InSAR-based large-scale detection and monitoring of the surface deformation in Linfen mining areas, Shanxi Province
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摘要: 矿区持续开采造成的地面沉陷会对环境带来巨大的破坏,如何快速获取大范围区域内矿区的位置和地表形变量成为矿区监测亟待解决的问题,为此利用合成孔径雷达干涉测量(interferometry synthetic aperture Radar,InSAR)技术对山西省临汾市开展矿区沉陷大范围探测和监测研究。首先,通过差分合成孔径雷达干涉测量方法(differential interferometric synthetic aperture Rader,D-InSAR)处理分析12景Sentinel-1A升轨数据,对研究区域进行了矿区沉陷灾害大范围探测; 然后利用小基线集(small baseline subset,SBAS)-InSAR处理了不同轨道共432景Sentinel-1A升轨数据,对普查出来的重点区域进行监测。研究结果发现,在临汾市共探测出105处沉陷区,沉陷区均处于临汾断陷盆地两侧的山体中。进一步对重点沉陷区域进行时序形变监测,发现多处沉陷区均处于持续形变过程中,且形变量级较大,最大形变速率达-381 mm/a,对地表生态环境和基础设施带来了巨大的破坏。通过光学影像寻找到了沉陷区附近的开采点,验证了基于InSAR技术的大范围探测与监测方法的可靠性,研究结果可为临汾市矿区沉陷灾害防治提供重要依据。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.
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Key words:
- large-scale detection /
- D-InSAR /
- SBAS /
- deformation monitoring
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