matrix table

    xyzRMS
    1.0000.0000.0000.565
    −0.0001.0000.0000.509
    −0.000−0.0001.0000.851
    0.0000.0000.0001.000
    下载: 导出CSV

    表  2  3种高程数据差值的平均值

    Table  2.   Average value of difference of three elevation data

    测线DGPS与SfM DEM差值/mDGPS与RTK-SfM DEM差值/m
    河床0.446489001.25817214
    T10.517279221.33264908
    T20.562538321.39865517
    T30.546953631.33524765
    T40.610028611.38761910
    T50.562030931.47095521
    平均值0.5408866181.36388305
    下载: 导出CSV

    表  3  去除系统误差后3种高程数据差值平均值与标准差

    Table  3.   Average difference and standard deviation of three elevation data after removing systematic error

    测线DGPS与SfM DEM差值/mDGPS与RTK-SfM DEM差值/m
    平均值标准差平均值标准差
    河床−0.108 6980.178 616−0.096 0390.158 909
    T1−0.037 3770.143 255−0.026 4880.081 722
    T20.021 1720.130 2260.013 1060.105 653
    T3−0.033 1850.189 726−0.010 6240.109 698
    T40.069 1410.120 6770.023 7360.150 740
    T50.107 0720.116 7930.021 1440.082 876
    下载: 导出CSV
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  • 收稿日期:  2022-02-07
  • 网络出版日期:  2022-05-31
  • 刊出日期:  2022-03-31

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