Michelle Guy
I architect, manage, and build highly specialized state-of-the-art scientific software systems. These systems are one of a kind and serve to bring the unique science of the GHSC into real-time operations and produce products for worldwide consumption by scientific communities, emergency responders, government agencies and the general public.
Funding
- Crowd-Sourced Earthquake Detections Integrated with Instrumental Seismic Processing; PI; April 2016; Community for Data Integration, USGS; https://bit.ly/2gxWsX0
- Characterization of Earthquake Damage and Effects Using Social-Media Data; Co-PI; April 2014; Community for Data Integration, USGS
Publications
- Guy, Michelle, Patton, John, Fee, J.M., Hearne, Mike, Martinez, E.M., Ketchum, D., Worden, C.B., Quitoriano, Vince, Hunter, E.J., Smoczyk, G.M., and Schwarz, Stan, 2015, National Earthquake Information Center systems overview and integration: U.S. Geological Survey Open-File Report 2015–1120, 25 p., https://dx.doi.org/10.3133/ofr20151120.
- Patton, J.M., Ketchum, D.C., and Guy, M.R., 2015, An overview of the National Earthquake Information Center acquisition software system, Edge/Continuous Waveform Buffer: U.S. Geological Survey Open-File Report 2015–1174, 10 p., https://dx.doi.org/10.3133/ofr20151174.
- Madison L. Langseth, Michelle Y. Chang, Jennifer Carlino, Daniella D. Birch, Joshua Bradley, R. Sky Bristol, Craig Conzelmann, Robert H. Diehl, Paul Earle, Laura E. Ellison, Anthony L. Everette, Pam Fuller, Janice M. Gordon, David L. Govoni, Michelle R. Guy, Heather S. Henkel, Vivian B. Hutchison, Tim Kern, Frances L. Lightsom, Joseph W. Long, Ryan Longhenry, Todd M. Preston, Stan Smith, Roland J. Viger, Katherine Wesenberg, Eric Wood. (July 2015). “Community for Data Integration 2014 Annual Report”. IPDS number IP-066330.
- Michelle Guy. Paul Earle, Scott Horvath, Jessica Turner, Douglas Bausch, Greg Smoczyk; Association of Computing Machinery (ACM) Significant Interest Group conference on Knowledge Discovery and Data Mining (SIGKDD) workshop on Learning about Emergencies from Social Media (LESI) August 2014: “Social Media Based Earthquake Detection and Characterization”; https://sites.google.com/site/kddlesi2014/program/papers;
- Earle, P.S., D.C. Bowden, and M. Guy (2011) Twitter earthquake detection: earthquake monitoring in a social world. Annals of Geophysics, 54(6), 708-715.
- Guy, M., P. Earle, C. Ostrum, K. Gruchalla and S. Horvath (2010) Integration and dissemination of citizen reported and seismically derived earthquake information via social network technologies. Advances in Intelligent Data Analysis IX Lecture Notes in Computer Science, 6065/2010, 42-53.
Science and Products
U.S. Geological Survey Earthquake Hazards Program decadal science strategy, 2024–33 U.S. Geological Survey Earthquake Hazards Program decadal science strategy, 2024–33
Executive Summary Earthquakes represent one of our Nation’s most significant and costly natural hazards, with estimated annual loses from earthquakes close to $15 billion in 2023. Over the past two centuries, 37 U.S. States have experienced an earthquake exceeding a magnitude of 5, and 50 percent of States have a significant potential for future damaging shaking; these statistics speak...
Authors
Gavin P. Hayes, Annemarie S. Baltay Sundstrom, William D. Barnhart, Michael L. Blanpied, Lindsay A. Davis, Paul S. Earle, Edward H. Field, Jill M. Franks, Douglas D. Given, Ryan D. Gold, Christine A Goulet, Michelle M. Guy, Jeanne L. Hardebeck, Nico Luco, Frederick Pollitz, Adam T. Ringler, Katherine M. Scharer, Steven Sobieszczyk, Valerie I. Thomas, Cecily J. Wolfe
Seismic monitoring during crises at the NEIC in support of the ANSS Seismic monitoring during crises at the NEIC in support of the ANSS
Over the past two decades, the U.S. Geological Survey (USGS) National Earthquake Information Center (NEIC) has overcome many operational challenges. These range from minor disruptions, such as power outages, to significant operational changes, including system reconfiguration to handle unique earthquake sequences and the need to handle distributed work during a pandemic. Our ability to...
Authors
Paul S. Earle, Harley M. Benz, William L. Yeck, Gavin P. Hayes, Michelle M. Guy, John Patton, David Kragness, David B. Mason, Brian Shiro, Emily Wolin, John Bellini, Jana Pursley, Robert Lorne Sanders
Leveraging deep learning in global 24/7 real-time earthquake monitoring at the National Earthquake Information Center Leveraging deep learning in global 24/7 real-time earthquake monitoring at the National Earthquake Information Center
Machine‐learning algorithms continue to show promise in their application to seismic processing. The U.S. Geological Survey National Earthquake Information Center (NEIC) is exploring the adoption of these tools to aid in simultaneous local, regional, and global real‐time earthquake monitoring. As a first step, we describe a simple framework to incorporate deep‐learning tools into NEIC...
