Analysis of Vertical Accuracy Based on Network/Base Station RTK-SfM Data
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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。
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关键词:
- 活动构造 /
- 移动摄影测量技术 /
- RTK-SfM DEM /
- 垂向误差 /
- 测量精度
Abstract: The development of Structure from Motion (SfM) technology makes it more convenient to obtain high precision DEM data in small and medium-sized areas quickly in the field of active tectonics research. The accuracy of DEM data is a major concern in the field of active tectonics and surveying. By comparing the SfM DEM data generated by non-RTK model UVA technology combined with ground control point (GCPs) and RTK-SfM DEM data obtained based on RTK SfM technology, this paper focuses on analyzing the vertical accuracy of DEM data obtained by SfM technology equipped with RTK module. The results of data acquisition, processing and comparison show that in the DEM data generated by non-RTK model SfM technology with the GCPs, the distortion rate is small in most areas except the distortion caused by fewer photos at the edge of the measurement area. The DEM data obtained by RTK-SfM has a smaller distortion rate, and the data generated by non-RTK SfM combined with GCPs has a system elevation error of about 0.85 m. After subtracting the system error, the point cloud comparison results show that more than 95% of the vertical errors of both are less than 0.05 m. The DEM data obtained by SfM technology equipped with RTK module has better vertical accuracy and saves time and labor cost.-
Key words:
- Active tectonics /
- SfM technology /
- RTK-SfM DEM /
- Vertical error /
- Accuracy of surveying
1) 2 CloudCompare user manual(Version 2.6.1),2015. -
表 1 初步对比点云转换矩阵数据
Table 1. Preliminary comparison point cloud transformation matrix table
x y z RMS 1.000 0.000 0.000 0.565 −0.000 1.000 0.000 0.509 −0.000 −0.000 1.000 0.851 0.000 0.000 0.000 1.000 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/m DGPS与RTK-SfM DEM差值/m 河床 0.44648900 1.25817214 T1 0.51727922 1.33264908 T2 0.56253832 1.39865517 T3 0.54695363 1.33524765 T4 0.61002861 1.38761910 T5 0.56203093 1.47095521 平均值 0.540886618 1.36388305 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/m DGPS与RTK-SfM DEM差值/m 平均值 标准差 平均值 标准差 河床 −0.108 698 0.178 616 −0.096 039 0.158 909 T1 −0.037 377 0.143 255 −0.026 488 0.081 722 T2 0.021 172 0.130 226 0.013 106 0.105 653 T3 −0.033 185 0.189 726 −0.010 624 0.109 698 T4 0.069 141 0.120 677 0.023 736 0.150 740 T5 0.107 072 0.116 793 0.021 144 0.082 876 -
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