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Remote Sensing for Natural Resources    2022, Vol. 34 Issue (3) : 146-153     DOI: 10.6046/zrzyyg.2021289
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InSAR-based large-scale detection and monitoring of the surface deformation in Linfen mining areas, Shanxi Province
MA Xuefei1,2(), ZHANG Shuangcheng1,2(), HUI Wenhua1, XU Qiang1
1. College of Geology Engineering and Geomatics, Chang’an University, Xi’an 710054, China
2. State Key Laboratory of Geo-Information Engineering, Xi’an 710054, China
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Abstract  

The ground subsidence caused by continuous mining in mining areas will seriously destroy the environment. There is an urgent need to quickly identify the locations and surface deformation of large-scope mining areas in the mining area monitoring. Given this, this study carried out large-scale detection and monitoring of the subsidence of mining areas in Linfen City using the synthetic aperture Radar interferometry (InSAR) technique. Firstly, by processing and analyzing 12 scenes of Sentinel 1A ascending data using the differential interferometric synthetic aperture Radar (D-InSAR) technique, this study conducted large-scale detection of subsidence disasters in mining areas in the study area. Then, this study processed 432 scenes of Sentinel 1A ascending data from different orbits using the small baseline subset InSAR (SBAS-InSAR) and monitored the obtained key areas. The results of this study show that there are a total of 105 subsidence areas in Linfen City, all of which are located in the mountains on both sides of the faulted Linfen basin. Further time-series deformation monitoring of key subsidence areas shows that many subsidence areas are continuously deforming, with high deformation amplitude and the deformation rate up to a maximum of -381 mm/a, and have caused huge damage to the ecological environment and infrastructure on the surface. The mining points near the subsidence area were identified according to optical images, thus verifying the reliability of the large-scale detection and monitoring method based on the InSAR technology. The results of this study will provide an important basis for the prevention and control of subsidence disasters in the mining areas of Linfen.

Keywords large-scale detection      D-InSAR      SBAS      deformation monitoring     
ZTFLH:  TP79  
Corresponding Authors: ZHANG Shuangcheng     E-mail: 516832020@qq.com;shuangcheng369@chd.edu.cn
Issue Date: 21 September 2022
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Xuefei MA
Shuangcheng ZHANG
Wenhua HUI
Qiang XU
Cite this article:   
Xuefei MA,Shuangcheng ZHANG,Wenhua HUI, et al. InSAR-based large-scale detection and monitoring of the surface deformation in Linfen mining areas, Shanxi Province[J]. Remote Sensing for Natural Resources, 2022, 34(3): 146-153.
URL:  
https://www.gtzyyg.com/EN/10.6046/zrzyyg.2021289     OR     https://www.gtzyyg.com/EN/Y2022/V34/I3/146
Fig.1  Technical flow chart
Fig.2  Image and DEM coverage
Fig.3  D-InSAR recognition results
参数名称 参数选择
多视比 4∶1
偏移量计算窗口 128×128
偏移量多项式参数个数 3
空间基线/m -120~120
时间基线/d 1~90
滤波窗口 32×32
解缠方法 MCF
Tab.1  Detailed data processing parameters
Fig.4  Deformation rate map of SBAS-InSAR subsidence area in Linfen City from March 2017 to December 2020
Fig.5  Results of SBAS-InSAR time series monitoring from 19 March,2017 to 28 December,2020 in region C
Fig.6  Timing changes of p1, p2, p3, p4
Fig.7  Key mining area profile
Fig.8  Remote sensing interpretation map of subsidence area
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