Authors
William L. Yeck, John Patton, Zachary E. Ross, Gavin P. Hayes, Michelle M. Guy, Nicholas Ambruz, David R. Shelly, Harley M. Benz, Paul S. Earle
GLASS3: A standalone multi-scale seismic detection associator GLASS3: A standalone multi-scale seismic detection associator
The automated global real-time association of phase picks into seismic sources comes with unique challenges when simultaneously monitoring at local, regional and global scales. High spatial variability in seismic station density, transitory seismic data availability, and time-varying noise characteristics of individual stations must be considered in the design of an associator that is...
Authors
William L. Yeck, John Patton, Caryl E. Johnson, David Kragness, Harley M. Benz, Paul S. Earle, Michelle M. Guy, Nicholas Ambruz
Limiting the effects of earthquakes on gravitational-wave interferometers Limiting the effects of earthquakes on gravitational-wave interferometers
Ground-based gravitational wave interferometers such as the Laser Interferometer Gravitational-wave Observatory (LIGO) are susceptible to ground shaking from high-magnitude teleseismic events, which can interrupt their operation in science mode and significantly reduce their duty cycle. It can take several hours for a detector to stabilize enough to return to its nominal state for...
Authors
Michael Coughlin, Paul S. Earle, Jan Harms, Sebastien Biscans, Christopher Buchanan, Eric Coughlin, Fred Donovan, Jeremy Fee, Hunter Gabbard, Michelle M. Guy, Nikhil Mukund, Matthew Perry
Community for Data Integration 2016 annual report Community for Data Integration 2016 annual report
The Community for Data Integration (CDI) represents a dynamic community of practice focused on advancing science data and information management and integration capabilities across the U.S. Geological Survey and the CDI community. This annual report describes the various presentations, activities, and outcomes of the CDI monthly forums, working groups, virtual training series, and other...
Authors
Madison L. Langseth, Leslie Hsu, Jon Amberg, Norman Bliss, Andrew R. Bock, Rachel T. Bolus, R. Sky Bristol, Katherine J. Chase, Theresa M. Crimmins, Paul S. Earle, Richard Erickson, A. Lance Everette, Jeff T. Falgout, John Faundeen, Michael N. Fienen, Rusty Griffin, Michelle R. Guy, Kevin D. Henry, Nancy J. Hoebelheinrich, Randall J. Hunt, Vivian B. Hutchison, Drew A. Ignizio, Dana M. Infante, Catherine Jarnevich, Jeanne M. Jones, Tim Kern, Scott Leibowitz, Francis L. Lightsom, R. Lee Marsh, S. Grace McCalla, Marcia McNiff, Jeffrey T. Morisette, John C. Nelson, Tamar Norkin, Todd M. Preston, Alyssa Rosemartin, Roy Sando, Jason T. Sherba, Richard P. Signell, Benjamin M. Sleeter, Eric T. Sundquist, Colin B. Talbert, Roland J. Viger, Jake F. Weltzin, Sharon Waltman, Marc Weber, Daniel J. Wieferich, Brad Williams, Lisamarie Windham-Myers
Crowd-Sourced Earthquake Detections Integrated into Seismic Processing
The goal of this project is to improve the USGS National Earthquake Information Center’s (NEIC) earthquake detection capabilities through direct integration of crowd-sourced earthquake detections with traditional, instrument-based seismic processing. During the past 6 years, the NEIC has run a crowd-sourced system, called Tweet Earthquake Dispatch (TED), which rapidly detects earthquakes...
Characterization of Earthquake Damage and Effects Using Social Media Data
People in the locality of earthquakes are publishing anecdotal information about the shaking within seconds of their occurrences via social network technologies, such as Twitter. In contrast, depending on the size and location of the earthquake, scientific alerts can take between two to twenty minutes to publish. The goals of this project are to assess earthquake damage and effects...
Science and Products
U.S. Geological Survey Earthquake Hazards Program decadal science strategy, 2024–33 U.S. Geological Survey Earthquake Hazards Program decadal science strategy, 2024–33
Executive Summary Earthquakes represent one of our Nation’s most significant and costly natural hazards, with estimated annual loses from earthquakes close to $15 billion in 2023. Over the past two centuries, 37 U.S. States have experienced an earthquake exceeding a magnitude of 5, and 50 percent of States have a significant potential for future damaging shaking; these statistics speak...
Authors
Gavin P. Hayes, Annemarie S. Baltay Sundstrom, William D. Barnhart, Michael L. Blanpied, Lindsay A. Davis, Paul S. Earle, Edward H. Field, Jill M. Franks, Douglas D. Given, Ryan D. Gold, Christine A Goulet, Michelle M. Guy, Jeanne L. Hardebeck, Nico Luco, Frederick Pollitz, Adam T. Ringler, Katherine M. Scharer, Steven Sobieszczyk, Valerie I. Thomas, Cecily J. Wolfe
Seismic monitoring during crises at the NEIC in support of the ANSS Seismic monitoring during crises at the NEIC in support of the ANSS
Over the past two decades, the U.S. Geological Survey (USGS) National Earthquake Information Center (NEIC) has overcome many operational challenges. These range from minor disruptions, such as power outages, to significant operational changes, including system reconfiguration to handle unique earthquake sequences and the need to handle distributed work during a pandemic. Our ability to...
