Estimation of Ground Displacement in San Francisco Bay Area Using a Spatio-Temporal Unwrapping Network Based Psinsar Algorithm

For many years, ground surface deformations have been monitored using the DInSAR technique. Because of some major drawbacks, this method has been taken over by a more precise remote sensing mechanism, known as PSInSAR (Persistent Scatterer Interferometric SAR). The latter approach proves helpful as it offers better precision, noise reduction in wider coverage of the geographical area when compared with DInSAR. In this work, we have estimated the deformation rate and topographic error of the San Francisco Bay area using the STUN (Spatio-Temporal Unwrapping Network) algorithm with the pre-selected PS points. Further, the outliers were removed using the squared-norm of least-square residuals. Finally, we validate the estimated deformation rate with the results of StaMPS (Stanford Method for Persistent Scatterer), and they are in agreement with minimal discrepancies (mean 0.9, standard deviation = 2.8 mm/y).