End-to-End LSTM-Based Earthquake Magnitude Estimation With a Single Station

Cofre, Aaron; Marin, Marcelo; Vasquez Pino,Oscar; Galleguillos, Nicolas; Riquelme, Sebastian; Barrientos, Sergio; "Nestor Becerra Yoma"

Abstract

In this letter, a method based on long short-term memory (LSTM) is presented to address the problem of earthquake magnitude estimation for earthquake early warning (EEW) and tsunami early warning (TW) purposes using a seismic station. An end-to-end-based scheme is adopted, and particular attention is paid to compute the magnitude of seismic events larger than M6 and reduce the effective time for TW. More so, these earthquakes are the ones that cause more fear or uncertainty in the population with the provision of the most significant destructive potential. However, the occurrence of large earthquakes is low, but to counteract the drawback of limited training data, engineered features were also proposed. The earthquake magnitude relative error estimation reported here in experiments with Chilean seismic data was 4.01% and 8.04% with earthquakes M4.0 or larger (up to M8.1) and M4.0 or smaller, respectively, by employing seismic traces in the nearest station to the corresponding seismic event. The average earthquake-nearest station distance was 196 km, and in 26% of the data, this distance was greater than 200 km. These results are competitive with those published elsewhere and suggest the possibility to reduce the time required for EEW and especially TW

Más información

Título de la Revista: IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
Volumen: 19
Editorial: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Fecha de publicación: 2022
URL: https://ieeexplore.ieee.org/abstract/document/9774421