Spatiotemporal Pattern of Social Vulnerability in Italy

Ivan Frigerio; Fabio Carnelli; Marta Cabinio; Mattia De Amicis

doi:10.1007/s13753-018-0168-7

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Article Navigation > International Journal of Disaster Risk Science > 2018 > 9(2): 249-262

Ivan Frigerio, Fabio Carnelli, Marta Cabinio, Mattia De Amicis. Spatiotemporal Pattern of Social Vulnerability in Italy[J]. International Journal of Disaster Risk Science, 2018, 9(2): 249-262. doi: 10.1007/s13753-018-0168-7

Citation:

Ivan Frigerio, Fabio Carnelli, Marta Cabinio, Mattia De Amicis. Spatiotemporal Pattern of Social Vulnerability in Italy[J]. International Journal of Disaster Risk Science, 2018, 9(2): 249-262. doi: 10.1007/s13753-018-0168-7

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Spatiotemporal Pattern of Social Vulnerability in Italy

doi: 10.1007/s13753-018-0168-7

1 Earth and Environmental Sciences Department, University of Milano-Bicocca, 20126 Milan, Italy;
2 Sociology and Social Research Department, University of Milano-Bicocca, 20126 Milan, Italy

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We would like to express our gratitude to the editors and the three anonymous reviewers whose feedback greatly improved the quality of this manuscript. We are also grateful to Professor Douglas L. Johnson (Clark University) for his useful suggestions.

Available Online: 2021-04-26

Abstract

Abstract

Evaluation of social vulnerability (SV) against natural hazards remains a big challenge for disaster risk reduction. Spatiotemporal analysis of SV is important for successful implementation of prevision and prevention measures for risk mitigation. This study examined the spatiotemporal pattern of SV in Italy, and also analyzed socioeconomic factors that may influence how the Italian population reacts to catastrophic natural events. We identified 16 indicators that quantify SV and collected data for the census years 1991, 2001, and 2011. We created a social vulnerability index (SVI) for each year by using principal component analysis outputs and an additive method. Exploratory spatial data analysis, including global and local autocorrelations, was used to understand the spatial patterns of social vulnerability across the country. Specifically, univariate local Moran’s index was performed for the SVI of each of the three most recent census years in order to detect changes in spatial clustering during the whole study period. The original contribution of this Italy case study was to use a bivariate spatial correlation to describe the spatiotemporal correlation between the threes annual SV indices. The temporal analysis shows that the percentage of municipalities with medium social vulnerability in Italy increased from 1991 to 2011 and those with very high social vulnerability decreased. Spatial analysis provided evidence of clusters that maintained significant high values of social vulnerability throughout the study periods. The SVI of many areas in the center and the south of the peninsula remained stable, and the people living there have continued to be potentially vulnerable to natural hazards.
- Bivariate Moran’s index,
- Cluster analysis,
- Italy,
- Natural hazards,
- Social vulnerability

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References(65)

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