A Network Inversion Filter combining GNSS and InSAR for tectonic slip modeling. Issue 3 (11th March 2016)

• Record Type: Journal Article
• Authors: Bekaert, D. P. S.; Segall, P.; Wright, T. J.; Hooper, A. J.
• Is Part Of: Journal of geophysical research. Volume 121:Issue 3(2016:Mar.)
• Page Start: 2069
• Page End: 2086
• Publication Date: 2016-03-11
• Subjects: NIF -- transient -- detection -- geodesy -- synthetic aperture radar -- Kalman filtering; Geomagnetism -- Periodicals; Geochemistry -- Periodicals; Geophysics -- Periodicals; Earth sciences -- Periodicals; 551.1
• DOI: 10.1002/2015JB012638
• Languages: English
• ISSNs: 2169-9313

Abstract

Abstract: Studies of the earthquake cycle benefit from long‐term time‐dependent slip modeling, as it can be a powerful means to improve our understanding on the interaction of earthquake cycle processes such as interseismic, coseismic, post seismic, and aseismic slip. Observations from Interferometric Synthetic Aperture Radar (InSAR) allow us to model slip at depth with a higher spatial resolution than when using Global Navigation Satellite Systems (GNSS) alone. While the temporal resolution of InSAR has typically been limited, the recent fleet of SAR satellites including Sentinel‐1, COSMO‐SkyMED, and RADARSAT‐2 permits the use of InSAR for time‐dependent slip modeling at intervals of a few days when combined. With the vast amount of SAR data available, simultaneous data inversion of all epochs becomes challenging. Here we expanded the original network inversion filter to include InSAR observations of surface displacements in addition to GNSS. In the Network Inversion Filter (NIF) framework, geodetic observations are limited to those of a given epoch, with a stochastic model describing slip evolution over time. The combination of the Kalman forward filtering and backward smoothing allows all geodetic observations to constrain the complete observation period. Combining GNSS and InSAR allows modeling of time‐dependent slip at unprecedented spatial resolution. We validate the approach with a simulation of the 2006 Guerrero slow slip event. We highlight the importance of including InSAR covariance information and demonstrate that InSAR provides an additional constraint on the spatial extent of the slow slip. Key Points: Adapted Network Inversion Filter allows for time‐dependent slip modeling of GNSS and InSAR High spatial resolution of InSAR complements high temporal resolution of GNSS InSAR variance‐covariance information should not be neglected during tectonic modeling