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Assessing impacts and community preparedness to cyclones: a fuzzy cognitive mapping approach

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  • Pramod K. Singh

    (Institute of Rural Management Anand)

  • Harpalsinh Chudasama

    (Institute of Rural Management Anand)

Abstract

Exposure to heightened intensity and frequency of extreme climatic events coupled with higher vulnerability of population has pushed up the disaster risk graph in developing nations. The area under study, India’s eastern coast, is particularly susceptible to cyclones originating in the Bay of Bengal. This paper is aimed at identifying perceptions of impacts and preparedness levels of coastal and inland fishermen, the inhabitants of the Ganjam and Puri districts in the eastern coast of India with the aid of fuzzy cognitive maps. Based on communities’ perceptions, we have attempted to capture both the economic impacts (losses and damages) wreaked by cyclones as well as the ecological and social impacts in a bid to unearth options for policy makers and planners to be used for bolstering disaster preparedness. The paper also aims at evaluating the effectiveness of current preparedness measures in the context of climate change by deploying various fuzzy cognitive mapping simulation-based preparedness pathways. On the methodological front, our findings confirm that FCM simulations developed through modified activation rule with a hyperbolic transformation function give better results compared to other methods. The findings reveal that none of the preparedness pathways with current preparedness measures is adequate in terms of providing resilience against cyclonic risks. Hence, in order to increase communities’ resilience against cyclones, there is a need for new sets of impact-specific preparedness measures.

Suggested Citation

  • Pramod K. Singh & Harpalsinh Chudasama, 2017. "Assessing impacts and community preparedness to cyclones: a fuzzy cognitive mapping approach," Climatic Change, Springer, vol. 143(3), pages 337-354, August.
    • Handle: RePEc:spr:climat:v:143:y:2017:i:3:d:10.1007_s10584-017-2007-z
    DOI: 10.1007/s10584-017-2007-z
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    References listed on IDEAS

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    1. Pramod Singh & Abhishek Nair, 2014. "Livelihood vulnerability assessment to climate variability and change using fuzzy cognitive mapping approach," Climatic Change, Springer, vol. 127(3), pages 475-491, December.
    2. Pramod K Singh & Harpalsinh Chudasama, 2017. "Pathways for drought resilient livelihoods based on people’s perception," Climatic Change, Springer, vol. 140(2), pages 179-193, January.
    3. A. Rao & P. Chittibabu & T. Murty & S. Dube & U. Mohanty, 2007. "Vulnerability from storm surges and cyclone wind fields on the coast of Andhra Pradesh, India," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 41(3), pages 515-529, June.
    4. Alexandros Nikas & Haris Doukas, 2016. "Developing Robust Climate Policies: A Fuzzy Cognitive Map Approach," International Series in Operations Research & Management Science, in: Michael Doumpos & Constantin Zopounidis & Evangelos Grigoroudis (ed.), Robustness Analysis in Decision Aiding, Optimization, and Analytics, chapter 0, pages 239-263, Springer.
    5. Areti D. Kontogianni & Elpiniki Papageorgiou, 2012. "Using Fuzzy Cognitive Mapping in Environmental Decision Making and Management: A Methodological Primer and an Application," Chapters, in: Stephen Young & Steven Silvern (ed.), International Perspectives on Global Environmental Change, IntechOpen.
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    Cited by:

    1. Konstantinos Papageorgiou & Pramod K. Singh & Elpiniki Papageorgiou & Harpalsinh Chudasama & Dionysis Bochtis & George Stamoulis, 2019. "Fuzzy Cognitive Map-Based Sustainable Socio-Economic Development Planning for Rural Communities," Sustainability, MDPI, vol. 12(1), pages 1-31, December.
    2. Singh, Pramod K. & Chudasama, Harpalsinh, 2023. "Geo-information-enabled village level micro-planning for enhancing common good," Technological Forecasting and Social Change, Elsevier, vol. 189(C).
    3. Mehryar, Sara & Surminski, Swenja, 2021. "Investigating flood resilience perceptions and supporting collective decision-making through fuzzy cognitive mapping," LSE Research Online Documents on Economics 115523, London School of Economics and Political Science, LSE Library.
    4. Renissa Quiñones & June Anne Caladcad & Hubert Quiñones & Shirley Ann Caballes & Dharyll Prince Abellana & Eula Margareth Jabilles & Celbert Himang & Lanndon Ocampo, 2019. "Open Innovation with Fuzzy Cognitive Mapping for Modeling the Barriers of University Technology Transfer: A Philippine Scenario," JOItmC, MDPI, vol. 5(4), pages 1-22, November.
    5. Konstantinos Papageorgiou & Pramod K Singh & Elpiniki I Papageorgiou & Harpalsinh Chudasama & Dionysios Bochtis & George Stamoulis, 2020. "Participatory modelling for poverty alleviation using fuzzy cognitive maps and OWA learning aggregation," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-28, June.
    6. Pramod K. Singh & Konstantinos Papageorgiou & Harpalsinh Chudasama & Elpiniki I. Papageorgiou, 2019. "Evaluating the Effectiveness of Climate Change Adaptations in the World’s Largest Mangrove Ecosystem," Sustainability, MDPI, vol. 11(23), pages 1-17, November.
    7. Mehryar, Sara & Surminski, Swenja, 2021. "Investigating flood resilience perceptions and supporting collective decision-making through fuzzy cognitive mapping," LSE Research Online Documents on Economics 115529, London School of Economics and Political Science, LSE Library.
    8. Kafferine Yamagishi & Lanndon Ocampo & Dharyll Prince Abellana & Reciel Ann Tanaid & Ann Myril Tiu & Maria Esther Medalla & Egberto Selerio & Chrisalyn Go & Rey Cesar Olorvida & Amalia Maupo & Deariel, 2021. "The impact of social media marketing strategies on promoting sustainability of tourism with fuzzy cognitive mapping: a case of Kalanggaman Island (Philippines)," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(10), pages 14998-15030, October.

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