School of Computer Science, China University of Geosciences, Wuhan, 430074, China.
Machine Intelligence and Slope Stability Laboratory, Department of Geosciences, University of Padova, 35131, Padua, Italy.
Environ Sci Pollut Res Int. 2024 Feb;31(8):12271-12287. doi: 10.1007/s11356-024-31995-x. Epub 2024 Jan 17.
Peshawar is one of the most densely populated cities of Pakistan with high urbanization rate. The city overexploits groundwater resources for household and commercial usage which has caused land subsidence. Land subsidence has long been an issue in Peshawar due to insufficient groundwater removal. In this research, we employ the persistent scatterer interferometry synthetic aperture radar (PS-InSAR) technique with Sentinel-1 imaging data to observe the yearly land subsidence and generate accumulative time-series maps for the years (2018 to 2020) using the SAR PROcessing tool (SARPROZ). The PS-InSAR findings from two contiguous paths are combined by considering the variance over the overlapping area. The subsidence rates in the Peshawar are from -59 to 17 mm/yr. The results show that subsidence is -28.48 mm/yr in 2018, the subsidence reached -49.02 mm/yr in 2019, while in 2020, the subsidence reached -49.90 mm/yr. The findings indicate a notable rise in land subsidence between the years 2018 and 2020. Subsidence is predicted in the research region primarily due to excessive groundwater removal and soil consolidation induced by surficial loads. The correlation of land subsidence observations with groundwater levels and precipitation data revealed some relationships. Overall, the proposed method efficiently monitors, maps, and detects subsidence-prone areas. The utilization of land subsidence maps will enhance the efficiency of urban planning, construction of surface infrastructure, and the management of risks associated with subsidence.
白沙瓦是巴基斯坦人口最密集的城市之一,城市化率很高。该市过度开采地下水用于家庭和商业用途,导致地面沉降。由于地下水抽取不足,白沙瓦长期以来一直存在地面沉降问题。在这项研究中,我们采用 Sentinel-1 成像数据的永久散射体干涉合成孔径雷达(PS-InSAR)技术,使用 SAR 处理工具(SARPROZ)观测每年的地面沉降,并生成 2018 年至 2020 年的累积时间序列图。通过考虑重叠区域的方差,将两条相邻路径的 PS-InSAR 结果进行合并。白沙瓦的沉降速率为-59 至 17 毫米/年。结果表明,2018 年沉降率为-28.48 毫米/年,2019 年沉降率达到-49.02 毫米/年,而 020 年沉降率达到-49.90 毫米/年。研究结果表明,2018 年至 2020 年间地面沉降明显增加。研究区域的沉降主要是由于过度抽取地下水和地表荷载引起的土壤固结。地面沉降观测与地下水位和降水数据的相关性表明存在一些关系。总的来说,该方法有效地监测、绘制和检测易沉降区域。利用地面沉降图将提高城市规划、地表基础设施建设和沉降相关风险管理的效率。