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Joint Inversion of GNSS and InSAR Data for Continuous 3-D Velocity and Strain Rate Fields in Southern California

William E. Holt, Jeonghyeop Kim, & Mradula Vashishtha

Submitted September 11, 2022, SCEC Contribution #12549, 2022 SCEC Annual Meeting Poster #080

We develop a joint inversion algorithm for continuous surface 3-D velocities and associated horizontal strain rate fields. Using a thin-elastic-sheet model, we construct basis functions that represent a response to body-force equivalents embedded within grid cells. The goal of this inversion is to find the best-fit linear combination of these basis functions that predict both GNSS and InSAR measurements. We use the 10-fold cross-validation method and the trade-off curve to determine an “optimal” level of smoothing. The relative weighting for each data set is initially decided based on the number of data points and uncertainties in GNSS data, and it is iteratively updated until the weighted root mean squared error (RMSE) of GNSS data achieves a value ~2 mm/yr. To test this algorithm, we performed synthetic tests. Our goal in these synthetic tests is to recover the full 3-D field associated with a mixture of a complex horizontal interseismic signal and a variable vertical signal. We first used the joint inversion technique to recover an estimate of the continuous 3-D velocity field in southern California using synthetic InSAR and GNSS data. To determine how much information the InSAR is providing for the horizontal component of the interseismic field, we compared results with a solution obtained from the inversion of GNSS data alone. Both of the solutions produced the same value of RMSE of GNSS data. We find that the velocity and strain rate fields inferred from the joint inversion of InSAR and GNSS data are closer to the “true” fields than the solution obtained using GNSS data alone. The result shows that the joint inversion can recover vertical signals well, and the addition of InSAR provides a much higher resolution estimate of the interseismic horizontal strain rate field. Our goal is to use this joint inversion algorithm to provide an estimate of the interseismic strain rate field for southern California that will be contributed to the Community Geodetic Model (CGM).

Key Words
GNSS, InSAR, Joint Inversion, Interseismic Deformation

Holt, W. E., Kim, J., & Vashishtha, M. (2022, 09). Joint Inversion of GNSS and InSAR Data for Continuous 3-D Velocity and Strain Rate Fields in Southern California. Poster Presentation at 2022 SCEC Annual Meeting.

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Tectonic Geodesy