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.