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Urban Growth Simulation Based on a Multi-Dimension Classification of Growth Types: Implications for China’s Territory Spatial Planning

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  • Siyu Miao

    (College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China
    Key Laboratory of Spatial Intelligent Planning Technology, Ministry of Natural Resources of the People’s Republic of China, Shanghai 200092, China)

  • Yang Xiao

    (College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China
    Key Laboratory of Spatial Intelligent Planning Technology, Ministry of Natural Resources of the People’s Republic of China, Shanghai 200092, China)

  • Ling Tang

    (Dongguan Geographic Information and Planning Research Center, Dongguan 523129, China)

Abstract

One of the primary aims of China’s territory spatial planning is to control the urban sprawl of local municipals and prevent regional competition and the negative consequences on the environment—which emphasizes the top-down spatial regulation. Indeed, the traditional cellular automaton (CA) model still has limitations when applied to the whole administration area since it may ignore the differences among cities and towns. Thus, this paper proposed a CM-CA (clustering, multi-level logit regression, integrated with cellular automaton) framework to simulate urban growth boundaries for cities and towns simultaneously. The significant novelty of this framework is to integrate several urban growth modes for all cities and towns. We applied our approach to the city of Xi’an, China, and the results showed satisfactory simulation accuracy of a CM-CA model for multiple cities and towns, and the clusters’ effects contributed 74% of the land change variance. Our study provides technical support for urban growth boundary delineation in China’s spatial planning.

Suggested Citation

  • Siyu Miao & Yang Xiao & Ling Tang, 2022. "Urban Growth Simulation Based on a Multi-Dimension Classification of Growth Types: Implications for China’s Territory Spatial Planning," Land, MDPI, vol. 11(12), pages 1-14, December.
    • Handle: RePEc:gam:jlands:v:11:y:2022:i:12:p:2210-:d:994069
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    References listed on IDEAS

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    1. Ilaria Tombolini & Ilaria Zambon & Achille Ippolito & Stathis Grigoriadis & Pere Serra & Luca Salvati, 2015. "Revisiting “Southern” Sprawl: Urban Growth, Socio-Spatial Structure and the Influence of Local Economic Contexts," Economies, MDPI, vol. 3(4), pages 1-23, December.
    2. Taher Osman & Prasanna Divigalpitiya & Takafumi Arima, 2016. "Using the SLEUTH urban growth model to simulate the impacts of future policy scenarios on land use in the Giza Governorate, Greater Cairo Metropolitan region," International Journal of Urban Sciences, Taylor & Francis Journals, vol. 20(3), pages 407-426, September.
    3. Luca Salvati & Margherita Carlucci, 2015. "Land-use structure, urban growth, and periurban landscape: a multivariate classification of the European cities," Environment and Planning B, , vol. 42(5), pages 801-829, September.
    4. Jan K. Brueckner, 2000. "Urban Sprawl: Diagnosis and Remedies," International Regional Science Review, , vol. 23(2), pages 160-171, April.
    5. Ding, Chengri & Knaap, Gerrit J. & Hopkins, Lewis D., 1999. "Managing Urban Growth with Urban Growth Boundaries: A Theoretical Analysis," Journal of Urban Economics, Elsevier, vol. 46(1), pages 53-68, July.
    6. 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.
    7. Yuan Wang & Yilong Han & Lijie Pu & Bo Jiang & Shaofeng Yuan & Yan Xu, 2021. "A Novel Model for Detecting Urban Fringe and Its Expanding Patterns: An Application in Harbin City, China," Land, MDPI, vol. 10(8), pages 1-16, August.
    8. Huang, Xinxin & Wang, Haijun & Xiao, Fentao, 2022. "Simulating urban growth affected by national and regional land use policies: Case study from Wuhan, China," Land Use Policy, Elsevier, vol. 112(C).
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