A robust method for selecting a high-quality interferogram subset in InSAR surface deformation analysis

Abstract

The accuracy of surface deformation derived from Interferometric Synthetic Aperture Radar (InSAR) observations depends on the quality of the chosen interferogram subset. We present a method to select interferogram subsets based on unwrapping errors rather than temporal baseline thresholds. Using Sentinel-1 interferograms over the Tulare Basin (CA), we show that tropospheric noise dominates short temporal baseline subset solutions (with up to 2.9 cm/yr residuals at co-located GPS sites), while decorrelation leads to a systematic underestimation of true deformation rate in long temporal baseline subset solutions (with up to 5.5 cm/yr residuals). Our new workflow better mitigates these two noise sources at the same time. In the Eagle Ford (TX) region, our strategy revealed up to ~11 cm of cumulative line-of-sight (LOS) deformation over a ~900 km2 region. This deformation feature is associated with ongoing oil and gas activities and is reported for the first time here.