Imaging cascadia slow slip events with modern interferometric synthetic aperture radar datasets

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The Cascadia subduction zone, famous for its potential to generate very large earthquakes, is one of the regions where slow slip events (SSEs) were first detected. While conventional earthquakes result from fast slip on the faults and take place in a few seconds or minutes, SSEs rupture much more slowly and can take place over weeks or even months. While these seismically silent events themselves are not dangerous, they can significantly alter their surrounding stress field, which in turn, influences the local seismic hazard potential. Although the discovery of SSEs is largely attributed to continuous Global Navigation Satellite System (GNSS) networks, GPS observations alone often lack the spatial resolution needed to model slow slip at depth. Interferometric synthetic aperture radar (InSAR), on the other hand, is an established geodetic technique that can provide dense surface measurements over large areas. However, the application of InSAR techniques to the study of SSEs is severely limited due to low signal to noise ratios (SNR). Since Cascadia has a vast forest cover due to abundant rainfall and mild climate, interferograms formed in this region also have large decorrelated areas. Furthermore, where measurement is possible, the relative small slow slip signal of < 1 cm is overprinted by noises such as atmospheric phase delay which can reach 2 cm standard deviation at large spatial scales, satellite orbit errors, and residual topographic correction errors. Therefore, it is nearly impossible to determine slow slip signals using only a few interferograms. We present here the use of InSAR time-series techniques to measure deformation associated with both slow slip events and inter-SSE velocity in the Cascadia region. Specifically, we address the statistical properties of different interferometric phase components in interferogram stacks and develop time-series approaches that take full advantage of the dense temporal sampling of modern InSAR datasets. We created more than 4500 interferograms with 303 scenes acquired across 96 different dates over the majority of Cascadia region using both Sentinel-1A and 1B data from June 2015 to May 2018. We focus on the 2015-2016 winter Central Cascadia slow slip event and produce two maps: one displays the average annual line-of-sight (LOS) velocity of the region during the three year observation window, and the other shows the LOS magnitude of the SSE surface deformation. The inter-SSE velocity map shows a 8 mm/year difference across the image. The observed inter-SSE velocity does not only reflect tectonic motion, but also any long-term deformation that took place during the observed time period. The observed SSE LOS deformation mostly reflect vertical movements of the surface resulting from the slow slip at depth. The range of SSE LOS deformation is around 1 cm across the studied area. Due to InSAR's insensitivity to north-south motion, combined with large uncertainties of GPS vertical measurements, comparisons between GPS measurements and InSAR measurements are not particularly informative. Nonetheless, projected LOS GPS measurements also shows 1 cm range of SSE deformation with a similar uplift to subsidence deformation pattern. Direct comparisons between GPS and InSAR measurements show that they agree within their respective 1-sigma uncertainty bounds -- for InSAR measurements, these error bounds range from 2 mm to 10 mm. Slip distributions obtained from InSAR measurements show a comparable moment magnitude (Mw 6.6) to slip distributions obtained from GPS horizontal data (also Mw 6.6). However, slip distributions obtained from InSAR measurements are concentrated in an area one third the size of those in GPS solutions with a peak slip magnitude three times the peak slip from GPS measurements. We have also developed software to form and analyze interferograms efficiently. With the anticipation of an ever-growing SAR archive, our effort in producing standardized and user-friendly InSAR products will help maximize InSAR's potential in helping the scientific community better understand our dynamic planet.


Type of resource text
Form electronic resource; remote; computer; online resource
Extent 1 online resource.
Place California
Place [Stanford, California]
Publisher [Stanford University]
Copyright date 2019; ©2019
Publication date 2019; 2019
Issuance monographic
Language English


Author Zheng, Yujie
Degree supervisor Zebker, Howard A
Thesis advisor Zebker, Howard A
Thesis advisor Dunham, Eric
Thesis advisor Schroeder, Dustin
Thesis advisor Segall, Paul, 1954-
Degree committee member Dunham, Eric
Degree committee member Schroeder, Dustin
Degree committee member Segall, Paul, 1954-
Associated with Stanford University, Department of Geophysics.


Genre Theses
Genre Text

Bibliographic information

Statement of responsibility Yujie Zheng.
Note Submitted to the Department of Geophysics.
Thesis Thesis Ph.D. Stanford University 2019.
Location electronic resource

Access conditions

© 2019 by Yujie Zheng
This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).

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