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http://hdl.handle.net/2122/14885
Authors: | Oliveti, Ilaria* Faenza, Licia* Michelini, Alberto* |
Title: | INGe: Intensity-ground motion dataset for Italy | Journal: | Annals of Geophysics | Series/Report no.: | 1/65 (2022) | Publisher: | INGV | Issue Date: | 2022 | DOI: | 10.4401/ag-8709 | Keywords: | Ground motion Macroseismic intensity Earthquakes Italy Dataset |
Subject Classification: | Solid Earth | Abstract: | In this paper we present an updated and homogeneous earthquake dataset for Italy compiled by joining the intensities available in the Italian Macroseismic Database DBMI15 and the peak ground motion (PGM) parameters present in the Engineering Strong-Motion (ESM) accelerometric data bank. The database has been compiled through an extensive procedure of evaluation and revision based on two main steps: 1) the selection of the earthquakes in DBMI15 with homogeneous macroseismic intensities in terms of data sources and 2) the extraction of all the localities reporting intensity data which are located within 3 km from the accelerograph stations that recorded the data. The final dataset includes 519 intensity-PGM data pairs from 65 earthquakes and 227 stations in the time span 1972–2016. The reported intensities are expressed either in the Mercalli-Cancani-Sieberg (MCS) or the European macroseismic (EMS-98) scales. The events are characterized by magnitudes in the range 4.1–6.8 and depths in the range 0–55 km. Here, we illustrate the data collection and the properties of the database in terms of recording, event and station distributions as well as macroseismic intensity points. Furthermore, we discuss the most relevant features of engineering interest showing several statistics with reference to the most significant metadata (such as moment magnitude, several distance metrics, style of faulting etc). The dataset is expected to be useful for benchmarking existing and for developing new ground motion intensity conversion equations offering a common basis, and sparing the time and effort required for assembling to the interested researchers. The dataset is available at https://zenodo.org/record/4623732#.YNX-AZMzbdc. |
Appears in Collections: | Article published / in press |
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File | Description | Size | Format | |
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8709-Article Text-28535-1-10-20220324.pdf | Open Access published article | 4.01 MB | Adobe PDF | View/Open |
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