SoResilere—A Social Resilience Index Applied to Portuguese Flood Disaster-Affected Municipalities

Abstract

Decades of academic discussion on social resilience have led to the development of indicators, indexes, and different approaches to assessing it at national and local levels. The need to show real-world applications of such assessments is evident since resilience became a political and disaster risk reduction governance component. This article gives a full description of the methodology used to develop SoResilere, a new social resilience index applied to flood disaster-affected Portuguese municipalities. Study cases were selected according to historical databases, academic sources and governmental entities. Statistical methods for data dimension reduction, such as Factor Analysis (through Principal Component Analysis), were applied to the quantitative data and Optimal Scaling to the categorical data. SoResilere results were analyzed. Since SoResilere is a new tool, component weighting was applied to compare results with no weighting, although it did not affect the SoResilere status in 55.5% of the study cases. There is a tendency to look at the improvement of SoResilere results with component weighting due mainly to the quantitative subindex. There is no evidence of the benefits of component weighting, as no logical association or spatial pattern was found to support SoResilere status improvement in 22.22% of the study cases.