An Integrated PCA–AHP Method to Assess Urban Social Vulnerability to Sea Level Rise Risks in Tampa, Florida

Weiwei Xie and Qingmin Meng ()
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Weiwei Xie: Department of Geosciences, Mississippi State University, Mississippi State, MS 39762, USA
Qingmin Meng: Department of Geosciences, Mississippi State University, Mississippi State, MS 39762, USA

Sustainability, 2023, vol. 15, issue 3, 1-21

Abstract: Coastal flooding risks are increasing with the rise of sea level due to global climate change. Such risk presents different groups of residents with diverse vulnerability. Using a coastal city as the study area, this study quantitatively and qualitatively examines social vulnerability across different communities at risk of sea level rising. This study develops a novel social vulnerability assessment method that integrates principal component analysis (PCA) and analytical hierarchical process (AHP), inputting the advantages of each into factor analysis for social vulnerability quantification. Twenty-four socioeconomic factors are first grouped into four different themes. PCA is then performed to identify major components within each theme. We apply AHP to generate the weighting scheme for each theme. Therefore, the AHP-derived weights to those PCA components according to each theme are used to obtain an overall social vulnerability index. The thematic map of PCA–AHP SVI showed that minority communities with low income, mobile home, and unemployed populations aggregated in the East Tampa shore (over 69% of the total minority), compared with the West Tampa (31% of the total minority). Our findings provide insightful spatial information of the social vulnerability index (SVI) that allows decision makers to make optimal efforts to mitigate damages and unexpected impacts on different communities, especially those marginalized minorities due to sea level rising risks.

Keywords: sea level rise; PCA–AHP; social vulnerability; flooding risk; marginalized communities (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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