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Simulating Intraurban Land Use Dynamics under Multiple Scenarios Based on Fuzzy Cellular Automata: A Case Study of Jinzhou District, Dalian

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  • Jun Yang
  • Weiling Liu
  • Yonghua Li
  • Xueming Li
  • Quansheng Ge

Abstract

The spatial evolution of land use in Jinzhou area was simulated using fuzzy cellular automata to determine all factors influencing urban land use change. For this purpose, land use data of multiple sources and remote sensing images from 2003 to 2015 were analyzed. The following results were obtained: (1) real land use data and simulation data for 2015 were tested using four indices. Under the 5 m × 5 m scale, the model shows good performance for simulation of areas with various land use types. (2) Among simulations under four scenarios, the effect of traffic guidance on the development of construction land was more distinct under the economic development mode, which clearly showed the phenomenon of “agglomeration” along major traffic lines. (3) Jinshitan Street is adjacent to the sea, and land use changes are significant under the 4th scenario, and thus related departments should pay more attention. (4) Shortcomings of conventional cellular automata model in processing complex systems could be mitigated through the integration of fuzzy sets.

Suggested Citation

  • Jun Yang & Weiling Liu & Yonghua Li & Xueming Li & Quansheng Ge, 2018. "Simulating Intraurban Land Use Dynamics under Multiple Scenarios Based on Fuzzy Cellular Automata: A Case Study of Jinzhou District, Dalian," Complexity, Hindawi, vol. 2018, pages 1-17, August.
    • Handle: RePEc:hin:complx:7202985
    DOI: 10.1155/2018/7202985
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    Citations

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    Cited by:

    1. Mauricio Verardo & Pedro P. B. de Oliveira, 2019. "A Fully Operational Framework for Handling Cellular Automata Templates," Complexity, Hindawi, vol. 2019, pages 1-11, April.
    2. Evan B Brooks & John W Coulston & Kurt H Riitters & David N Wear, 2020. "Using a hybrid demand-allocation algorithm to enable distributional analysis of land use change patterns," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-21, October.
    3. Xuejiao Fan & Bin Quan & Zhiwei Deng & Jianxiong Liu, 2022. "Study on Land Use Changes in Changsha–Zhuzhou–Xiangtan under the Background of Cultivated Land Protection Policy," Sustainability, MDPI, vol. 14(22), pages 1-17, November.
    4. Yi Lu & Shawn Laffan & Chris Pettit & Min Cao, 2020. "Land use change simulation and analysis using a vector cellular automata (CA) model: A case study of Ipswich City, Queensland, Australia," Environment and Planning B, , vol. 47(9), pages 1605-1621, November.
    5. Li, Zeyang & Luan, Weixin & Zhang, Zhenchao & Su, Min, 2020. "Relationship between urban construction land expansion and population/economic growth in Liaoning Province, China," Land Use Policy, Elsevier, vol. 99(C).
    6. Chenxi Li & Jingyao Wu & Zenglei Xi & Weiqiang Zhang, 2021. "Farmers’ Satisfaction with Land Expropriation System Reform: A Case Study in China," Land, MDPI, vol. 10(12), pages 1-16, December.
    7. Tianqi Rong & Pengyan Zhang & Wenlong Jing & Yu Zhang & Yanyan Li & Dan Yang & Jiaxin Yang & Hao Chang & Linna Ge, 2020. "Carbon Dioxide Emissions and Their Driving Forces of Land Use Change Based on Economic Contributive Coefficient (ECC) and Ecological Support Coefficient (ESC) in the Lower Yellow River Region (1995–20," Energies, MDPI, vol. 13(10), pages 1-18, May.
    8. Chenxi Li & Zenglei Xi, 2019. "Social Stability Risk Assessment of Land Expropriation: Lessons from the Chinese Case," IJERPH, MDPI, vol. 16(20), pages 1-20, October.
    9. Xiuyan Zhao & Changhong Miao, 2022. "Spatial-Temporal Changes and Simulation of Land Use in Metropolitan Areas: A Case of the Zhengzhou Metropolitan Area, China," IJERPH, MDPI, vol. 19(21), pages 1-27, October.

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