InSAR Time Series Analysis of Subtle Transient Crustal Deformation Signals Associated with the 2010 Slow Slip Event at Kilauea, Hawaii

Download or read book InSAR Time Series Analysis of Subtle Transient Crustal Deformation Signals Associated with the 2010 Slow Slip Event at Kilauea, Hawaii written by Jingyi Chen and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: We address here the use of Interferometric Synthetic Aperture Radar (InSAR) to measure and characterize subtle transient deformation events of the Earth's crust. We develop an imaging geodetic method to identify slow slip events (SSEs) that may go unrecognized because they occur in unexpected areas where instrumentation has not been installed. We illustrate our approach by studying Kilauea volcano and imaging the signature of an SSE that occurred in 2010. Kilauea is the youngest and most active volcano on the island of Hawaii. Nearly continuous eruptions along Kilauea's east rift zone over 30 years have built up a large area of accumulated lava on the volcano's south flank. Tectonic extension along the rift zone and gravitational spreading lead to the south flank of Kilauea slipping constantly seaward on a shallowly landward dipping basal decollement fault at rates of up to 10 cm/year. Since 2002, a sequence of SSEs has been observed on Kilauea's south flank using continuous Global Positioning System (GPS) data. SSEs, viewed as fault activity somewhere between steady sliding and a catastrophic earthquake, release energy over a period of hours to months and can lead to crustal deformation on the order of centimeters. The mechanisms behind these SSEs are still poorly understood. High spatial resolution, accurate SSE displacement measurements can help us constrain the depth of slip and understand the SSEs' potential relationship to catastrophic earthquakes and flank failure. The focus of this dissertation is using time series InSAR data to collect and analyze subtle, transient deformation. InSAR time series are commonly used to obtain surface topography and surface motion. The benefits of InSAR are fine spatial resolution and broad ground coverage, both compared to measurements using GPS or other geodetic network alone. We use 49 sets of TerraSAR-X data acquired between August, 2009 and December, 2010 to study the recent Kilauea SSE of February 1, 2010. The TerraSAR-X satellite has a revisit cycle of 11 days, which is relatively short compared to most existing spaceborne radar systems. This shorter revisit cycle makes it possible to collect many measurements over a fixed period of time. Moreover, since a phase cycle in a TerraSAR-X interferogram corresponds to only 1.55 cm line of sight (LOS) deformation, the system is well-suited to monitoring ground deformation on the order of centimeters at Kilauea. The challenge in using X-band InSAR time series to study ground deformation at Kilauea is the very low signal to noise ratio (SNR) of the SSE deformation signal compared to atmospheric noise. We develop a small baseline subset InSAR time series analysis algorithm, which jointly inverts InSAR and GPS data to improve the accuracy of the displacement estimates. This algorithm is suitable for extracting both transient and secular ground deformation on the order of millimeters in the presence of atmospheric noise on the order of centimeters. We obtain high spatial resolution displacement estimates due to the 2010 slow slip event as well as secular motion at Kilauea and demonstrate that the results are consistent with GPS time series over the same period. We also develop an L1-norm based sparse reconstruction algorithm to detect transient events in very noisy InSAR time series. This algorithm is well-suited to detecting unknown transient events using only InSAR time series, particularly when no auxiliary data such as GPS are available. We apply this algorithm to solve for the time of the SSE's occurrence and confirm that the largest jump detected in the TerraSAR-X InSAR time series is temporally and spatially correlated with the 2010 Kilauea SSE. Because phase artifacts due to atmospheric propagation delays in InSAR images frequently degrade the interpretability of the phase signatures of terrain, we further analyze the impact of tropospheric artifacts in InSAR images. We show that tropospheric noise is the primary error source in the X-band InSAR data we processed for the study of the 2010 Kilauea slow slip event. We also address the impact of ionospheric delay artifacts in InSAR images, which are often seen in L-band interferograms.