Authors
Paul S. Earle, Harley M. Benz, William L. Yeck, Gavin P. Hayes, Michelle M. Guy, John Patton, David Kragness, David B. Mason, Brian Shiro, Emily Wolin, John Bellini, Jana Pursley, Robert Lorne Sanders
Leveraging deep learning in global 24/7 real-time earthquake monitoring at the National Earthquake Information Center Leveraging deep learning in global 24/7 real-time earthquake monitoring at the National Earthquake Information Center
Machine‐learning algorithms continue to show promise in their application to seismic processing. The U.S. Geological Survey National Earthquake Information Center (NEIC) is exploring the adoption of these tools to aid in simultaneous local, regional, and global real‐time earthquake monitoring. As a first step, we describe a simple framework to incorporate deep‐learning tools into NEIC...
Authors
William L. Yeck, John Patton, Zachary E. Ross, Gavin P. Hayes, Michelle M. Guy, Nicholas Ambruz, David R. Shelly, Harley M. Benz, Paul S. Earle
GLASS3: A standalone multi-scale seismic detection associator GLASS3: A standalone multi-scale seismic detection associator
The automated global real-time association of phase picks into seismic sources comes with unique challenges when simultaneously monitoring at local, regional and global scales. High spatial variability in seismic station density, transitory seismic data availability, and time-varying noise characteristics of individual stations must be considered in the design of an associator that is...
Authors
William L. Yeck, John Patton, Caryl E. Johnson, David Kragness, Harley M. Benz, Paul S. Earle, Michelle M. Guy, Nicholas Ambruz
Limiting the effects of earthquakes on gravitational-wave interferometers Limiting the effects of earthquakes on gravitational-wave interferometers
Ground-based gravitational wave interferometers such as the Laser Interferometer Gravitational-wave Observatory (LIGO) are susceptible to ground shaking from high-magnitude teleseismic events, which can interrupt their operation in science mode and significantly reduce their duty cycle. It can take several hours for a detector to stabilize enough to return to its nominal state for...
Authors
Michael Coughlin, Paul S. Earle, Jan Harms, Sebastien Biscans, Christopher Buchanan, Eric Coughlin, Fred Donovan, Jeremy Fee, Hunter Gabbard, Michelle M. Guy, Nikhil Mukund, Matthew Perry
Community for Data Integration 2016 annual report Community for Data Integration 2016 annual report
The Community for Data Integration (CDI) represents a dynamic community of practice focused on advancing science data and information management and integration capabilities across the U.S. Geological Survey and the CDI community. This annual report describes the various presentations, activities, and outcomes of the CDI monthly forums, working groups, virtual training series, and other...
Authors
Madison L. Langseth, Leslie Hsu, Jon Amberg, Norman Bliss, Andrew R. Bock, Rachel T. Bolus, R. Sky Bristol, Katherine J. Chase, Theresa M. Crimmins, Paul S. Earle, Richard Erickson, A. Lance Everette, Jeff T. Falgout, John Faundeen, Michael N. Fienen, Rusty Griffin, Michelle R. Guy, Kevin D. Henry, Nancy J. Hoebelheinrich, Randall J. Hunt, Vivian B. Hutchison, Drew A. Ignizio, Dana M. Infante, Catherine Jarnevich, Jeanne M. Jones, Tim Kern, Scott Leibowitz, Francis L. Lightsom, R. Lee Marsh, S. Grace McCalla, Marcia McNiff, Jeffrey T. Morisette, John C. Nelson, Tamar Norkin, Todd M. Preston, Alyssa Rosemartin, Roy Sando, Jason T. Sherba, Richard P. Signell, Benjamin M. Sleeter, Eric T. Sundquist, Colin B. Talbert, Roland J. Viger, Jake F. Weltzin, Sharon Waltman, Marc Weber, Daniel J. Wieferich, Brad Williams, Lisamarie Windham-Myers
Crowd-Sourced Earthquake Detections Integrated into Seismic Processing
The goal of this project is to improve the USGS National Earthquake Information Center’s (NEIC) earthquake detection capabilities through direct integration of crowd-sourced earthquake detections with traditional, instrument-based seismic processing. During the past 6 years, the NEIC has run a crowd-sourced system, called Tweet Earthquake Dispatch (TED), which rapidly detects earthquakes...
Characterization of Earthquake Damage and Effects Using Social Media Data
People in the locality of earthquakes are publishing anecdotal information about the shaking within seconds of their occurrences via social network technologies, such as Twitter. In contrast, depending on the size and location of the earthquake, scientific alerts can take between two to twenty minutes to publish. The goals of this project are to assess earthquake damage and effects...