Using MEMS Sensors and Distributed Sensing For a Rapid Array Mobilization Program (RAMP) Following the M8.8 Maule, Chile Earthqu

Using MEMS Sensors and Distributed Sensing For a Rapid Array Mobilization Program (RAMP) Following the M8.8 Maule, Chile Earthquake Figure 1: Left: Accelerograms from a M5.1 aftershock of the 27 February 2010 M8.8 Maule, Chile earthquake recorded on QCN stations in the Bio Bio region. Top right: Number of earthquakes and cumulative number of QCN stations installed versus days after the mainshock. Bottom right: Shake map produced using QCN records to locate and estimate the magnitude of the aftershock.
The Quake-Catcher Network (QCN) exploits recent advances in sensing technologies and distributed sensing techniques. Micro-ElectroMechanical Systems (MEMS) triaxial accelerometers are very low cost and interface to any desktop computer via USB cable enabling dense strong motion observations. Shake table tests show the MEMS accelerometers record high-fidelity seismic data and provide linear phase and amplitude response over a wide frequency range. Volunteer sensing using distributed computing techniques provides a mechanism to expand strong-motion seismology with minimal infrastructure costs, while promoting community participation in science. QCN has approximately 2000 participants worldwide that collect seismic data using a variety of MEMS sensors internal and external to computers. Distributed sensing allows for rapid transfer of metadata from participating stations, including data used to rapidly determine the magnitude and location of an earthquake. Trigger metadata are received with average data latencies between 3-7 seconds; the larger data latencies are correlated with greater server-station distances. Trigger times, wave amplitude, and station information are currently uploaded to the server for each trigger. Following the 27 February 2010 M8.8 earthquake in Maule, Chile we initiated a QCN Rapid Aftershock Mobilization Program (RAMP) and installed 100 USB sensors to record aftershocks. The USB accelerators were deployed mainly in regions directly affected by the mainshock and were densely concentrated around ConcepciÃ3n. Using this data, we refined our triggering and event detection algorithms and tested, retrospectively, whether the network can rapidly and accurately identify the loca- tion and magnitude of the moderate to large aftershocks (M>4). Figure 1 illustrates QCN’s ability to grow rapidly, record large aftershocks, and produce useful results such as earthquake locations and ShakeMaps. These results suggest that MEMS sensors installed in homes, schools, and offices provide a way to dramatically increase the density of strong motion observations for use in earthquake early warning. With QCN’s low-latency real-time data collection strategy, future investigations with next- generation sensors will yield data pertinent to ground shaking, earthquake location, and rupture mechanics in near real-time.
</p><p>Cochran, E.S., J.F. Lawrence, C. Christensen, and R. Jakka, The Quake-Catcher Network: Citizen science expanding seismic horizons, Seismol. Res. Lett., 80, 26-30,2009.
</p><p>Cochran E., Lawrence J., Christensen C., Chung A., A novel strong-motion seismic network for community participation in earthquake monitoring, IEEE Inst & Meas, 12, 6, 8-15, 2009.
</p><p>Acknowledgements: This work was preformed with support from NSF-EAR1035919, NSF-GEO0753435, and an IRIS subaward. We thank the thousands of volunteer participants who make the Quake-Catcher Network possible.</p>


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