Allen CV
Seismo Lab
Earth & Planetary
UC Berkeley

Rapid Earthquake Characterization Using MEMS Accelerometers and Volunteer Hosts Following the M 7.2 Darfield, New Zealand, Earthquake

Jesse F. Lawrence, Elizabeth S. Cochran, Angela Chung, Anna Kaiser, Carl M. Christensen, Richard Allen, Jack W. Baker, Bill Fry, Thomas Heaton, Deborah Kilb, Monica D. Kohler, and Michela Taufer

Stanford University, U.S. Geological Survey, GNS Science, University of California, Berkeley, California Institute of Technology, Scripps Institute of Oceanography, University of Delaware

Bull. Seismo. Soc. Am. , 104, 184-192 doi: 10.1785/0120120196, 2014.
Download a reprint: LawrenceEtAl-QuakeCatcherNewZealand-BSSA-2014.pdf

We test the feasibility of rapidly detecting and characterizing earthquakes with the Quake-Catcher Network (QCN) that connects low-cost microelectromechanical systems accelerometers to a network of volunteer-owned, Internet-connected computers. Following the 3 September 2010 M 7.2 Darfield, New Zealand, earthquake we installed over 180 QCN sensors in the Christchurch region to record the aftershock sequence. The sensors are monitored continuously by the host computer and send trigger reports to the central server. The central server correlates incoming triggers to detect when an earthquake has occurred. The location and magnitude are then rapidly estimated from a minimal set of received ground-motion parameters. Full seismic time series are typically not retrieved for tens of minutes or even hours after an event. We benchmark the QCN real-time detection performance against the GNS Science GeoNet earthquake catalog. Under normal network operations, QCN detects and characterizes earthquakes within 9.1 s of the earthquake rupture and determines the magnitude within 1 magnitude unit of that reported in the GNS catalog for 90% of the detections.