Multi-regional urban systems vulnerability and disaster impact analysis

• Main Authors: Tang, Xiuke, Mandapaka, Pradeep V., Tai, Kang, Lo, Edmond Y. M.
• Format: Conference Proceeding
• Language: English
• Subjects: Analytical models; Biological system modeling; Couplings; Decision making; Disasters; Economics; indirect impacts; input-output model; linkage analysis; multiple regions; multiplier analysis; Sociology; urban system
• ISSN: 2472-9647
• DOI: 10.1109/SysCon61195.2024.10553502

Urban systems are becoming more sophisticated, with their constituent economic/industrial sectors interacting in complex ways that are difficult to study partly due to data unavailability or confidentiality. Very often, a tiny disruption may cause a considerable disruption not only in the original impacted region and sector but also in other regions and sectors due to cascading effects resulting from complex interdependencies. These interdependencies can serve as a measure of the level of vulnerability. Previous studies were about assessing one or two types of interdependencies only. That means only a partial picture of vulnerabilities of the urban system can be revealed. The more thorough interdependencies assessed by some models may also be modeled at larger spatial scales like the national or provincial level. Thus, in this article, the multi-regional (MR) input-output (IO) model, as well as the linkage analysis and multiplier analysis, are applied to identify and quantify the overall interdependencies and reveal the vulnerability of regions and sectors at multiple counties levels, which reveal a more detailed picture of the vulnerability of individual regions. Through the case study in Singapore, the characteristics of vulnerabilities in the highly interdependent urban system can be uncovered - similarities in regional vulnerabilities while varying vulnerabilities in regional sectoral transactions, exhibiting the varying functionality of different regions within an urban system. By uncovering the interdependencies and vulnerabilities, urban planners and policymakers can make better decisions with regards to the urban system's resilience. Moreover, the downscaled disaster loss can also be computed, which helps to further study the resilience of an urban system before disruption happens or during the recovery phases.