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Urban–Rural Differences in Disaster Resilience

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  • Susan L. Cutter
  • Kevin D. Ash
  • Christopher T. Emrich

Abstract

The concept of disaster resilience has gained attention in political spheres and news outlets over the past few years, yet relatively few empirical measures of the concept exist. Furthermore, research into urban resilience has dwarfed our understanding of disaster resilience in rural places. This schism in what is known about the differences between urban and rural places becomes the topic of this article. Employing a suite of spatial and statistical techniques using an established measure of community resilience, the Baseline Resilience Indicators for Communities (BRIC), we focus on two key questions to better explain the resilience divide between urban and rural areas of the United States. Nonparametric rank analysis, analysis of variance, and logistic regression help describe the relationships between rurality and disaster resilience in contrast to resilience in urban areas. Pinpointing the driving factors, or characteristics, of resilience in rural America compared to metropolitan America, accomplished through binary logistic regression, revealed notable distinctions. Resilience in urban areas is primarily driven by economic capital, whereas community capital is the most important driver of disaster resilience in rural areas. Within rural areas there is considerable spatial variability in the components of disaster resilience. This suggests that attempts to enhance resilience cannot be approached using a one-size-fits-most strategy given the variability in the primary drivers of disaster resilience at county scales.

Suggested Citation

  • Susan L. Cutter & Kevin D. Ash & Christopher T. Emrich, 2016. "Urban–Rural Differences in Disaster Resilience," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 106(6), pages 1236-1252, November.
    • Handle: RePEc:taf:raagxx:v:106:y:2016:i:6:p:1236-1252
    DOI: 10.1080/24694452.2016.1194740
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    Citations

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    Cited by:

    1. Mahya Ghouchani & Mohammad Taji & Amirhassan Yaghoubi Roshan & Mohammad Seifi Chehr, 2021. "Identification and assessment of hidden capacities of urban resilience," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(3), pages 3966-3993, March.
    2. Jonathan R. Barton & Felipe Gutiérrez-Antinopai & Miguel Escalona Ulloa, 2021. "Adaptive Capacity as Local Sustainable Development: Contextualizing and Comparing Risks and Resilience in Two Chilean Regions," Sustainability, MDPI, vol. 13(9), pages 1-32, April.
    3. Christine Camacho & Roger T. Webb & Peter Bower & Luke Munford, 2024. "Adapting the Baseline Resilience Indicators for Communities (BRIC) Framework for England: Development of a Community Resilience Index," IJERPH, MDPI, vol. 21(8), pages 1-25, August.
    4. Sahar Derakhshan & Leah Blackwood & Margot Habets & Julia F. Effgen & Susan L. Cutter, 2022. "Prisoners of Scale: Downscaling Community Resilience Measurements for Enhanced Use," Sustainability, MDPI, vol. 14(11), pages 1-15, June.
    5. Shulei Cheng & Yu Yu & Wei Fan & Chunxia Zhu, 2022. "Spatio-Temporal Variation and Decomposition Analysis of Livelihood Resilience of Rural Residents in China," IJERPH, MDPI, vol. 19(17), pages 1-25, August.
    6. Jang, Seongsoo & Kim, Jinwon, 2022. "Remedying Airbnb COVID-19 disruption through tourism clusters and community resilience," Journal of Business Research, Elsevier, vol. 139(C), pages 529-542.
    7. Fei Su & Jiaqi Luo & Hang Liu & Lei Tong & Yuan Li, 2022. "Assessment and Promotion Strategy of Rural Resilience in Yangtze River Delta Region, China," Sustainability, MDPI, vol. 14(9), pages 1-21, April.
    8. Xuewei Chen & Hongliang Chen, 2020. "Differences in Preventive Behaviors of COVID-19 between Urban and Rural Residents: Lessons Learned from A Cross-Sectional Study in China," IJERPH, MDPI, vol. 17(12), pages 1-14, June.
    9. Jianghong Xu & Chenguang Wang & Xukang Yin & Weixin Wang, 2024. "Digital economy and rural household resilience: Evidence from China," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 70(5), pages 244-263.
    10. Goerlandt, Floris & Islam, Samsul, 2021. "A Bayesian Network risk model for estimating coastal maritime transportation delays following an earthquake in British Columbia," Reliability Engineering and System Safety, Elsevier, vol. 214(C).

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