GNSS/InSAR/UAVSAR Integration for 3-D Deformation Field and fault creep rates in California

Zheng-Kang Shen, & Zhen Liu

Submitted September 7, 2025, SCEC Contribution #14681, 2025 SCEC Annual Meeting Poster #TBD

We have developed a method to integrate GNSS and InSAR data to produce a 3-D surface velocity field of the Earth [Shen and Liu, 2020, 2025]. The method includes the following key components: (a) An optimal interpolation approach to convert discrete GNSS velocity measurements into a continuous velocity field. (b) A pragmatic strategy to estimate uncertainties for InSAR and GNSS measurements, as well as for interpolated GNSS velocities, and to use these uncertainties as weights in data integration. (c) Global optimization to determine ramp parameters for multiple InSAR tracks, minimizing systematic biases in the solution. (d) Averaging InSAR LOS data within small grid cells, then combining the de-ramped InSAR data with interpolated GNSS velocities to solve for the 3-D deformation field in each grid via least-squares regression. We have applied this method to integrate GNSS and InSAR data for studying 3-D crustal deformation in California and western Nevada [Shen and Liu, 2025]. In this study, we further extend the approach to incorporate UAVSAR data, enabling an integrated solution for crustal deformation with a particular focus on estimating creep rates along faults that exhibit interseismic creep in California.

Since 2009, NASA’s airborne UAVSAR program has been systematically mapping the entire San Andreas Fault (SAF) system. UAVSAR’s optimized viewing geometry and very high spatial resolution make it possible to capture near-fault deformation with exceptional accuracy. Our time series analysis of UAVSAR data from the central SAF reveals localized deformation associated with fault creep, resolving spatial variations along strike at a resolution of ~6 m. We are expanding our analysis to include UAVSAR stacks along the SAF, particularly over known creeping fault segments. We process the UAVSAR data using the JPL/Caltech InSAR Scientific Computing Environment (ISCE) software [Rosen et al., 2012]. The resulting UAVSAR interferograms are then analyzed in a time series framework to estimate average line-of-sight rates and uncertainties, using an in-house variant of the Small Baseline Subset InSAR time series analysis approach [Liu et al., 2019; Shen and Liu, 2020]. The UAVSAR data are treated in a manner consistent with other InSAR datasets, removing orbital ramps using GNSS constraints, and jointly analyzed with GNSS and InSAR data to generate the integrated 3-D deformation field and fault creep rate estimates. The results will be presented at the meeting.

Key Words
GNSS, InSAR, UAVSAR, deformation, fault creep, California

Citation
Shen, Z., & Liu, Z. (2025, 09). GNSS/InSAR/UAVSAR Integration for 3-D Deformation Field and fault creep rates in California. Poster Presentation at 2025 SCEC Annual Meeting.

Related Projects & Working Groups
Tectonic Geodesy