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Scenario-Based Simulation of Tianjin City Using a Cellular Automata–Markov Model

Author

Listed:
  • Ruci Wang

    (Graduate School of Life and Environmental Science, University of Tsukuba, 1-1-1 Tennodai, Tsukuba City, Ibaraki 305-8572, Japan)

  • Hao Hou

    (Institute of Remote Sensing and Earth Sciences, Hangzhou Normal University, Yuhangtang Road No. 2318, Hangzhou 311121, China)

  • Yuji Murayama

    (Faculty of Life and Environmental Science, University of Tsukuba,1-1-1 Tennodai, Tsukuba City, Ibaraki 305-8572, Japan)

Abstract

Rapid urbanization is occurring throughout China, especially in megacities. Using a land use model to obtain future land use/cover conditions is an essential method to prevent chaotic urban sprawl and imbalanced development. This study utilized historical Landsat images to create land use/cover maps to predict the land use/cover changes of Tianjin city in 2025 and 2035. The cellular automata–Markov (CA–Markov) model was applied in the simulation under three scenarios: the environmental protection scenario (EPS), crop protection scenario (CPS), and spontaneous scenario (SS). The model achieved a kappa value of 86.6% with a figure of merit (FoM) of 12.18% when compared to the empirical land use/cover map in 2015. The results showed that the occupation of built-up areas increased from 29.13% in 2015 to 38.68% (EPS), 36.18% (CPS), and 47.94% (SS) in 2035. In this context, current urbanization would bring unprecedented stress on agricultural resources and forest ecosystems, which could be attenuated by implementing protection policies along with decelerating urban expansion. The findings provide valuable information for urban planners to achieve sustainable development goals.

Suggested Citation

  • Ruci Wang & Hao Hou & Yuji Murayama, 2018. "Scenario-Based Simulation of Tianjin City Using a Cellular Automata–Markov Model," Sustainability, MDPI, vol. 10(8), pages 1-20, July.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:8:p:2633-:d:160188
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    References listed on IDEAS

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    1. Yang, Xin & Zheng, Xin-Qi & Lv, Li-Na, 2012. "A spatiotemporal model of land use change based on ant colony optimization, Markov chain and cellular automata," Ecological Modelling, Elsevier, vol. 233(C), pages 11-19.
    2. K C Clarke & S Hoppen & L Gaydos, 1997. "A Self-Modifying Cellular Automaton Model of Historical Urbanization in the San Francisco Bay Area," Environment and Planning B, , vol. 24(2), pages 247-261, April.
    3. Ruiting Zhai & Chuanrong Zhang & Weidong Li & Mark A. Boyer & Dean Hanink, 2016. "Prediction of Land Use Change in Long Island Sound Watersheds Using Nighttime Light Data," Land, MDPI, vol. 5(4), pages 1-16, December.
    4. Cohen, Barney, 2004. "Urban Growth in Developing Countries: A Review of Current Trends and a Caution Regarding Existing Forecasts," World Development, Elsevier, vol. 32(1), pages 23-51, January.
    5. M Batty & H Couclelis & M Eichen, 1997. "Urban Systems as Cellular Automata," Environment and Planning B, , vol. 24(2), pages 159-164, April.
    6. Ruci Wang & Ahmed Derdouri & Yuji Murayama, 2018. "Spatiotemporal Simulation of Future Land Use/Cover Change Scenarios in the Tokyo Metropolitan Area," Sustainability, MDPI, vol. 10(6), pages 1-18, June.
    7. Guan, DongJie & Li, HaiFeng & Inohae, Takuro & Su, Weici & Nagaie, Tadashi & Hokao, Kazunori, 2011. "Modeling urban land use change by the integration of cellular automaton and Markov model," Ecological Modelling, Elsevier, vol. 222(20), pages 3761-3772.
    8. Wenjie Wang & Chuanrong Zhang & Jenica M. Allen & Weidong Li & Mark A. Boyer & Kathleen Segerson & John A. Silander, 2016. "Analysis and Prediction of Land Use Changes Related to Invasive Species and Major Driving Forces in the State of Connecticut," Land, MDPI, vol. 5(3), pages 1-22, July.
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    Cited by:

    1. Gebdang B. Ruben & Ke Zhang & Zengchuan Dong & Jun Xia, 2020. "Analysis and Projection of Land-Use/Land-Cover Dynamics through Scenario-Based Simulations Using the CA-Markov Model: A Case Study in Guanting Reservoir Basin, China," Sustainability, MDPI, vol. 12(9), pages 1-20, May.
    2. Xiaoe Ding & Minrui Zheng & Xinqi Zheng, 2021. "The Application of Genetic Algorithm in Land Use Optimization Research: A Review," Land, MDPI, vol. 10(5), pages 1-21, May.
    3. Selamawit Haftu Gebresellase & Zhiyong Wu & Huating Xu & Wada Idris Muhammad, 2023. "Scenario-Based LULC Dynamics Projection Using the CA–Markov Model on Upper Awash Basin (UAB), Ethiopia," Sustainability, MDPI, vol. 15(2), pages 1-27, January.

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