Abstract
Land deformation has become a crucial threat in recent decades, caused by various natural and anthropogenic activities in the environment. The seismic land dynamics, landslides activities, heavy rainfall resulting in flood events, and subsurface aquifer shrinkage due to the excessive extraction of groundwater are among the major reasons for land deformation, which may cause serious damage to the overall land surface, civil infrastructure, underground tunnels, and pipelines, etc. This study focuses on preparing a framework for estimating land deformation and analyzing the causes associated with land deformation. A time-series SAR Interferometry-based technique called PsInSAR was used to measure land deformation, using Sentinel-1 datasets from 2015 to 2021 by estimating land deformation velocities for this region. The obtained PSInSAR deformation velocity results ranged between -4 mm to +2 mm per year. Further, land use land cover (LULC) changes in the area were analyzed as an essential indicator and probable cause of land deformation. LULC products were first generated using Landsat-8 images for two time periods (2015, 2021), which were then evaluated in accordance with the deformation analysis. The results indicated an increase in the built-up areas and agricultural cover in the region at the cost of shrinkage in the vegetated lands, which are highly correlated with the land subsidence in the region, probably due to the over-extraction of groundwater. Further, the outer region of the study area consisting of undulating terrain and steep slopes also coincides with the estimated high subsidence zones, which could be related to higher instances of landslides identified in those areas from various primary and secondary information collected. One of the causes of landslides and soil erosion in the region is identified to be high-level precipitation events that loosen the surface soil that flows through the steep slopes. Furthermore, the study region lying in a high seismic zone with characteristic unstable slopes are more susceptible to land deformation due to high seismic activities. The approach developed in the study could be an useful tool for constant monitoring and estimation of land deformation and analysis of the associated causes which can be easily applied to any other region.