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Simulation of urban growth scenarios using integration of multi-criteria analysis and game theory

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  • Sadooghi, Seyed Ehsan
  • Taleai, Mohammad
  • Abolhasani, Somaie

Abstract

Urban growth is a dynamic and evolutionary spatial and social process. Urban development can be considered as a function of strategic behavior of the involved agents, which is affected by various factors such as land use interactions, density of population, economic situation, etc. This study presents an integrated model of cellular automata, multi-criteria analysis, game-theory and agent-based methods for land-use planning and simulation of urban development scenarios based on growth and distribution of the population. This model quantifies and simulates the land-use interactions concerning regulations and guidelines of the master plan. In the proposed approach, the suitability of developed land-use types is evaluated by using the multi-criteria analysis. Land-use changes are defined as an outcome of the interaction between two types of decision-makers (agents): Land Developer and Municipality. Game theory is used to simulate and quantify the strategic behavior of these two agents. The optimal decision between the agents is obtained using the backward induction process. The proposed model was implemented in the region of Roozieh in the city of Semnan. Six scenarios were simulated based on the Semnan’s approved master plan and considering the stochastic perturbation. The outcome of each scenario was evaluated based on the spatial equity factors. The results demonstrated the ability of the model to simulate the consequence of urban land-use development plans based on the regulations and guidelines of the master plan, especially for the balanced distribution of services concerning existing demand in their undersupply regions.

Suggested Citation

  • Sadooghi, Seyed Ehsan & Taleai, Mohammad & Abolhasani, Somaie, 2022. "Simulation of urban growth scenarios using integration of multi-criteria analysis and game theory," Land Use Policy, Elsevier, vol. 120(C).
    • Handle: RePEc:eee:lauspo:v:120:y:2022:i:c:s0264837722002940
    DOI: 10.1016/j.landusepol.2022.106267
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    3. Song, Youcheng & Wang, Haijun & Peng, Xiaotao & Sun, Duan & Chen, Rui, 2023. "Modeling land use change prediction using multi-model fusion techniques: A case study in the Pearl River Delta, China," Ecological Modelling, Elsevier, vol. 486(C).

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