The Application of Composite Indicators to Disaster Resilience: A Case Study in Osaka Prefecture, Japan

Maiko Ebisudani, Akihiro Tokai

Abstract


This paper presents an empirical verification of the measurement of baseline characteristics for fostering regional resilience. A set of indicators was selected from previous studies of disaster resilience, and an environmental element was added. The aims of the study were (1) to select a set of indicators that could be used for measuring disaster resilience, based on a review of the research literature, (2) to evaluate these indicators using the statistical approach of standardization, and to visualize the results using Geographic Information System (GIS) technology, and (3) to identify the key resilience characteristics using principal component analysis (PCA). The study focused on 29 municipalities in Osaka Prefecture, Japan. From the literature review, a total of 17 disaster resilience indicators were selected, covering economic, social, and community connection factors. The novel environmental attributes were selected from the literature on environmental sustainability. The standardized measures demonstrated that municipalities with a high level of resilience were also ranked highly on both the “social” and “community connection” attributes. The GIS mapping resulted a prominent urban-suburban divide, with urban areas having a lower level of resilience than suburban areas. The PCA demonstrated significant variation across the 29 municipalities, characterized by the factors “living standard” and “regional involvement.” An understanding of these baseline characteristics would allow governments to monitor chronological changes in the resilience of specific regions. This information can be used to support the establishment of an evaluation platform, and can contribute to a more systematic management of resilience.


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DOI: http://dx.doi.org/10.5539/jsd.v10n1p81

Copyright (c) 2017 Maiko Ebisudani

License URL: http://creativecommons.org/licenses/by/4.0

Journal of Sustainable Development   ISSN 1913-9063 (Print)   ISSN 1913-9071 (Online) Email: jsd@ccsenet.org

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