Summer papers 2022 - ShakeRec and RAN
During the summer of 2022 two papers whose I was a co-author have been published!
The first one is “A Machine Learning Approach for the Reconstruction of Ground Shaking Fields in Real Time “ by Simone Francesco Fornasari, Veronica Pazzi, and Giovanni Costa published at BSSA.
The work revolves around the idea of reconstructing the ground shaking maps for an area in real time using sparse data (i.e., the values of the ground motion parameter recorded at each seismic station).
It has applicability in a monitoring environment, complementing traditional methods which rely on ground motion predictions equations and thus require information about the magnitude and location of the event, which are slow to compute: the Italian Department of Civil Protection gets this information (manually revised by INGV operators) on average 12 minutes after an event; on the other hand, the data from the stations are available with a delay of just a few seconds since the data have been recorded.
The station information available in real-time is exploited using a machine learning approach that provides robust results in real-time: despite the hardware at DMG seeming to be the bottleneck, an updated ground shaking map is available every few seconds using the data from the whole Italian accelerometric network (RAN).
I presented an early version of the work at EGU22: I talked about it here.
The second one is “Near-Real-Time Strong Motion Acquisition at National Scale and Automatic Analysis” by Giovanni Costa, Piero Brondi, Laura Cataldi, Stefano Cirilli, Arianna Cuius, Deniz Ertuncay, Piero Falconer, Luisa Filippi, Simone Francesco Fornasari, Veronica Pazzi, and Philippe Turpaud published on Sensors (on the “Advanced Sensor Networks/Seismic Networks and Monitoring for Earthquakes and Phenomena Having a Seismic Signature” special issue). This paper aims to present the Italian Strong Motion Network (RAN), describing its current status, employment, and further developments.