Simultaneous magnitude and slip distribution characterization from high-rate GNSS using deep learning: case studies of the 2021 Mw 7.4 Maduo and 2023 Turkey doublet events

Simultaneous magnitude and slip distribution characterization from high-rate GNSS using deep learning: case studies of the 2021 Mw 7.4 Maduo and 2023 Turkey doublet events

Rapid and accurate characterization of earthquake sources is crucial for mitigating seismic hazards. In this study, based on 18 000 scenario ruptures ranging from Mw 6.4 to Mw 8.3 and corresponding synthetic high-rate Global Navigation Satellite System (HR-GNSS) waveforms, we developed a multibranch...

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Bibliographic Details
Main Authors: Cui, Wenfeng, Chen, Kejie, Wei, Guoguang, Lyu, Mingzhe, Zhu, Feng
Other Authors: Asian School of the Environment
Format: Journal Article
Language:English
Published: 2024
Subjects:
Earth and Environmental Sciences
Large Earthquake
Deeping Learning
Online Access:https://hdl.handle.net/10356/179649

Internet

https://hdl.handle.net/10356/179649

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