A Robust Method for Selecting a High-Quality Interferogram Subset in InSAR Surface Deformation Analysis

Abstract

The accuracy of Interferometric Synthetic Aperture Radar surface deformation solutions 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, California, we show that subtle phase noise can lead to up to 31.5 mm/yr line-of-sight (LOS) errors in short temporal baseline subset solutions, while decorrelation leads to a systematic underestimation of LOS rates (up to 92.3 mm/yr) in long temporal baseline subset solutions. Our new workflow better mitigates these noise sources at the same time. In the Eagle Ford region, Texas, our strategy better reconstructed up to 11.9 cm of cumulative LOS deformation between 2017 and 2021 over a (Formula presented.) 900 (Formula presented.) region. This deformation feature can be linked to the total volume of produced oil and water through a linear relationship.