TY - JOUR
T1 - Rethinking disaster resilience in high-density cities
T2 - Towards an urban resilience knowledge system
AU - Sajjad, Muhammad
AU - Chan, Johnny C. L.
AU - Chopra, Shauhrat S.
N1 - Funding Information:
This work is partly supported by a Research Studentship from the City University of Hong Kong ( 000618 ), Hong Kong Special Administrative Region. All the data used in this study are available within the paper and the supplementary information, or the links to the resources are provided. The results from this study will be made available online using the interactive platform (available at: https://arcg.is/1zGzSq ) developed by Sajjad M. after the publication. The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher Copyright:
© 2021 Elsevier Ltd
PY - 2021/6
Y1 - 2021/6
N2 - Fostering high-resolution disaster resilience assessment is essential for high-density cities (HDCs) given their congested built environment. This study introduces and demonstrates a spatial disaster resilience profiling (S-DReP) framework for HDCs. First, an indicator set is presented for resilience assessment in HDCs within a built environment. Second, this indicator set is adopted to identify the spatially-varying patterns of neighbourhood disaster resilience in HDCs. In contrast to typical resilience frameworks, the developed framework also takes into account the spatio-environmental factors within the built environment. As an illustrative example, we demonstrate the application of S-DReP framework to one of the most populated districts in Hong Kong, namely Sha Tin. Building-level data for 24 indicators and infrastructure data are used to compute a spatially-relative disaster resilience index. To inform the planners with disparities among different resilience components, the Analysis of Variance approach is employed to explore the distribution of resilience. To identify the priority intervention areas, the spatial assessments are made using several geo-information models. The proposed S-DReP framework provides a roadmap to establish an urban resilience knowledge system in HDCs enabling practitioners, decision-makers, and local bodies to design action plans for future vigilance reducing the worsening impacts of hazards on cities.
AB - Fostering high-resolution disaster resilience assessment is essential for high-density cities (HDCs) given their congested built environment. This study introduces and demonstrates a spatial disaster resilience profiling (S-DReP) framework for HDCs. First, an indicator set is presented for resilience assessment in HDCs within a built environment. Second, this indicator set is adopted to identify the spatially-varying patterns of neighbourhood disaster resilience in HDCs. In contrast to typical resilience frameworks, the developed framework also takes into account the spatio-environmental factors within the built environment. As an illustrative example, we demonstrate the application of S-DReP framework to one of the most populated districts in Hong Kong, namely Sha Tin. Building-level data for 24 indicators and infrastructure data are used to compute a spatially-relative disaster resilience index. To inform the planners with disparities among different resilience components, the Analysis of Variance approach is employed to explore the distribution of resilience. To identify the priority intervention areas, the spatial assessments are made using several geo-information models. The proposed S-DReP framework provides a roadmap to establish an urban resilience knowledge system in HDCs enabling practitioners, decision-makers, and local bodies to design action plans for future vigilance reducing the worsening impacts of hazards on cities.
KW - Built environment
KW - Geographic information system
KW - Hong Kong
KW - Natural hazards
KW - Spatial analysis
KW - Urban resilience knowledge system
UR - http://www.scopus.com/inward/record.url?scp=85103089703&partnerID=8YFLogxK
U2 - 10.1016/j.scs.2021.102850
DO - 10.1016/j.scs.2021.102850
M3 - Journal article
SN - 2210-6707
VL - 69
JO - Sustainable Cities and Society
JF - Sustainable Cities and Society
M1 - 102850
ER -
