Enhanced earthquake detection from orbit

Source: Journal of Geophysical Research: Solid Earth

When a major earthquake strikes, nearby seismographs can communicate quick alerts to residents and emergency services that potentially dangerous tremors or tsunamis may be on the way. However, local seismometer measurements are not sufficient to determine the magnitude of the largest earthquakes in real time.

Scientists have harnessed high-resolution measurements of ground displacement from global navigation satellite systems (GNSS), such as GPS, to complement seismometer observations. GNSS data can differentiate between larger earthquakes but is much noisier than data from conventional seismometers, which has limited its contributions to natural hazard applications.

To address noisy data, Dittmann et al. They made two decision choices based on previous GNSS seismology research and machine learning development: they adopted an alternative method for processing geodetic measurements, and they trained a machine learning model to use GNSS sensor data to detect earthquakes. The team trained, validated, and tested the model using data from the National Science Foundation’s Geodetic Facility for Geosciences Archives from 77 earthquakes larger than magnitude 4.5 that occurred over a 20-year period.

When matched with existing GNSS earthquake detection methods, the new model detected more real seismic signals and triggered fewer false alarms. In addition, unlike previous methods, the new model is based on computationally lightweight processing and does not rely on additional corrections to account for false signals.

The researchers suggest that the new model can be widely applied to enhance the role of GNSS sensors in earthquake detection. It also outlines opportunities for future improvement, such as applying more comprehensive data sets to train and validate the model. (Journal of Geophysical Research: Solid Earth, https://doi.org/10.1029/2022JB024854, 2022)

Sarah Stanley, science writer

Citation: Stanley, S. (2022), Enhancing Earthquake Detection from Orbit, EOS, 103, https://doi.org/10.1029/2022EO220550. Posted on December 2, 2022. Text © 2022. AGU. CC BY-NC-ND 3.0 Unless otherwise noted, images are subject to copyright. Any reuse without the express permission of the copyright owner is prohibited. Related

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