An iterative PS-InSAR method for the analysis of large spatio-temporal baseline data stacks for land subsidence estimation

South-west of Tehran, the capital city of Iran, is subjected to a high deformation rate due to excessive groundwater extractions. Persistent Scatterrer SAR Interferometry (PS-InSAR) technique is used to monitor Tehran's deformation. Three time series data including two Sentinel-1A (S-1A) spanning from 2014 to 2017, and an ENVISAT-ASAR data stack spanning from 2004 to 2010, are analyzed. The PS-InSAR technique does not perform well on ENVISAT-ASAR due to poor selection of PS points induced by large perpendicular baselines and strong temporal decorrelation of the dataset. In this paper, a novel Iterative PSI method (IPSI) is proposed to increase the PS points which are lost in PS-InSAR technique because of the unsuccessful derivation of the absolute phase value due to an integer ambiguity. The method selects PS points based on simultaneous analysis of their amplitude and phase. Results demonstrate that the density of PSs has been increased by about 4.5 times. Line of Sight (LOS) velocities obtained from both S-1A and ENVISAT-ASAR data analysis are highly compatible with each other, indicating the reliability of the both applied methods. The maximum cumulative displacements are estimated as 39.6 cm and 88.4 cm for Sentinel-1A and ENVISAT-ASAR datasets respectively. Moreover, the subsidence area has grown in the period between the data acquisition time. The methods are successfully validated by subsidence rates obtained from precise leveling and GPS observations.