INGe: Intensity-ground motion data set for Italy

Main Article Content

Ilaria Oliveti
Licia Faenza
Alberto Michelini

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.

Article Details

How to Cite
Oliveti, I., Faenza, L. and Michelini, A. (2022) “INGe: Intensity-ground motion data set for Italy”, Annals of Geophysics, 65(1), p. DM102. doi: 10.4401/ag-8709.
Section
Data and Methods

Most read articles by the same author(s)