摘要
Quantitative assessment of community resilience can provide support for hazard mitigation,disaster risk reduction,disaster relief,and long-term sustainable development.Traditional resilience assessment tools are mostly theory-driven and lack empirical validation,which impedes scientific understanding of community resilience and practical decision-making of resilience improvement.In the advent of the Big Data Era,the increasing data availability and advances in computing and modeling techniques offer new opportunities to understand,measure,and promote community resilience.This article provides a comprehensive review of the definitions of community resilience,along with the traditional and emerging data and methods of quantitative resilience measurement.The theoretical bases,modeling principles,advantages,and disadvantages of the methods are discussed.Finally,we point out research avenues to overcome the existing challenges and develop robust methods to measure and promote community resilience.This article establishes guidance for scientists to further advance disaster research and for planners and policymakers to design actionable tools to develop sustainable and resilient communities.
基金
supported by the U.S.National Science Foundation under the Methodology,Measurement&Statistics(MMS)Program(Award#:2102019)
the Human Networks&Data Science Infrastructure Program(Award#:2318204&2318206)
the Smart and Connected Communities(Award#:2325631)
Texas A&M University Innovation[X]Program.
