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Building Adaption Model in Assessing Adaption Potential of Old Residential Quarters Read chapter Read first chapter

2021 | OriginalPaper | Chapter

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

Authors : Mohammed Abdul-Rahman, Edwin H. W. Chan, X. Li, Man Sing Wong, Pengpeng Xu

Published in: Proceedings of the 24th International Symposium on Advancement of Construction Management and Real Estate

Publisher: Springer Singapore

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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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Metadata
Title
Big Data for Community Resilience Assessment: A Critical Review of Selected Global Tools
Authors
Mohammed Abdul-Rahman
Edwin H. W. Chan
X. Li
Man Sing Wong
Pengpeng Xu
Copyright Year
2021
Publisher
Springer Singapore
Book
Proceedings of the 24th International Symposium on Advancement of Construction Management and Real Estate

Print ISBN: 978-981-15-8891-4

Electronic ISBN: 978-981-15-8892-1

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-981-15-8892-1_94