A GIS-based approach to identify the spatial variability of social vulnerability to seismic hazard in Italy

Frigerio, I; Ventura, Stefania; Strigaro, Daniele; Mattavelli, M; Amicis, M De; Mugnano, S; Boffi, Marco

doi:10.1016/j.apgeog.2016.06.014

Cited by 136 publications

(101 citation statements)

References 24 publications

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“…Based on a wide range of academic literature of social vulnerability and social inequality to air pollution, major influencing factors of social vulnerability to air pollution were identified and relevant indicators were initially selected (see Table 1) [29,30,34,36,38,41,[48][49][50][51][52]. …”

Section: Datamentioning

confidence: 99%

Mapping Social Vulnerability to Air Pollution: A Case Study of the Yangtze River Delta Region, China

Zhang

Dou

et al. 2017

Sustainability

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Many frequent and severe air pollution incidents have emerged across the vast parts of China recently. The identification of factors and mapping social vulnerability has become extremely necessary for environmental management and sustainable development. However, studies associating social vulnerability with air pollution remain sparse. With reference to research achievements of social vulnerability, this study made a new trial regarding social vulnerability assessment to air pollution. With the projection pursuit cluster (PPC) model, the top three factors contributing to social vulnerability index (SVI) were discovered and SVI and SVI dimensions (susceptibility, exposure, and adaptability) were evaluated. Results revealed that adaptability values are higher than susceptibility and exposure values. SVI is in a poor condition as, for the whole region, most values belong to the high-medium level. High SVI values mainly appear in the northern and the southern ends of study area. SVI in Shanghai is lower than in Jiangsu and Zhejiang provinces. On the scale of prefecture-level city, it can be found that the low-value centers of SVI always occurred in urban core areas. The spatial variation and inequality in social vulnerability provide policy-makers a scientific basis for air pollution prevention and sustainable management.

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Section: Datamentioning

confidence: 99%

Mapping Social Vulnerability to Air Pollution: A Case Study of the Yangtze River Delta Region, China

Zhang

Dou

et al. 2017

Sustainability

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“…Guillard-Gonçalves et al (2015) chose 46 variables to develop a social vulnerability index of 149 civil parishes of Great Lisbon with PCA [34]. Following the hazard-of-place model, used multiple proxy variables to calculate social vulnerability with Factor Analysis (FA) [35]. Mendes (2017) also applied PCA to estimate social vulnerability in the Centre Region of Portugal.…”

Section: Traditional Methods For Social Vulnerability Assessmentmentioning

confidence: 99%

A New Approach to Identify Social Vulnerability to Climate Change in the Yangtze River Delta

Dou

Dai

2017

Sustainability

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This paper explored a new approach regarding social vulnerability to climate change, and measured social vulnerability in three parts: (1) choosing relevant indicators of social vulnerability to climate change; (2) based on the Hazard Vulnerability Similarity Index (HVSI), our method provided a procedure to choose the referenced community objectively; and (3) ranked social vulnerability, exposure, sensitivity, and adaptability according to profiles of similarity matrix and specific attributes of referenced communities. This new approach was applied to a case study of the Yangtze River Delta (YRD) region and our findings included: (1) counties with a minimum and maximum social vulnerability index (SVI) were identified, which provided valuable examples to be followed or avoided in the mitigation planning and preparedness of other counties; (2) most counties in the study area were identified in high exposure, medium sensitivity, low adaptability, and medium SVI; (3) four cities, Shanghai, Nanjing, Suzhou, and Hangzhou were much less vulnerable than others due to their high adaptability; (4) to some extent, there were geographical similarities of SVI, exposure index, sensitivity index, and adaptability index; and (5) the indicator of "Employees in primary industry" related to SVI the most, the indicator of "Renter" related to exposure index (EI) most, the indicator of "Elderly" related to sensitivity index (SI) the most, and the indicator of "Urban residents" relates to adaptability index (AI) most. These results can help decision makers find the focus of their mitigation works, where the efficient of practices will then be improved.

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“…Actually, most of analyses use data from national census to build social vulnerability indices (Cutter et al 2000;Wu et al 2002;Chakraborty et al, 2005;Fekete, 2009;Guillard-Gonçalves et al, 2014, Frigerio et al, 2016. Some indicators repeatedly appear in these analyses such as poverty, age, ethnicity and disabilities (Table 1).…”

Section: Construction and Organisation Of The Sivimentioning

confidence: 99%

Improvement of an index oriented methodology for consequence analysis of natural hazards: application to the Upper Guil Catchment (Southern French Alps)

Carlier¹,

Puissant²,

Dujarric³

et al. 2017

Preprint

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10Vulnerability is a complex concept involving a variety of disciplines from physical and socio-economic sciences. Currently, two opposite trends exist: the physical approach in which vulnerability is analysed as potential impacts on the exposed elements; and the social approach in which vulnerability is viewed as a combination of socio-economic variables determining people's ability to anticipate before a catastrophic event, to react during it, and to recover after it. Finding a way to combine these two approaches is a key issue for a global vulnerability 15 assessment. The objective of this paper is to improve the Potential Damage Index (Puissant et al., 2013) originally developed to assess the physical, structural and functional consequences of landslide hazard, by including social and institutional criteria. These criteria, derived from INSEE French census data and risk perception survey were selected to represent the three main phases of risk management: preparedness, crisis management and recovery. The new Global Potential Damage Index is then applied on the Upper Guil Catchment to assess torrential floods. 20Results of the PDI are compared with the GPDI and show significant differences. GPDI scores are globally lower than PDI scores indicating that resilient population may qualify results obtained for physical consequences.

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A GIS-based approach to identify the spatial variability of social vulnerability to seismic hazard in Italy

Cited by 136 publications

References 24 publications

Mapping Social Vulnerability to Air Pollution: A Case Study of the Yangtze River Delta Region, China

Mapping Social Vulnerability to Air Pollution: A Case Study of the Yangtze River Delta Region, China

A New Approach to Identify Social Vulnerability to Climate Change in the Yangtze River Delta

Improvement of an index oriented methodology for consequence analysis of natural hazards: application to the Upper Guil Catchment (Southern French Alps)

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