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    Disaster risk index: How far should it take account of local attributes?

    Access Status
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    Authors
    Islam, M.
    Swapan, Mohammad
    Haque, S.
    Date
    2013
    Type
    Journal Article
    
    Metadata
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    Citation
    Islam, M. and Swapan, M. and Haque, S. 2013. Disaster risk index: How far should it take account of local attributes?. International Journal of Disaster Risk Reduction. 3 (1): pp. 76-87.
    Source Title
    International Journal of Disaster Risk Reduction
    DOI
    10.1016/j.ijdrr.2012.10.001
    ISSN
    2212-4209
    School
    Department of Planning and Geography
    URI
    http://hdl.handle.net/20.500.11937/54471
    Collection
    • Curtin Research Publications
    Abstract

    The coastal areas of Bangladesh are disaster prone. Along with natural hazards there are persisting local hazards (e.g., salinity, river bank erosion) in the coastal parts. An approach to disaster reduction strategy, therefore, varies here highly with other areas and also with other disasters. Disaster risk that comes from hazard, vulnerability and local capacity can only be applied here if the assessment addresses socio-political aspects as well. In this study we identified prevailing hazards including the ones which are particularly important for the study area. All hazards are then assessed based on local vulnerability and coping capacity. Participatory appraisal has been taken into account to understand the level of devastation of the disasters. All these qualitative aspects are then categorized to fit in mathematical model of disaster risk estimation. A GIS based approach of multi-criteria analysis has been applied to incorporate the spatial factors in the index. Therefore, the final output is enumerated for each land parcel (locally called mouza) where spatial variability is represented and shown on maps. There are 11 identified hazards in the study area which have association with 11 social factors of vulnerability. The disaster risk index (DRI) also takes account of three geographic factors of vulnerability that are aggregated with the social factors to calculate a reliable DRI. The aggregated outcome is finally validated with historical data of disaster occurrences in the study area and found significant correspondence. © 2012 Elsevier Ltd.

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