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Influencing Factors Analysis and Optimization of Land Use Allocation: Combining MAS with MOPSO Procedure

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  • Jingjie Liu

    (College of Geographic Information and Tourism, Chuzhou University, Chuzhou 239000, China
    Anhui Province Key Laboratory of Physical Geographic Environment, Chuzhou 239000, China
    College of Land Management, Nanjing Agricultural University, Nanjing 210095, China)

  • Min Xia

    (College of Land Management, Nanjing Agricultural University, Nanjing 210095, China)

Abstract

The rural land use preferences of multiple agents are crucial for optimizing land-use allocation. Taking Guanlin Town, Yixing City, China as an example, this study analyzed the factors by agents effecting rural land use conversion probability, identified the objectives and the constraints within the optimization of rural land-use allocation, and simulated the optimal land-use allocation for 2030 by combining MAS with an MOPSO procedure. The results showed that the preferences and decisions of main actors effected the optimal land-use allocation. The Government determined the conversion between land-use types. The preferences of the entrepreneurs resulted in the distribution of industrial land. Town residents made a high contribution to the configuration of the town residential land by considering some factors. Rural families influenced land-use allocation by considering the quality of cultivated soils, and the optimal spatial location of aquaculture systems. Four optimization objectives were identified. The most relevant constraints were the upper and lower limits of each land-use type. The land-use types in Guanlin town in 2015 had a low intensification and an unreasonable structure. The modeling results indicated a tendency for concentrated spatial distributions of rural land. The results of the present study can provide useful support for decision-making within land planning and consequent management.

Suggested Citation

  • Jingjie Liu & Min Xia, 2023. "Influencing Factors Analysis and Optimization of Land Use Allocation: Combining MAS with MOPSO Procedure," Sustainability, MDPI, vol. 15(2), pages 1-17, January.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:2:p:1401-:d:1032525
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    References listed on IDEAS

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    1. Zheng, Dan & Shi, Minjun, 2018. "Industrial land policy, firm heterogeneity and firm location choice: Evidence from China," Land Use Policy, Elsevier, vol. 76(C), pages 58-67.
    2. Sante, Ines & Crecente, Rafael, 2007. "LUSE, a decision support system for exploration of rural land use allocation: Application to the Terra Cha district of Galicia (N.W. Spain)," Agricultural Systems, Elsevier, vol. 94(2), pages 341-356, May.
    3. Yun Li & Yanping Chen & Miaoxi Zhao & Xinxin Zhai, 2018. "Optimization of Planning Layout of Urban Building Based on Improved Logit and PSO Algorithms," Complexity, Hindawi, vol. 2018, pages 1-11, November.
    4. Liu, Tao & Huang, Daquan & Tan, Xin & Kong, Fanhao, 2020. "Planning consistency and implementation in urbanizing China: Comparing urban and land use plans in suburban Beijing," Land Use Policy, Elsevier, vol. 94(C).
    5. Zhang, Honghui & Zeng, Yongnian & Jin, Xiaobin & Shu, Bangrong & Zhou, Yinkang & Yang, Xuhong, 2016. "Simulating multi-objective land use optimization allocation using Multi-agent system—A case study in Changsha, China," Ecological Modelling, Elsevier, vol. 320(C), pages 334-347.
    6. Huafeng Xu & Bin Liu & Zhigeng Fang, 2014. "New grey prediction model and its application in forecasting land subsidence in coal mine," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 71(2), pages 1181-1194, March.
    7. Li An & Alex Zvoleff & Jianguo Liu & William Axinn, 2014. "Agent-Based Modeling in Coupled Human and Natural Systems (CHANS): Lessons from a Comparative Analysis," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 104(4), pages 723-745, July.
    8. Liu, Dongya & Zheng, Xinqi & Wang, Hongbin, 2020. "Land-use Simulation and Decision-Support system (LandSDS): Seamlessly integrating system dynamics, agent-based model, and cellular automata," Ecological Modelling, Elsevier, vol. 417(C).
    9. Peng, Jianchao & Yan, Siqi & Strijker, Dirk & Wu, Qun & Chen, Wei & Ma, Zhiyuan, 2020. "The influence of place identity on perceptions of landscape change: Exploring evidence from rural land consolidation projects in Eastern China," Land Use Policy, Elsevier, vol. 99(C).
    10. Huang, Yaofu & Hui, Eddie C.M. & Zhou, Jinmiao & Lang, Wei & Chen, Tingting & Li, Xun, 2020. "Rural Revitalization in China: Land-Use Optimization through the Practice of Place-making," Land Use Policy, Elsevier, vol. 97(C).
    11. Tian, Fenghao & Li, Mingyu & Han, Xulong & Liu, Hui & Mo, Boxian, 2020. "A Production–Living–Ecological Space Model for Land-Use Optimisation: A case study of the core Tumen River region in China," Ecological Modelling, Elsevier, vol. 437(C).
    12. Xia, Min & Zhang, Yanyuan & Zhang, Zihong & Liu, Jingjie & Ou, Weixin & Zou, Wei, 2020. "Modeling agricultural land use change in a rapid urbanizing town: Linking the decisions of government, peasant households and enterprises," Land Use Policy, Elsevier, vol. 90(C).
    13. Zhanqi Wang & Jun Yang & Xiangzheng Deng & Xi Lan, 2015. "Optimal Water Resources Allocation under the Constraint of Land Use in the Heihe River Basin of China," Sustainability, MDPI, vol. 7(2), pages 1-18, February.
    14. Mingxing Chen & Yuan Zhou & Xinrong Huang & Chao Ye, 2021. "The Integration of New-Type Urbanization and Rural Revitalization Strategies in China: Origin, Reality and Future Trends," Land, MDPI, vol. 10(2), pages 1-16, February.
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