What is it about?
We developed a computational method "RSIT" for alerting possible strong earthquakes by analyzing real-time surface deformation data from the Global Navigation Satellite System or geodetic waveform monitoring, achieving an 83% True Positive Rate and a 0.98% False Positive Rate of earthquake alerting for earthquakes with magnitude larger than or equal to M5.0, based on recent data of five earthquake-prone regions in China, Japan, and Alaska. By combining "unpredictability" and "fluctuation" criteria, this method may help develop early warning systems for alerting possible earthquakes in advance.
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Why is it important?
From a perspective of nonlinear dynamics, we transform high-dimensional information of the global navigation satellite system into one-dimensional dynamics and then detect signals from both "unpredictability" and "instability" of such transformed geodynamics, thus alerting for possible earthquakes.
Perspectives
Our approach represents a preliminary exploration of earthquake alerting from the viewpoint of nonlinear dynamics. Many challenges will still require further investigation before the implementation in future research. Additionally, we acknowledge the existence of various other factors contributing to local surface deformation, such as landslides, engineering blasting, and volcanic eruptions, which could potentially result in false-positive signals in earthquake alerts.
Luonan Chen
University of the Chinese Academy of Sciences
Read the Original
This page is a summary of: Earthquake alerting based on spatial geodetic data by spatiotemporal information transformation learning, Proceedings of the National Academy of Sciences, September 2023, Proceedings of the National Academy of Sciences,
DOI: 10.1073/pnas.2302275120.
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