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Simulation of Urban Environments for Disaster Risk Management: Comprehensive Review of Techniques and Future Directions

  • Kieun LEE (Department of Civil Systems Engineering, College of Engineering, Ajou University) ;
  • Taeyong KIM (Department of Civil Systems Engineering, College of Engineering, Ajou University) ;
  • Sungkon MOON (Department of Civil Systems Engineering, College of Engineering, Ajou University)
  • Published : 2024.07.29

Abstract

As cities continue to evolve and expand, the importance of accurately modeling and simulating urban environments to predict and assess various risk scenarios has become increasingly recognized. Since city simulation can capture the intricate dynamics of urban life, the versatility of city simulation has been demonstrated in numerous case studies across diverse applications. Owing to this capacity, city simulation plays a critical role in the disaster risk management field, especially in accounting for the uncertainties in natural/man-made disasters. For example, in the event of an earthquake, having detailed information about an urban area is instrumental for evaluating stakeholder decisions and their impact on urban recovery strategies. Although numerous research efforts have been made to introduce city simulation techniques in disaster risk reduction, there is no clear guideline or comprehensive summary of their characteristics and features. Therefore, this study aims to provide a high-level overview of the latest research and advancements in urban simulation under different hazards. The study begins by examining the simulation techniques used in urban simulation, with a focus on their applicability in disaster scenarios. Subsequently, by analyzing various case studies, this research categorizes them based on their unique characteristics and key findings. The knowledge gained from this literature review will serve as a foundation for subsequent research on simulating the impacts of urban areas under various hazards.

Keywords

Acknowledgement

This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (Grant Number: 2022R1F1A1074039)

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