Showing papers by "Howard A. Zebker published in 2002"

Fault Slip Distribution of the 1999 Mw 7.1 Hector Mine, California, Earthquake, Estimated from Satellite Radar and GPS Measurements

Abstract: We use a combination of satellite radar and GPS data to estimate the slip distribution of the 1999 M w 7.1 Hector Mine Earthquake, a right-lateral strikeslip earthquake that occurred on a northwest–southeast striking fault in the southern California Mojave Desert. The data include synthetic aperture radar interferograms (InSAR) from both ascending and descending orbits, radar amplitude image offset fields (SARIO) for both ascending and descending azimuth directions, and campaign GPS observations from 55 stations provided by Agnew et al. (2002). We model the fault with nine segments derived from the field-mapped fault rupture, the SARIO data, and aftershock locations. We first estimate the dip of each fault segment, as well as a single constant strike-slip component across each segment, resulting in an average dip of 83° to the northeast and slip of up to 5.6 m. Then, we fix the optimal fault segment dip, discretize the fault segments into 1.5 km × 1.5 km patches, and solve for the variable slip distribution using a nonnegative least-squares method that includes an appropriate degree of smoothing. Our preferred solution has both right-lateral strike-slip and reverse faulting. The estimated geodetic moment is 5.93 × 10 19 N m ( M w 7.1), similar to seismological estimates, indicating that there are insignificant interseismic and postseismic deformation signals in the data. We find strike-slip displacements of up to 6.0 m and reverse faulting of up to 1.6 m, with the maximum slip located just northwest of the epicenter. Most of the slip is concentrated northwest and south of the epicenter; little slip is found on the northeastern branch of the fault. The SARIO data and our modeling indicate that the amount and extent of surface fault rupture were underestimated in the field.

Phase unwrapping for large SAR interferograms: statistical segmentation and generalized network models

Abstract: Two-dimensional (2-D) phase unwrapping is a key step in the analysis of interferometric synthetic aperture radar (InSAR) data. While challenging even in the best of circumstances, this problem poses unique difficulties when the dimensions of the interferometric input data exceed the limits of one's computational capabilities. In order to deal with such cases, we propose a technique for applying the statistical-cost, network-flow phase-unwrapping algorithm (SNAPHU) of Chen and Zebker (2001) to large datasets. Specifically, we introduce a methodology whereby a large interferogram is partitioned into a set of several smaller tiles that are unwrapped individually and then divided further into independent, irregularly shaped reliable regions. These regions are subsequently assembled into a full unwrapped solution, with the phase offsets between regions computed in a secondary optimization problem whose objective is to maximize the a posteriori probability of the final solution. As this secondary problem assumes the same statistical models as employed in the initial tile-unwrapping stage, the technique results in a solution that approximates the solution that would have been obtained had the full-size interferogram been unwrapped as a single piece. The secondary problem is framed in terms of network-flow ideas, allowing the use of an existing nonlinear solver. Applying the algorithm to a large topographic interferogram acquired over central Alaska, we find that the technique is less prone to unwrapping artifacts than more simple tiling approaches.