Seismic noise characterization of broad-band stations in the Italian region using power spectral density: a frequency, spatial and statistical analysis
Year: 2025
Type: article
Abstract: SUMMARY Currently, there are few studies in the literature on the sources and power distribution of background seismic noise in Italy. In this research, the seismic noise recorded by 233 broad-band seismic stations of the Italian Seismic Network, operating continuously from 2015 to 2018, was investigated. Starting from the average Power Spectral Density calculated for each selected station, the seismic noise powers in four subsets from 0.025 to 30 Hz frequency bands were analysed. Using the Inverse Distance Weighted interpolation method, the background noise distribution across the entire Italian territory was mapped, producing noise interpolation maps for each of the four frequency bands. Additionally, regional seismic noise models and local anomalies for each subset of the frequency bands were found by applying 2-D moving average spatial filtering techniques. Furthermore, a first attempt of linear regression analysis is performed to investigate potential relationships between seismic noise powers and geographical parameters (site elevation and minimal station–coast distance) and the role of meteorological parameters such as rainfall. The large data set enabled a comprehensive assessment of the main characteristics and sources of seismic noise across the network. One can thus know the distribution of noise levels in the Italian territory and in particular study their predominant sources related to natural and anthropic vibrations. Finally, to support the analysis, a comparison between the seismic noise maps and the completeness magnitude map was carried out, highlighting the effectiveness of the national seismic network.
DOI: 10.1093/gji/ggaf168
Authors: M Catania, A Figlioli, G Vitale, A D’Alessandro
Language: English
Topic: Seismic Waves and Analysis
Subfield: Geophysics
Field: Earth and Planetary Sciences
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,416
OpenAlex ID: W4410217690
