Mapping social vulnerability to natural hazards in Italy: A suitable tool for risk mitigation strategies. Issue 63 (September 2016)

• Record Type: Journal Article
• Authors: Frigerio, Ivan; De Amicis, Mattia
• Is Part Of: Environmental science & policy. Issue 63(2016:Sep.)
• Page Start: 187
• Page End: 196
• Publication Date: 2016-09
• Subjects: Social vulnerability -- Indicators -- Natural hazards -- Italy -- Mapping vulnerability -- Risk mitigation; Environmental policy -- Periodicals; Environmental sciences -- Periodicals; Environnement -- Politique gouvernementale -- Périodiques; Sciences de l'environnement -- Périodiques; Environmental policy; Environmental sciences; Periodicals; Electronic journals; 363.70561
• DOI: 10.1016/j.envsci.2016.06.001
• Languages: English
• ISSNs: 1462-9011

Abstract

Highlights: Evaluation of the main social vulnerability indicators to natural hazards in Italy. Constructing and mapping social vulnerability index. Results highlight a strong spatial variation of social vulnerability. Applicability, usefulness and policy implications of social vulnerability index. Abstract: Italy is one of the European countries that are most heavily exposed to a wide range of natural hazards, which might cause large economic losses. In this context, the assessment of social vulnerability has an important role for evaluating the capacity of a community to prepare for, respond to and recover from disasters. However there are currently no published studies analysing social vulnerability and its spatial distribution in Italy. Within this framework, this paper aims to apply a proven method for assessing social vulnerability at the national scale, while considering the contribution of the socioeconomic and demographic factors that affect the Italian population. The proposed methodology is based on the Hazard-of-Place Model approach, and uses free and open source software applications (FOSS). Specifically, we selected significant components through Principal Component Analysis and derived their spatial distribution. Using component scores, we derived a social vulnerability index, evaluated its geographic distribution, and performed a cluster analysis on its spatial variation. The analysis identified different spatial patterns across Italy, providing useful information for identifying the communities most likely to experience negative natural disaster impacts due to their socioeconomic and demographic characteristics. This research represents an important contribution to improve the potentiality of risk mitigation strategies and in designing risk custom-made policies.