Big data seismology
The discipline of seismology is based on observations of ground motion that are inherently
undersampled in space and time. Our basic understanding of earthquake processes and our …
undersampled in space and time. Our basic understanding of earthquake processes and our …
SMART subsea cables for observing the earth and ocean, mitigating environmental hazards, and supporting the blue economy
The Joint Task Force, Science Monitoring And Reliable Telecommunications (JTF SMART)
Subsea Cables, is working to integrate environmental sensors for ocean bottom …
Subsea Cables, is working to integrate environmental sensors for ocean bottom …
Deep learning for laboratory earthquake prediction and autoregressive forecasting of fault zone stress
Earthquake forecasting and prediction have long and in some cases sordid histories but
recent work has rekindled interest based on advances in early warning, hazard assessment …
recent work has rekindled interest based on advances in early warning, hazard assessment …
Magnitude estimation and ground motion prediction to harness fiber optic distributed acoustic sensing for earthquake early warning
Earthquake early warning (EEW) systems provide seconds to tens of seconds of warning
time before potentially-damaging ground motions are felt. For optimal warning times, seismic …
time before potentially-damaging ground motions are felt. For optimal warning times, seismic …
Great expectations for earthquake early warnings on the United States West Coast
Abstract In October 2019, California became the first state in the United States to fully
activate a public earthquake early warning system—ShakeAlert®—managed by the US …
activate a public earthquake early warning system—ShakeAlert®—managed by the US …
DeepShake: Shaking intensity prediction using deep spatiotemporal RNNs for earthquake early warning
We propose a deep spatiotemporal recurrent neural network, DeepShake, to project future
shaking intensity directly from current ground‐motion observations. DeepShake is a network …
shaking intensity directly from current ground‐motion observations. DeepShake is a network …
Cumulative absolute velocity prediction for earthquake early warning with deep learning
Y Wang, Q Zhao, K Qian, Z Wang… - Computer‐Aided Civil …, 2024 - Wiley Online Library
A rapid and accurate estimate of earthquake damage is a key component in a successful
earthquake early warning (EEW) system. The cumulative absolute velocity (CAV) is an …
earthquake early warning (EEW) system. The cumulative absolute velocity (CAV) is an …
Peak ground acceleration prediction for on-site earthquake early warning with deep learning
Y Liu, Q Zhao, Y Wang - Scientific reports, 2024 - nature.com
Rapid and accurate prediction of peak ground acceleration (PGA) is an important basis for
determining seismic damage through on-site earthquake early warning (EEW). The current …
determining seismic damage through on-site earthquake early warning (EEW). The current …
New methodology for unbiased ground‐motion intensity conversion equations
M Gallahue, N Abrahamson - Bulletin of the …, 2023 - pubs.geoscienceworld.org
Ground‐motion intensity conversion equations (GMICEs) allow for conversions between
ground‐motion amplitude and shaking intensity. The current methods used to develop …
ground‐motion amplitude and shaking intensity. The current methods used to develop …
Early warning for great earthquakes from characterization of crustal deformation patterns with deep learning
Abstract Although infrequent, large (Mw7. 5+) earthquakes can be extremely damaging and
occur on subduction and intraplate faults worldwide. Earthquake early warning (EEW) …
occur on subduction and intraplate faults worldwide. Earthquake early warning (EEW) …