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A new temporal–spatial dynamics method of simulating land-use change

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  • Liu, Dongya
  • Zheng, Xinqi
  • Zhang, Chunxiao
  • Wang, Hongbin

Abstract

The integration of a system dynamics (SD) model, a cellular automata (CA) model, and a Geographic Information System (GIS) is an important topic in the temporal and spatial simulation of land-use changes. Based on many previous studies, the temporal–spatial dynamics method (TSDM) has been proposed as a research framework that removes the limitations of using loosely coupled SD–CA–GIS. In this study, TSDM was successfully implemented in the NetLogo platform. The results show that: (1) Integration SD–CA–GIS based on grids leads to the seamless implementation of real-time data exchange among SD, CA, and GIS; (2) The temporal–spatial dynamic mechanisms can be represented using common time steps in SD–CA–GIS, and TSDM can be used for spatial visualization; and (3) The model accuracy can be improved by extending the CA transition rules with SD. The land-use patterns for 2000, 2010, and 2016 in Beijing, China, were simulated to test the TSDM implementation, and the simulation accuracies were 83.75%, 80.98%, and 77.40%, respectively. The results indicate that TSDM achieves a much better accuracy than conventional SD–CA–GIS coupled models, and is a more practical approach to simulate land-use change.

Suggested Citation

  • Liu, Dongya & Zheng, Xinqi & Zhang, Chunxiao & Wang, Hongbin, 2017. "A new temporal–spatial dynamics method of simulating land-use change," Ecological Modelling, Elsevier, vol. 350(C), pages 1-10.
    • Handle: RePEc:eee:ecomod:v:350:y:2017:i:c:p:1-10
    DOI: 10.1016/j.ecolmodel.2017.02.005
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    References listed on IDEAS

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    Cited by:

    1. 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).
    2. Fei Liu & Xinqi Zheng & Qing Huang, 2017. "Predictive Measurement of the Structure of Land Use in an Urban Agglomeration Space," Sustainability, MDPI, vol. 10(1), pages 1-13, December.
    3. Qihao Wang & Dongya Liu & Feiyao Gao & Xinqi Zheng & Yiqun Shang, 2023. "A Partitioned and Heterogeneous Land-Use Simulation Model by Integrating CA and Markov Model," Land, MDPI, vol. 12(2), pages 1-20, February.
    4. Ye Zhou & Feng Zhang & Zhenhong Du & Xinyue Ye & Renyi Liu, 2017. "Integrating Cellular Automata with the Deep Belief Network for Simulating Urban Growth," Sustainability, MDPI, vol. 9(10), pages 1-19, October.
    5. Datola, Giulia & Bottero, Marta & De Angelis, Elena & Romagnoli, Francesco, 2022. "Operationalising resilience: A methodological framework for assessing urban resilience through System Dynamics Model," Ecological Modelling, Elsevier, vol. 465(C).
    6. Liu, Dongya & Zheng, Xinqi & Wang, Hongbin & Zhang, Chunxiao & Li, Jiayang & Lv, Yongqiang, 2018. "Interoperable scenario simulation of land-use policy for Beijing–Tianjin–Hebei region, China," Land Use Policy, Elsevier, vol. 75(C), pages 155-165.

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