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Next Generation Seismic Detection

Date: 4/26/2019

Time: 8:30 AM to 9:45 AM

Room: Elliott Bay

A range of new technologies are revolutionizing how we can detect and characterize seismic events. These include the use of new types of sensors to record motion, as well as new algorithms to process the geophysical data that they generate. Real-time processing of geodetic data is now the norm as the number of GNSS receivers streaming continuous data is steadily increasing. Tens of millions of smartphones equipped with both GNSS and accelerometer sensors have been deployed throughout the western US, while hundreds of millions exist throughout tectonically regions globally, and these are increasingly being harnessed in myriad new ways through crowd-sourcing. Seismic detection by voice- and shaking-activated Internet of Things offer to push sensor density far higher still. Machine learning algorithms are being applied to a wide variety of geophysical data and are improving our capability to detect events of interest. We invite contributions from researchers developing new and innovative ways to detect and characterize seismic events.

Conveners

Timothy Melbourne, Pacific Northwest Geodetic Array/Central Washington University (tim@geology.cwu.edu)
Richard Allen, Berkeley Seismological Laboratory (rallen@berkeley.edu)
Gavin P. Hayes, National Earthquake Information Center/U.S. Geological Survey (ghayes@usgs.gov)
Raymond J. Willemann, Air Force Research Laboratory (raywillemann@gmail.com)   
G. Eli Baker, Air Force Research Laboratory (glenn.baker.3@us.af.mil)

Oral Presentations