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A CLUMondo Model-Based Multi-Scenario Land-Use Change Simulation in the Yangtze River Delta Urban Agglomeration, China

Author

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  • Yanhua Zhao

    (Chinese Research Academy of Environmental Sciences, Beijing 100012, China
    Key Laboratory of Regional Eco-Process and Function Assessment and State Environment Protection, Beijing 100012, China)

  • De Su

    (Chinese Research Academy of Environmental Sciences, Beijing 100012, China
    Key Laboratory of Regional Eco-Process and Function Assessment and State Environment Protection, Beijing 100012, China)

  • Yang Bao

    (Chinese Research Academy of Environmental Sciences, Beijing 100012, China
    Key Laboratory of Regional Eco-Process and Function Assessment and State Environment Protection, Beijing 100012, China)

  • Wei Yang

    (Chinese Research Academy of Environmental Sciences, Beijing 100012, China
    Key Laboratory of Regional Eco-Process and Function Assessment and State Environment Protection, Beijing 100012, China)

  • Yibo Sun

    (Chinese Research Academy of Environmental Sciences, Beijing 100012, China
    Key Laboratory of Regional Eco-Process and Function Assessment and State Environment Protection, Beijing 100012, China)

Abstract

Land-use changes have profound effects on both socio-economic development and the environment. As a result, to optimize land-use planning and management, models are often employed to identify land-use patterns and their associated driving forces. In this work, physical and socioeconomic factors within the Yangtze River Delta Urban Agglomeration (YRDUA) from 2000 to 2015 were identified, integrated, and used as the foundation for a CLUMondo model. Subsequently, the Markov model and the CLUMondo model were combined to predict land-use changes in 2035. Natural growth (NG), economic development (ED), ecological protection (EP), and coordinated social and economic development (CSE) scenarios were set according to the land-use date in the assessment. Results showed that: (1) From 2000 to 2015, urban land increased by 8139.5 km 2 (3.93%), and the paddy field decreased by 7315.8 km 2 (8.78%). The Kappa coefficient of the CLUMondo model was 0.86, indicating that this model can be used to predict the land-use changes of the YRDUA. (2) When this trend was used to simulate landscape patterns in 2035, the land-use structure and landscape patterns varied among the four simulated urban development scenarios. Specifically, urban land increased by 47.6% (NG), 39.6% (ED), 32.9% (EP), and 23.2% (CSE). The paddy field was still the primary landscape, with 35.85% NG, 36.95% ED, 37.01% EP, and 36.96% CSE. Furthermore, under all four scenarios, the landscape pattern tended to simplify and fragment, while connectivity and equilibrium diminished. The results provided herein are intended to elucidate the law of urban agglomeration development and aid in promoting urban sustainable development.

Suggested Citation

  • Yanhua Zhao & De Su & Yang Bao & Wei Yang & Yibo Sun, 2022. "A CLUMondo Model-Based Multi-Scenario Land-Use Change Simulation in the Yangtze River Delta Urban Agglomeration, China," Sustainability, MDPI, vol. 14(22), pages 1-15, November.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:22:p:15336-:d:976886
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    References listed on IDEAS

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    1. Xingang Fan & Zhuguo Ma & Qing Yang & Yunhuan Han & Rezaul Mahmood & Ziyan Zheng, 2015. "Land use/land cover changes and regional climate over the Loess Plateau during 2001–2009. Part I: observational evidence," Climatic Change, Springer, vol. 129(3), pages 427-440, April.
    2. Gang Lin & Dong Jiang & Jingying Fu & Chenglong Cao & Dongwei Zhang, 2020. "Spatial Conflict of Production–Living–Ecological Space and Sustainable-Development Scenario Simulation in Yangtze River Delta Agglomerations," Sustainability, MDPI, vol. 12(6), pages 1-11, March.
    3. Wenyi Qiao & Weihua Guan & Xianjin Huang, 2021. "Assessing the Potential Impact of Land Use on Carbon Storage Driven by Economic Growth: A Case Study in Yangtze River Delta Urban Agglomeration," IJERPH, MDPI, vol. 18(22), pages 1-20, November.
    4. Tian, Guangjin & Jiang, Jing & Yang, Zhifeng & Zhang, Yaoqi, 2011. "The urban growth, size distribution and spatio-temporal dynamic pattern of the Yangtze River Delta megalopolitan region, China," Ecological Modelling, Elsevier, vol. 222(3), pages 865-878.
    5. Xingang Fan & Zhuguo Ma & Qing Yang & Yunhuan Han & Rezaul Mahmood, 2015. "Land use/land cover changes and regional climate over the Loess Plateau during 2001–2009. Part II: interrelationship from observations," Climatic Change, Springer, vol. 129(3), pages 441-455, April.
    6. Zimu Jia & Bingran Ma & Jing Zhang & Weihua Zeng, 2018. "Simulating Spatial-Temporal Changes of Land-Use Based on Ecological Redline Restrictions and Landscape Driving Factors: A Case Study in Beijing," Sustainability, MDPI, vol. 10(4), pages 1-18, April.
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