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Simulating the Conversion of Rural Settlements to Town Land Based on Multi-Agent Systems and Cellular Automata

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  • Yaolin Liu
  • Xuesong Kong
  • Yanfang Liu
  • Yiyun Chen

Abstract

Rapid urbanization in China has triggered the conversion of land from rural to urban use, particularly the conversion of rural settlements to town land. This conversion is the result of the joint effects of the geographic environment and agents involving the government, investors, and farmers. To understand the dynamic interaction dominated by agents and to predict the future landscape of town expansion, a small town land-planning model is proposed based on the integration of multi-agent systems (MAS) and cellular automata (CA). The MAS-CA model links the decision-making behaviors of agents with the neighbor effect of CA. The interaction rules are projected by analyzing the preference conflicts among agents. To better illustrate the effects of the geographic environment, neighborhood, and agent behavior, a comparative analysis between the CA and MAS-CA models in three different towns is presented, revealing interesting patterns in terms of quantity, spatial characteristics, and the coordinating process. The simulation of rural settlements conversion to town land through modeling agent decision and human-environment interaction is very useful for understanding the mechanisms of rural-urban land-use change in developing countries. This process can assist town planners in formulating appropriate development plans.

Suggested Citation

  • Yaolin Liu & Xuesong Kong & Yanfang Liu & Yiyun Chen, 2013. "Simulating the Conversion of Rural Settlements to Town Land Based on Multi-Agent Systems and Cellular Automata," PLOS ONE, Public Library of Science, vol. 8(11), pages 1-14, November.
    • Handle: RePEc:plo:pone00:0079300
    DOI: 10.1371/journal.pone.0079300
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    References listed on IDEAS

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    1. R White & G Engelen, 1993. "Cellular Automata and Fractal Urban Form: A Cellular Modelling Approach to the Evolution of Urban Land-Use Patterns," Environment and Planning A, , vol. 25(8), pages 1175-1199, August.
    2. Tian, Guangjin & Ouyang, Yun & Quan, Quan & Wu, Jianguo, 2011. "Simulating spatiotemporal dynamics of urbanization with multi-agent systems—A case study of the Phoenix metropolitan region, USA," Ecological Modelling, Elsevier, vol. 222(5), pages 1129-1138.
    3. Karen C Seto & Michail Fragkias & Burak Güneralp & Michael K Reilly, 2011. "A Meta-Analysis of Global Urban Land Expansion," PLOS ONE, Public Library of Science, vol. 6(8), pages 1-9, August.
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    Cited by:

    1. Ma, Shenglan & Huang, Junlin & Wang, Xiuxiu & Fu, Ying, 2025. "Multi-scenario simulation of low-carbon land use based on the SD-FLUS model in Changsha, China," Land Use Policy, Elsevier, vol. 148(C).
    2. Zhao, Xiang & Cai, Bocheng & He, Jianhua & Kong, Xuesong, 2024. "Identifying potential rural residential areas for land consolidation using a data driven agent-based model," Land Use Policy, Elsevier, vol. 145(C).
    3. Song, Wei & Li, Huanhuan, 2020. "Spatial pattern evolution of rural settlements from 1961 to 2030 in Tongzhou District, China," Land Use Policy, Elsevier, vol. 99(C).
    4. Yujing Zhao & Hong Leng & Pingjun Sun & Qing Yuan, 2019. "Application and Validation of a Municipal Administrative Area Spatial Zoning Model in Village-Town System Planning," Sustainability, MDPI, vol. 11(7), pages 1-25, March.
    5. Ling Xie & Hongwei Wang & Suhong Liu, 2022. "Simulating the spatiotemporal variations of oasis rural settlements in the upper reaches of rivers of arid regions in Xinjiang, China," PLOS ONE, Public Library of Science, vol. 17(9), pages 1-24, September.
    6. Raphael Karutz & Christian J. A. Klassert & Sigrun Kabisch, 2023. "On Farmland and Floodplains—Modeling Urban Growth Impacts Based on Global Population Scenarios in Pune, India," Land, MDPI, vol. 12(5), pages 1-21, May.

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