Map representation of vulnerability is a crucial step in evaluating flood impact and all vulnerability indicators that are the final product of risk assessment. So far, in flood risk assessment, this is probably the weakest link. Flood risk mapping suffers from inequality in the level of development in presenting the different components: where exposure and hazard modelling and mapping is well developed and advanced, while vulnerability analysis and mapping are underdeveloped. Therefore, the objective of this paper is to discuss a newly developed GIS-based approach on micro-scale flood vulnerability mapping of physical elements at risk using an indicator-based method. Micro-scale flood vulnerability is used to eliminate flood vulnerability in an area with a high probability of occurrences. The approach is suitable for cost-benefit analysis of structures protection measures. At micro-scale flood vulnerability mapping, it is more suitable to adopt indicator-based vulnerability assessment methods. Because it provides an opportunity for incorporating all the factors and characteristics of elements at risk that contribute to generating their flood vulnerability. Likewise, a considerable amount of studies argue that vulnerability assessment and its representation on maps should focus on the identification of variables that influence the vulnerability of an element at risk. Flood vulnerability mapping at micro-scale provides critical information for the decision-makers on why specific infrastructures are susceptible more than the others. Moreover, assessing and managing flood risk is crucial in order to reduce the loss and adapt to the combined effects of rapid urbanization and climate changes.
Ismaila Usman Kaoje, Muhammad Zulkarnain Abdul Rahman*, Tze Huey Tam and Mohd Radhie Mohd Salleh (I Net Spatial Sdn Bhd)
How to cite:
Kaoje, I. U., Abdul Rahman, M. Z., Tam, T. H., and Mohd Salleh, M. R.: AN INDICATOR-BASED APPROACH FOR MICRO-SCALE PHYSICAL FLOOD VULNERABILITY MAPPING, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W16, 331–337, https://doi.org/10.5194/isprs-archives-XLII-4-W16-331-2019, 2019.