Application of the split range-spectrum method and GACOS model to correct the ionospheric and tropospheric delay of the InSAR time series

Synthetic aperture radar interferometry (InSAR) is an effective tool for large area measurements and analysis, including topography measurements or ground surface subsidence caused by mining operations, earthquakes, or volcanic activity. However, the accuracy of these measurements is often limited by the disturbances that arise during the microwave propagation process in the ionosphere and troposphere. The atmospheric delay in the interferometric phase may cause the detection of terrain surface changes to be impossible or significantly distorted.  In our proposed approach, we propose a complete workflow to computing a time series from raw data obtained with the Sentinel-1 mission. The solution consists of a Small Baseline Subset (SBAS) algorithm with an implementation of the split range-spectrum method and the Generic Atmospheric Correction Online Service (GACOS) model. The proposed solution was used in time series calculations of SAR data in two areas: northern Chile and Taiwan. It is demonstrated that simultaneous allowance for both the tropospheric and ionospheric corrections significantly improves final results.