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Automated detection of slow slip events by l1 trend filtering
Description : Slow-slip events, characterized by slower fault rupture compared to ordinary earthquakes, have been discovered in tectonic zones worldwide. The discovery of slow-slip events is essential to understanding the behavior of the fault-slip phenomena in the vicinity, including megathrust zones where large earthquakes occur. Short-term slow-slip events with a duration of a few days rarely result in sufficient displacement to be detected visually, so a refined automated detection method is required. In this project, we developed an automatic detection method for short-term slow-slip events using the Global Navigation Satellite System (GNSS) array. The developed method combines a sparse estimation technique called l1 trend filtering with a p-value integration method to provide not only candidate points in time for events, but also confidence in detection. For more information, please see the paper below and obtain the program from the link below.
Details : Keisuke Yano and Masayuki Kano (2022) l1 Trend Filtering-based Detection of Short-term Slow Slip Events: Application to a GNSS Array in Southwest Japan, accepted at Journal of Geophysical Research: Solid Earth
Program : https://github.com/star-e-tohoku/ssedetection
Example of filtering and event detection
