29 Aug 2023
 | 29 Aug 2023
Status: this preprint is currently under review for the journal NHESS.

A dense MEMS-based seismic network in populated areas: rapid estimation of exposure maps in Trentino (NE Italy)

Davide Scafidi, Alfio Viganò, Jacopo Boaga, Valeria Cascone, Simone Barani, Daniele Spallarossa, Gabriele Ferretti, Mauro Carli, and Giancarlo De Marchi

Abstract. The MEMS-based seismic network of Trentino (NE Italy) consists of 76 low-cost accelerometers installed close to inhabited areas. These sensors have a suitable sensitivity to detect moderate-to-strong earthquakes but are able to record even weaker seismicity. The densely distributed peak ground acceleration values recorded by MEMS and other types of stations are integrated within the existing seismic monitoring procedure in order to automatically obtain a complete set of strong motion parameters a few minutes after the origin time. The exposure for resident population and critical buildings is estimated by quantifying the different levels of shaking, which is expressed according to the Mercalli-Cancani-Sieberg intensity scale. These types of results, summarized in synthetic PDF (Portable Document Format) documents, can be useful for civil protection purposes to timely evaluate the state of emergency after a strong earthquake and to choose how and where activate first aid measures and targeted structural monitoring.

Davide Scafidi et al.

Status: open (until 15 Oct 2023)

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Davide Scafidi et al.

Davide Scafidi et al.


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Short summary
Our manuscript concerns the use of a dense network of low-cost seismic accelerometers in populated areas to achieve rapid and reliable estimation of exposure maps in Trentino (NE Italy). These additional data, in conjunction with the automatic monitoring procedure, allow us to obtain dense measurements which only rely on actual recorded data, avoiding the use of ground motion prediction equations. This leads to a more reliable picture of the actual ground shaking.