An improved data integration algorithm to constrain the 3D displacement field induced by fast deformation phenomena tested on the Napa Valley earthquake

In this work, we propose an improved algorithm to constrain the 3D ground displacement field induced by fast surface deformations due to earthquakes or landslides. Based on the integration of different data, we estimate the three displacement components by solving a function minimization problem from the Bayes theory. We exploit the outcomes from SAR Interferometry (InSAR), Global Positioning System (GNSS) and Multiple Aperture Interferometry (MAI) to retrieve the 3D surface displacement field. Any other source of information can be added to the processing chain in a simple way, being the algorithm computationally efficient. Furthermore, we use the intensity Pixel Offset Tracking (POT) to locate the discontinuity produced on the surface by a sudden deformation phenomenon and then improve the GNSS data interpolation. This approach allows to be independent from other information such as in-situ investigations, tectonic studies or knowledge of the data covariance matrix. We applied such a method to investigate the ground deformation field related to the 2014 Mw 6.0 Napa Valley earthquake, occurred few kilometers from the San Andreas fault system.