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Simulation and Analysis of Urban Production–Living–Ecological Space Evolution Based on a Macro–Micro Joint Decision Model

Author

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  • Yuanyuan Tao

    (School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China)

  • Qianxin Wang

    (School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China)

  • Yan Zou

    (School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China
    School of Humanity and Law, Beijing University of Civil Engineering and Architecture, Beijing 102616, China)

Abstract

The precise simulation of urban space evolution and grasping of the leading factors are the most important basis for urban space planning. However, the simulation ability of current models is lacking when it comes to complicated/unpredictable urban space changes, resulting in flawed government decision-making and wasting of urban resources. In this study, a macro–micro joint decision model was proposed to improve the ability of urban space evolution simulation. The simulation objects were unified into production, living and ecological space to realize “multiple planning in one”. For validation of the proposed model and method, remote sensing images, geographic information and socio-economic data of Xuzhou, China from 2000 to 2020 were collected and tested. The results showed that the simulation precision of the cellular automata (CA) model was about 87% (Kappa coefficient), which improved to 89% if using a CA and multi-agent system (MAS) joint model. The simulation precision could be better than 92% using the prosed model. The result of factor weight determination indicated that the micro factors affected the evolution of production and living space more than the macro factors, while the macro factors had more influence on the evolution of ecological space than the micro factors. Therefore, active policies should be formulated to strengthen the ideological guidance towards micro individuals (e.g., a resident, farmer, or entrepreneur), and avoid disordered development of living and production space. In addition, ecological space planning should closely link with the local environment and natural conditions, to improve urban ecological carrying capacity and realize urban sustainable development.

Suggested Citation

  • Yuanyuan Tao & Qianxin Wang & Yan Zou, 2021. "Simulation and Analysis of Urban Production–Living–Ecological Space Evolution Based on a Macro–Micro Joint Decision Model," IJERPH, MDPI, vol. 18(18), pages 1-21, September.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:18:p:9832-:d:638215
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    References listed on IDEAS

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    1. Jianfeng Zhu & Shenzhen Tian, 2020. "A Dynamic Urban Lake Area Evolution Model Based on Multilevel Grid, Cellular Automata, and Multiagent System," Complexity, Hindawi, vol. 2020, pages 1-19, September.
    2. Han Li & Long Li & Longqian Chen & Xisheng Zhou & Yifan Cui & Yunqiang Liu & Weiqiang Liu, 2019. "Mapping and Characterizing Spatiotemporal Dynamics of Impervious Surfaces Using Landsat Images: A Case Study of Xuzhou, East China from 1995 to 2018," Sustainability, MDPI, vol. 11(5), pages 1-22, February.
    3. Li Jiang & Yonghui Zhang, 2016. "Modeling Urban Expansion and Agricultural Land Conversion in Henan Province, China: An Integration of Land Use and Socioeconomic Data," Sustainability, MDPI, vol. 8(9), pages 1-12, September.
    4. Di Wang & Dong Jiang & Jingying Fu & Gang Lin & Jialun Zhang, 2020. "Comprehensive Assessment of Production–Living–Ecological Space Based on the Coupling Coordination Degree Model," Sustainability, MDPI, vol. 12(5), pages 1-18, March.
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    Cited by:

    1. Ning Xu & Wanxu Chen & Sipei Pan & Jiale Liang & Jiaojiao Bian, 2022. "Evolution Characteristics and Formation Mechanism of Production-Living-Ecological Space in China: Perspective of Main Function Zones," IJERPH, MDPI, vol. 19(16), pages 1-19, August.

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