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Modelling a community resilience index for urban flood-prone areas of Kerala, India (CRIF)

Communities are ever-evolving, cities are constantly expanding, and the threat of natural hazards has escalated like never before. Cities can develop and prosper only if their society is resilient to external shocks. Measuring community resilience over time is crucial with the influence of technolog...

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Detalles Bibliográficos
Autores principales: Ali, Sameer, George, Abraham
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Netherlands 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8906364/
https://www.ncbi.nlm.nih.gov/pubmed/35287382
http://dx.doi.org/10.1007/s11069-022-05299-7
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author Ali, Sameer
George, Abraham
author_facet Ali, Sameer
George, Abraham
author_sort Ali, Sameer
collection PubMed
description Communities are ever-evolving, cities are constantly expanding, and the threat of natural hazards has escalated like never before. Cities can develop and prosper only if their society is resilient to external shocks. Measuring community resilience over time is crucial with the influence of technology and change in community lifestyles. With the frequent onset of floods in Kerala in recent years, the community must be well-prepared for future calamities. Thus, this paper develops a community resilience index for Kerala’s urban flood-prone areas (CRIF) through a rigorous bottom-up approach. The criteria for the index were developed using multi-criteria decision analysis that covered a fuzzy Delphi study, an empirical study using multi-variate probit regression, and an AHP analysis. The fuzzy Delphi study selected seven criteria: ‘social’, ‘economical’, ‘governance/political’, ‘health’, ‘communication/coordination, ‘education’, and ‘infrastructure’ from 65 experts. The empirical study helped apprehend the public’s viewpoints under each criterion. Finally, the AHP analysis helped assign appropriate weights to the criteria which 28 experts designated. The index is also designed according to the Sendai Framework for Disaster Risk Reduction (2015–2030). Further, the CRIF Index is put into action through a case study of the Kochi Municipal Corporation area, and the results are also validated using the Spearman’s rank correlation coefficient method. Results from validation returned a value of 0.7209 for the perceived CRIF method and 0.5798 for the external validation method, which corresponds to a ‘high’ and ‘moderate’ correlation, respectively. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11069-022-05299-7.
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spelling pubmed-89063642022-03-10 Modelling a community resilience index for urban flood-prone areas of Kerala, India (CRIF) Ali, Sameer George, Abraham Nat Hazards (Dordr) Original Paper Communities are ever-evolving, cities are constantly expanding, and the threat of natural hazards has escalated like never before. Cities can develop and prosper only if their society is resilient to external shocks. Measuring community resilience over time is crucial with the influence of technology and change in community lifestyles. With the frequent onset of floods in Kerala in recent years, the community must be well-prepared for future calamities. Thus, this paper develops a community resilience index for Kerala’s urban flood-prone areas (CRIF) through a rigorous bottom-up approach. The criteria for the index were developed using multi-criteria decision analysis that covered a fuzzy Delphi study, an empirical study using multi-variate probit regression, and an AHP analysis. The fuzzy Delphi study selected seven criteria: ‘social’, ‘economical’, ‘governance/political’, ‘health’, ‘communication/coordination, ‘education’, and ‘infrastructure’ from 65 experts. The empirical study helped apprehend the public’s viewpoints under each criterion. Finally, the AHP analysis helped assign appropriate weights to the criteria which 28 experts designated. The index is also designed according to the Sendai Framework for Disaster Risk Reduction (2015–2030). Further, the CRIF Index is put into action through a case study of the Kochi Municipal Corporation area, and the results are also validated using the Spearman’s rank correlation coefficient method. Results from validation returned a value of 0.7209 for the perceived CRIF method and 0.5798 for the external validation method, which corresponds to a ‘high’ and ‘moderate’ correlation, respectively. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11069-022-05299-7. Springer Netherlands 2022-03-09 2022 /pmc/articles/PMC8906364/ /pubmed/35287382 http://dx.doi.org/10.1007/s11069-022-05299-7 Text en © The Author(s), under exclusive licence to Springer Nature B.V. 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Original Paper
Ali, Sameer
George, Abraham
Modelling a community resilience index for urban flood-prone areas of Kerala, India (CRIF)
title Modelling a community resilience index for urban flood-prone areas of Kerala, India (CRIF)
title_full Modelling a community resilience index for urban flood-prone areas of Kerala, India (CRIF)
title_fullStr Modelling a community resilience index for urban flood-prone areas of Kerala, India (CRIF)
title_full_unstemmed Modelling a community resilience index for urban flood-prone areas of Kerala, India (CRIF)
title_short Modelling a community resilience index for urban flood-prone areas of Kerala, India (CRIF)
title_sort modelling a community resilience index for urban flood-prone areas of kerala, india (crif)
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8906364/
https://www.ncbi.nlm.nih.gov/pubmed/35287382
http://dx.doi.org/10.1007/s11069-022-05299-7
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