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Monitoring and analysis of mining 3D time-series deformation based on multi-track SAR data

机译:基于多轨SAR数据的3D时间序列变形监测与分析

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摘要

Accurate monitoring of the developing process of a surface subsidence basin is the basis of building damage assessment and surface deformation prediction. In this paper, the Synthetic Aperture Radar (SAR) data of three different imaging geometries, TerraSAR, Radarsat-2, and Sentinel-1A, were exploited. Firstly, two-dimensional (2D) time-series deformation of the surface subsidence basin caused by 15,235 working face mining was obtained based on Multidimensional Small Baseline Subset (MSBAS) technology from 19 December 2015 to 5 March 2016. By comparing vertical deformation with levelling data, it is shown that the root-mean-square error of vertical deformation is 3.2 mm and the standard deviation is 1.9 mm when the ascending-descending track SAR data is available. Otherwise, the root-mean-square error of vertical deformation is 18.1 mm and the standard deviation is 11.6 mm. Because of the low precision of the north-south horizontal movement monitored by the SAR sensor, the vertical deformation acquired by MSBAS technology and the rules of the mining subsidence (horizontal movement is proportional to tilt) were combined to obtain the north-south horizontal movement which was proven to be reliable by comparing the 2D time-series deformation obtained by MSBAS technology. Then, the deformation of the railway in the surface subsidence basin was analysed based on the three-dimensional (3D) time-series deformation. The results show that the subsidence, tilt, and horizontal movement strongly influence the railway in the monitoring period, but will not affect the normal traffic. This experiment lays a technical foundation for preventing the occurrence of mining disasters and verifies the ability to monitor the deformation of buildings and structures by interferometry synthetic aperture radar technology.
机译:准确监测地表塌陷盆地的发育过程是建筑物破坏评估和地表变形预测的基础。本文利用了三种不同成像几何形状的合成孔径雷达(SAR)数据,分别是TerraSAR,Radarsat-2和Sentinel-1A。首先,基于多维小基线子集(MSBAS)技术,从2015年12月19日至2016年3月5日,获得了由15,235个工作面开采引起的地表沉陷盆地的二维(2D)时间序列变形。数据显示,当有上升和下降轨道SAR数据时,垂直变形的均方根误差为3.2 mm,标准偏差为1.9 mm。否则,垂直变形的均方根误差为18.1 mm,标准偏差为11.6 mm。由于SAR传感器监测的南北水平运动精度较低,因此结合了MSBAS技术获得的垂直变形和开采沉陷规则(水平运动与倾斜成比例)来获得南北水平运动。通过比较MSBAS技术获得的2D时间序列变形,证明了该方法是可靠的。然后,基于三维时间序列变形,分析了地面沉降盆地中铁路的变形。结果表明,在监测期内,沉降,倾斜和水平运动对铁路影响很大,但对正常交通没有影响。该实验为预防采矿灾害的发生奠定了技术基础,并验证了通过干涉法合成孔径雷达技术监测建筑物和结构变形的能力。

著录项

  • 来源
    《International journal of remote sensing》 |2019年第4期|1411-1427|共17页
  • 作者单位

    China Univ Min & Technol, NASG Key Lab Land Environm & Disaster Monitoring, Xuzhou, Jiangsu, Peoples R China|China Univ Min & Technol, Jiangsu Key Lab Resources & Environm Informat Eng, Xuzhou, Jiangsu, Peoples R China|China Univ Min & Technol, Sch Environm Sci & Spatial Informat, Xuzhou, Jiangsu, Peoples R China;

    China Univ Min & Technol, NASG Key Lab Land Environm & Disaster Monitoring, Xuzhou, Jiangsu, Peoples R China;

    China Univ Min & Technol, Jiangsu Key Lab Resources & Environm Informat Eng, Xuzhou, Jiangsu, Peoples R China;

    China Univ Min & Technol, Jiangsu Key Lab Resources & Environm Informat Eng, Xuzhou, Jiangsu, Peoples R China|China Univ Min & Technol, Sch Environm Sci & Spatial Informat, Xuzhou, Jiangsu, Peoples R China;

    East China Univ Technol, Fac Geomat, Nanchang, Jiangxi, Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-18 04:14:40

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