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The potential of Sentinel-IA interferometric SAR data in monitoring of surface subsidence caused by overdrafting groundwater in agricultural areas

机译:Sentinel-IA干涉SAR数据在监测农业地区地下水超采引起的地面沉降中的潜力

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The use of Interferometric Synthetic Aperture Radar (InSAR) data has become known as an important technique for monitoring and measuring land surface deformations caused by groundwater level fluctuations. In this study, a region from the closed Konya agricultural basin is selected to infer the spatial and temporal distributions of the ground deformations using SAR images acquired by the comparatively new satellite Sentinel-1A of the European Space Agency (ESA). With the purpose of revealing Sentinel-1A satellite sensors potential we employ 18 months of periodical data obtained of 43 SAR scenes on the ascending T87 and 45 SAR scenes on the descending T167 satellite tracks. We apply GMTSAR, an open source InSAR processing system that uses Generic Mapping Tools (GMT). InSAR time series have been calculated using the SBAS method. The preliminary results obtained indicate the efficiency of Sentinel-1A alone over a comparatively short period of time in monitoring land surface subsidence. Even though the calculations and processing were performed in presence of relatively noisy data, the results obtained are consistent and in agreement regardless of the flight direction of the satellite. The estimated deformation rate obtained from both ascending and descending tracks is about 2 (+/-1) cm/yr.
机译:干涉式合成孔径雷达(InSAR)数据的使用已成为监测和测量由地下水位波动引起的地表变形的重要技术。在这项研究中,选择了来自封闭的科尼亚农业盆地的一个区域,以使用由欧洲航天局(ESA)相对较新的卫星Sentinel-1A采集的SAR图像来推断地面变形的时空分布。为了揭示Sentinel-1A卫星传感器的潜力,我们使用了18个月的定期数据,这些数据是从上升的T87卫星上的43个SAR场景和下降的T167卫星轨道上的45个SAR场景获得的。我们应用GMTSAR,这是一个使用通用映射工具(GMT)的开源InSAR处理系统。已使用SBAS方法计算了InSAR时间序列。获得的初步结果表明,仅Sentinel-1A在相对较短的时间内即可监测地面沉降。即使在存在相对嘈杂的数据的情况下执行了计算和处理,无论卫星的飞行方向如何,所获得的结果都是一致且一致的。从上升和下降轨道获得的估计变形率约为2(+/- 1)cm / yr。

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