The landscape of disaster resilience indicators in the USA

Susan Cutter ()

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2016, vol. 80, issue 2, 758 pages

Abstract: The landscape of disaster resilience indicators is littered with wide range of tools, scorecards, indices that purport to measure disaster resilience in some manner. This paper examines the existing qualitative and quantitative approaches to resilience assessment in order to delineate common concepts and variables. Twenty seven different resilience assessment tools, indices, and scorecards were examined. Four different parameters were used to distinguish between them—focus (on assets baseline conditions); spatial orientation (local to global), methodology (top down or bottom up), and domain area (characteristics to capacities). There is no dominant approach across these characteristics. In a more detailed procedure, fourteen empirically based case studies were examined that had actually implemented one of the aforementioned tools, indices, or scorecards to look for overlaps in both concepts measured and variables. The most common elements in all the assessment approaches can be divided into attributes and assets (economic, social, environmental, infrastructure) and capacities (social capital, community functions, connectivity, and planning). The greatest variable overlap in the case studies is with specific measures of social capital based on religious affiliation and civic organizations, and for health access (measured by the number of physicians). Based on the analysis a core set of attributes/assets, capacities, and proxy measures are presented as a path forward, recognizing that new data may be required to adequately measure many of the dimensions of community disaster resilience. Copyright Springer Science+Business Media Dordrecht 2016

Keywords: Disaster resilience indicators; Measuring community resilience; USA (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (71)

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DOI: 10.1007/s11069-015-1993-2

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