郑翔天, 杨晓琳, 何秀凤, 马海涛, 于正兴, 任贵文, 张浩, 张劲松. 点云辅助GB-InSAR影像与地形数据应急变形监测方法[J]. 武汉大学学报 ( 信息科学版), 2022, 47(7): 1081-1092. DOI: 10.13203/j.whugis20200280
引用本文: 郑翔天, 杨晓琳, 何秀凤, 马海涛, 于正兴, 任贵文, 张浩, 张劲松. 点云辅助GB-InSAR影像与地形数据应急变形监测方法[J]. 武汉大学学报 ( 信息科学版), 2022, 47(7): 1081-1092. DOI: 10.13203/j.whugis20200280
ZHENG Xiangtian, YANG Xiaolin, HE Xiufeng, MA Haitao, YU Zhengxing, REN Guiwen, ZHANG Hao, ZHANG Jinsong. Integrated GB-InSAR Images and Terrain Data for Emergency Deformation Monitoring Assisted by Point Clouds[J]. Geomatics and Information Science of Wuhan University, 2022, 47(7): 1081-1092. DOI: 10.13203/j.whugis20200280
Citation: ZHENG Xiangtian, YANG Xiaolin, HE Xiufeng, MA Haitao, YU Zhengxing, REN Guiwen, ZHANG Hao, ZHANG Jinsong. Integrated GB-InSAR Images and Terrain Data for Emergency Deformation Monitoring Assisted by Point Clouds[J]. Geomatics and Information Science of Wuhan University, 2022, 47(7): 1081-1092. DOI: 10.13203/j.whugis20200280

点云辅助GB-InSAR影像与地形数据应急变形监测方法

Integrated GB-InSAR Images and Terrain Data for Emergency Deformation Monitoring Assisted by Point Clouds

  • 摘要: 将采用地面三维激光扫描(terrestrial laser scanning, TLS)、地基合成孔径雷达干涉测量(ground-based interferometric synthetic aperture radar, GB-InSAR)和无人机航空摄影测量(unmanned aerial vehicle photography, UAV)的综合遥感方案应用于崩塌体应急监测。引入迭代最近点法(iterative closest point, ICP),首先实现TLS点云和UAV影像离散点云配准;然后,利用几何映射方法实现GB-InSAR二维形变图与TLS点云三维匹配;针对崩塌体应急缺少人工目标辅助校正几何映射偏差的问题,综合目视解译以及峰值相关性分析提取各数据间的同名特征点,根据同名特征点计算空间坐标变换参数,建立变换方程来完成误匹配纠正。利用所提的匹配方法处理模拟数据及某滑坡崩塌残余体实际监测数据,结果表明实测匹配精度达像素级,满足应急监测需求。

     

    Abstract:
      Objectives  Terrestrial laser scanning (TLS), ground-based interferometric synthetic aperture radar (GB-InSAR) and unmanned aerial vehicle(UAV) photography have been applied to emergency deformation monitoring of rockslide. The objectives are concerns about new problems of 3D visualization of deformation data.
      Methods  Firstly, we introduced iterative closest point method (ICP) to complete the registration between the TLS point cloud and UAV terrain model. Secondly, geometric mapping method was applied to achieve data fusion between GB-InSAR deformation map and TLS point cloud.The mapping deviation is difficult to be corrected by conventional methods, because the lack of artificial control points on the rockslide. Visual interpretation and GB-InSAR images simulation method were combined to extract the control points.The spatial coordinate transformation parameters were estimated with the least square method. The transformation model was established to correct the mismatch.
      Results  The proposed method was verified by the simulation data and the actual monitoring data of a landslide. The result shows that the accuracy reaches the pixel level which meet the needs of emergency monitoring.
      Conclusions  The proposed method is limited by the working conditions of emergency and the subjectivity of image interpretation. If the accuracy of control point selection was not narrowed, the final matching fusion position accuracy may reach pixel-level accuracy.

     

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