Application of DInSAR-GPS Optimization for Derivation of Three Dimensional Surface Motion of Southern California

A spatio-temporal Bayesian modeling technique based on optimization of Gibb's energy function within MRF framework is applied to derive three-dimensional surface motion maps of southern California region from sparse GPS measurements from Southern California Integrated GPS Network (SCIGN) and ERS-2 Differential InSAR interferogram. This technique produces a continuous high-resolution velocity field containing estimates of surface motion over a given time period, complete with error estimates. Significant improvement in the accuracy of the vertical component and the moderate improvement in accuracy of the horizontal components of velocity are achieved in comparison with the GPS data alone. The method can be applied to consequent time periods therefore providing four dimensional velocity field of the region.