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Using provincial baseline indicators to model geographic variations of disaster resilience in Thailand

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Abstract

Understanding a community’s capacity for responding to and recovering from natural disasters has been an emphasis of recent disaster research. In particular, scholars have called for the development of methodologies for measuring a location’s resilience to disasters. While several studies propose methodologies and frameworks for measuring disaster resilience in the USA, few studies examine and measure resilience in international settings. This study applies Cutter et al.’s (Glob Environ Change 18:598–606, 2008) Disaster Resilience of Place (DROP) model in order to examine disaster resilience at the provincial level in Thailand. Guided by the DROP model, 25 variables were selected from the 2000 and 2010 Thai Census and 2005–2006 Statistical Yearbook that served as indicators of resilience. Using a principal component analysis, a set of baseline metrics reflecting dimensions of community capacities that influence disaster resilience was created. This analysis resulted in four dimensions describing resilience: household assets, economic assets, community/response assets, and institutional assets. Using the derived index, a correlation analysis was then conducted to examine differences in rural and urban disaster resilience. While the results of the model suggest that disaster resilience is generally higher in the more urbanized areas, we also note that communities located in rural areas in Thailand may not necessarily be less resilient to the impacts of disasters and call for studies conducted at both the macrolevel (provincial level) and at microlevel (village or neighborhood level) to get a nuanced understanding of community resiliency.

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Notes

  1. As described in Flood (2000), a tambon is a political subdistrict similar to a township that includes a minimum of 7000 citizens in which many of the government activities and services are organized.

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Acknowledgments

This work was supported by a grant from the National Science Foundation under NSF RAPID Award 1242004. Any opinions, findings, and conclusions or recommendations expressed in this paper are those of the authors and do not necessarily reflect the views of the National Science Foundation. The authors wish to thank Dr. Kanappa Pongponrat, Thamassat University, Thailand, and Kraiwuth Jaikampan doctoral student at the University of North Texas for help with data collection. The authors are indebted to all the organizational contacts who responded to our survey in Thailand.

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  1. Department of Public Administration, University of North Texas, 1155 Union Circle #310617, Denton, TX, 76203-5017, USA

    Laura Siebeneck, Sudha Arlikatti & Simon A. Andrew

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  1. Laura Siebeneck
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  2. Sudha Arlikatti
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  3. Simon A. Andrew
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Correspondence to Laura Siebeneck.

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Siebeneck, L., Arlikatti, S. & Andrew, S.A. Using provincial baseline indicators to model geographic variations of disaster resilience in Thailand. Nat Hazards 79, 955–975 (2015). https://doi.org/10.1007/s11069-015-1886-4

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