Abstract
Urban areas worldwide are increasingly facing challenges related to land subsidence, a phenomenon exacerbated by uncontrolled groundwater extraction and urban expansion. This research focuses on the Tehran plain, Iran's capital city, where significant subsidence has been observed due to uncontrolled migrations influenced by various economic and political factors. This expansion has increased demand for energy, notably water, leading to irregular water withdrawals from underground sources and, consequently, land subsidence. Monitoring this subsidence, particularly its effects on urban infrastructure, has become a critical challenge. This research first reviewed the existing body of knowledge related to subsidence measurement in the Tehran plain with an emphasis on their findings and limitations and then used radar images to study the subsidence patterns in the Tehran plain from 2016 to the end of 2020. Finally, the results collaborated by optical imagery analysis to find the relationship between surface change detection and spatiotemporal distribution of subsidence. As a result, through processing Sentinel-1A SAR images, consistent vertical displacements (subsidence) were observed, especially in areas heavily reliant on groundwater from wells, with some areas experiencing a rate of more than −20 mm/year. Horizontal displacement, however, was approximately about ±8 mm/year. Also, our results show that the subsidence rate in this plain has decreased in recent years. Therefore, the study integrated multispectral satellite data to clarify this issue and compensate for missing groundwater level data, specifically the Normalized-Difference Vegetation Index (NDVI) and Normalized-Difference Moisture Index (NDMI). These datasets were used to monitor changes in vegetation cover distribution and moisture in response to the variations of groundwater depth over time. The results of this research can be beneficial in adequately managing groundwater resource utilization to reduce the potential damage to infrastructure and the environment.
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More From: Remote Sensing Applications: Society and Environment
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