Reduction of Atmospheric Effects on InSAR Observations Through Incorporation of GACOS and PCA Into Small Baseline Subset InSAR

Abstract

Small Baseline Subset InSAR (SBAS InSAR) utilizes a series of synthetic aperture radar (SAR) interferograms to generate a time series that can analyze the surface displacements of coherent points. Still, atmospheric errors in interferometric SAR (InSAR) measurements can seriously affect the reliability of the surface displacement time series. In this article, a new approach incorporating the Generic Atmospheric Correction Online Service for InSAR (GACOS) and principal component analysis (PCA) is proposed to reduce atmospheric errors in SBAS InSAR. Its application to Southern California, USA suggests that the incorporation of GACOS and PCA can efficiently reduce atmospheric effects on InSAR observations and hence improve the accuracy of InSAR-derived surface displacements. The overall standard deviations of the SAR interferograms were reduced from 4.97 to 2.02 rad after applying GACOS and PCA with the root mean square error (RMSE) reducing by 61.1% from 18 to 7 mm. In addition, comparisons between different PCA processing strategies suggest that the more principal components are removed, the smaller the standard deviations of the interferograms, but the lower the accuracy of InSAR-derived surface displacements.