A large-scale seismic risk approach accounting for local site effects and modelling of building exposure based on open-access datasets

This study proposes an enhanced macroseismic framework for regional seismic risk assessment that accounts for litho-stratigraphic site effects and refines building exposure modelling using open-access spatial datasets. The methodology is applied to the Campania region in southern Italy, combining official census data with high-resolution building height estimates to disaggregate structural typologies into three classes: low-rise (1-3 storeys), mid-rise (4-7 storeys), and high-rise (≥8 storeys), associated with distinct vibration period ranges. In addition, the year of construction and the conservation status of the buildings are considered to refine the vulnerability assessment. Seismic hazard is quantified through period-dependent spectral acceleration, which is then converted to macroseismic intensity. The results reveal significant spatial variability in damage scenarios and repair costs, driven by both structural typology and site conditions. Metropolitan areas exhibit the highest vulnerability and economic impact, with site amplification increasing estimated regional repair costs by over 60%. The proposed GIS-compatible methodology offers a replicable and policy-relevant tool for supporting seismic risk mitigation, urban resilience planning, and targeted retrofitting strategies.

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Publication Details

Journal
International Journal of Disaster Risk Reduction
Published
2025-11-28
DOI
https://doi.org/10.1016/j.ijdrr.2025.105936
Citations
1
Primary Topic
Seismic Performance and Analysis
Type
article
Field-Weighted Citation Impact
0.95
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article

A large-scale seismic risk approach accounting for local site effects and modelling of building exposure based on open-access datasets

Angela Stefania Bergantino, Gianfranco Urciuoli, Gaetano Falcone, Anna d’Onofrio et al.
1 citations
International Journal of Disaster Risk Reduction
Seismic Performance and Analysis
0.95
article

A large-scale seismic risk approach accounting for local site effects and modelling of building exposure based on open-access datasets

Angela Stefania Bergantino, Gianfranco Urciuoli, Gaetano Falcone, Anna d’Onofrio, Mario Intini
article en
1 citations

Abstract

This study proposes an enhanced macroseismic framework for regional seismic risk assessment that accounts for litho-stratigraphic site effects and refines building exposure modelling using open-access spatial datasets. The methodology is applied to the Campania region in southern Italy, combining official census data with high-resolution building height estimates to disaggregate structural typologies into three classes: low-rise (1-3 storeys), mid-rise (4-7 storeys), and high-rise (≥8 storeys), associated with distinct vibration period ranges. In addition, the year of construction and the conservation status of the buildings are considered to refine the vulnerability assessment. Seismic hazard is quantified through period-dependent spectral acceleration, which is then converted to macroseismic intensity. The results reveal significant spatial variability in damage scenarios and repair costs, driven by both structural typology and site conditions. Metropolitan areas exhibit the highest vulnerability and economic impact, with site amplification increasing estimated regional repair costs by over 60%. The proposed GIS-compatible methodology offers a replicable and policy-relevant tool for supporting seismic risk mitigation, urban resilience planning, and targeted retrofitting strategies.

International Journal of Disaster Risk ReductionVol. 132
Ingegneria dei Trasporti (Italy) (IT), University of Bari Aldo Moro (IT), University of Naples Federico II (IT)
Openalex Percentile: Top 19%
Seismic Performance and Analysis
0.95
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A large-scale seismic risk approach accounting for local site effects and modelling of building exposure based on open-access datasets — Angela Stefania Bergantino, Gianfranco Urciuoli, et al. · International Journal of Disaster Risk Reduction (2025) | TGRS Research Map | TGRS