Bayesian Inversion of Wrapped Satellite Interferometric Phase to Estimate Fault and Volcano Surface Ground Deformation Models

Bayesian inference and an improved downsampling method is used to determine earthquake and volcano source parameters using a popular geodetic observation method, satellite radar interferometry. The main novelty of the proposed approach is that the interferometric wrapped phase can be directly inverted, circumventing the ill‐posed phase unwrapping processing step. Phase unwrapping errors severely affect the estimation of earthquake and volcano source parameters using interferometric observations. Therefore, it is desirable to avoid phase unwrapping completely. To overcome the need for phase unwrapping, we propose a downsampling algorithm and a method to estimate the covariance function of the wrapped phase and establish an appropriate misfit function between the observed and simulated wrapped phase. Uncertainties in source parameters are assessed with a Bayesian approach, and finally, the robustness of the inversion methodology is tested in multiple simulations including variable decorrelation and atmospheric noise simulations. The method is shown to be robust in challenging noise scenarios. It features an improvement in performance with the Bayesian approach, compared to similar previous methods, avoiding any influence of seed starting models and escaping local minima. The impact of a small percentage of incorrectly unwrapped phase observations in current state‐of‐the‐art methods is shown to strongly affect the estimation process. We conclude that in the cases where phase unwrapping is difficult or even impossible, the proposed inversion methodology with wrapped phase will provide an alternative approach to assess earthquake and volcano source model parameters.