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Big Data for Community Resilience Assessment: A Critical Review of Selected Global Tools

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Proceedings of the 24th International Symposium on Advancement of Construction Management and Real Estate (CRIOCM 2019)

Abstract

As the global call to build sustainable cities becomes louder, the community resilience concept is also fast becoming popular in the global scientific and policy discourse. To put this concept in perspective, a lot of methodologies have been developed in the last two decades. This paper critically reviews 12 selected global community resilience assessment tools using content analysis. The results show that none of the selected tools use big data for their assessments, they mainly rely on literature review, stakeholders’ input, expert opinions and field testing. The results also show that the selected tools are mostly formulated using top-down approaches and only half of them provide action plans after their resilience assessment. Most of the tools also do not account for cross-scale relationships and temporal dynamism. The study concludes that new community resilience assessment tools need to employ iterative processes, encourage participation, and incorporate the use of big data, machine learning and artificial intelligence to take care of spatiotemporal dynamism.

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Acknowledgements

The work described in this paper was supported by the Ph.D. studentship from the Research Institute for Sustainable Development (RISUD) of the Hong Kong Polytechnic University, with the Department of Building and Real Estate providing other resources (Project No. 1-YBU6).

Author information

Authors and Affiliations

  1. Department of Building and Real Estate, The Hong Kong Polytechnic University, Hong Kong SAR, China

    Mohammed Abdul-Rahman & Edwin H. W. Chan

  2. School of Geography and Planning, Sun Yat-Sen University, Guangzhou, China

    X. Li

  3. Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hong Kong SAR, China

    Man Sing Wong

  4. School of Management Science and Real Estate, Chongqing University, Chongqing, China

    Pengpeng Xu

Authors
  1. Mohammed Abdul-Rahman
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  2. Edwin H. W. Chan
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  3. X. Li
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  4. Man Sing Wong
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  5. Pengpeng Xu
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Corresponding author

Correspondence to Mohammed Abdul-Rahman .

Editor information

Editors and Affiliations

  1. School of Management Science and Real Estate, Chongqing University, Chongqing, Chong Qing, China

    Gui Ye

  2. School of Management, Guangzhou University, Guangzhou, Guangdong, China

    Hongping Yuan

  3. School of Architecture and Built Environment, University of Adelaide, Adelaide, SA, Australia

    Jian Zuo

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Abdul-Rahman, M., Chan, E.H.W., Li, X., Wong, M.S., Xu, P. (2021). Big Data for Community Resilience Assessment: A Critical Review of Selected Global Tools. In: Ye, G., Yuan, H., Zuo, J. (eds) Proceedings of the 24th International Symposium on Advancement of Construction Management and Real Estate. CRIOCM 2019. Springer, Singapore. https://doi.org/10.1007/978-981-15-8892-1_94

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