Characterizing fault motion using edge detection in radar images

Margaret T. Glasscoe, Jay W. Parker, & Andrea Donnellan

Submitted August 14, 2017, SCEC Contribution #7569, 2017 SCEC Annual Meeting Poster #106

A moderate sized or secondary near-surface fault slip appears in a radar interferogram as a roughly linear feature with cross-section resembling either a step function or a Gaussian-filtered step, called a sigmoid. Building on past work that detects (near-)surface fractures in radar images with missing data from decorrelated patches, we have developed a script that analyzes the neighborhood of each detection to characterize the slip direction, shear width, and sigmoid amplitude.

These indicate a candidate mechanism, characteristic locking depth, and the projected slip at depth from the radar perspective. The values of these are helpful for characterizing dipping oblique and dip slip faults, but interpretation requires additional information.

Maps indicating sense of slip, characteristic depth, and projected amplitude are shown for fault maps derived from UAVSAR data repeat passes that cover the 2010 El Mayor-Cucapah coseismic and post seismic time periods in the Yuha Desert. Additional maps cover the region around the 2014 South Napa earthquake.

Sense of slip shows conjugate near-perpendicular slip patterns of NW-trending right lateral and NE-trending left lateral faults, interlaced. These maps include secondary faults that indicate surface rupture near the center, but deeper locking depths near the ends. Some secondary faults display greater slip close to the main EMC rupture and smaller slip further away.

These maps have potential to guide micro-tectonic analysis of regions near major ruptures, and serve as a guide to emergency response, including infrastructure inspection priority. Inclusion as optional layers in the GeoGateway GoogleMaps-based web service system is in progress.

Key Words
Earthquake fault, interferogram, UAVSAR

Citation
Glasscoe, M. T., Parker, J. W., & Donnellan, A. (2017, 08). Characterizing fault motion using edge detection in radar images. Poster Presentation at 2017 SCEC Annual Meeting.


Related Projects & Working Groups
Tectonic Geodesy