An approach for multi-dimensional land subsidence velocity estimation using time-series Sentinel-1 SAR datasets by applying persistent scatterer interferometry technique

The time-series interferometric synthetic aperture radar (InSAR) techniques has the potential of estimating the land subsidence at a high accuracy of nearly in millimeter scale. The major limitation of the present InSAR methods like persistent scatterer interferometry (PSI) is that they measure land deformation velocities only in the direction of the radar line of sight (LOS). Hence, the real prospects of the deformation velocity, i.e. the horizontal and vertical components of velocity remain uncertain. This study is focusing on retrieving PSI based multi-dimensional land deformation velocity along horizontal and vertical directions in an urban region by using ascending and descending pass Sentinel-1 datasets. The area for this study is Lucknow city in Uttar Pradesh state of India. The estimated LOS velocity vectors from ascending and descending pass time-series datasets are utilized for retrieving multidimensional subsidence velocity. Further, the retrieved time-series land subsidence is correlated to the groundwater level variation during the considered time span.