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Volume 37, Issue 3 (2022)                   GeoRes 2022, 37(3): 339-349 | Back to browse issues page
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Behrouzi H, Zand Moghadam M, Kamyabi S. Modeling the Resilience of the City Against Natural Hazards with Emphasis on Landslide (Case study: Ghaemshahr City). GeoRes 2022; 37 (3) : 4
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1- Department of Geography and Urban Planning, Semnan Branch, Islamic Azad University, Semnan, Iran
* Corresponding Author Address: Department of Geography and Urban Planning, Semnan Branch, Islamic Azad University, 5 km of Semnan, Damghan road, Semnan, Iran (dr.zandmoghadam@gmail.com)
Abstract   (1277 Views)
Aims: Resilient cities are cities that support the development of wider resilience in economic and social life, its infrastructure, and institutions; resilient cities also reduce vulnerability to severe events and creatively respond to environmental, economic, and social changes to increase their long-term sustainability. Therefore, the purpose of this study was to model the city's resilience to hazards.
Methodology: The method used in this research is to use GIS software version 10.3 in order to determine points with greater resilience and to use genetic algorithm methods and particle swarm intelligence and their programming in the MATLAB environment in order to use it to determine the most important components of city resilience and effective strategies to strengthen resilience are identified.
Findings: The present study was conducted in two stages. In the first stage, first, using the analytical hierarchy process model, the degree of resilience of urban areas against landslides was determined and then, by combining all the mentioned components, the final hazard map was prepared. In the second stage, to determine The most important components of resilience in the city This time, 32 indicators of resilience components based on 4 criteria (physical-spatial, economic, social, institutional) were compiled and examined using a genetic algorithm, which finally 3 points of the city, respectively (Talar park, Shahid Watani Stadium, Siraj Park) were selected and prioritized as areas with more resilience. Then, to confirm and compare the research findings by genetic algorithm, the Particle Swarm Intelligence method was used.
Conclusion: There is a difference in terms of resiliency among the city areas, and increasing the resiliency of Qaimshahr city in the first stage requires strengthening and modifying the structures of the natural environment and then maintaining the safe environment.
 
Article number: 4
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