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Multi-Scenario Simulation of Land-Use Change and Delineation of Urban Growth Boundaries in County Area: A Case Study of Xinxing County, Guangdong Province

Author

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  • Zhipeng Lai

    (School of Geography and Remote Sensing, Guangzhou University, Guangzhou 510006, China)

  • Chengjing Chen

    (School of Geography and Remote Sensing, Guangzhou University, Guangzhou 510006, China)

  • Jianguo Chen

    (Center of GeoInformatics for Public Security, Guangzhou University, Guangzhou 510006, China)

  • Zhuo Wu

    (School of Geography and Remote Sensing, Guangzhou University, Guangzhou 510006, China)

  • Fang Wang

    (School of Geography and Remote Sensing, Guangzhou University, Guangzhou 510006, China)

  • Shaoying Li

    (School of Geography and Remote Sensing, Guangzhou University, Guangzhou 510006, China)

Abstract

Delineating urban growth boundaries (UGBs) by combining the land-use/land-cover (LULC) change simulation method has become common in recent studies. However, few of the existing studies have integrated multi-source big data to analyze the driving factors of LULC dynamics in the simulation. Moreover, most of previous studies mainly focused on the UGBs delineation in macroscale areas rather than small-scale areas, such as the county area. In this study, taking Xinxing County of Guangdong Province as the study area, we coupled a system dynamics (SD) model and a patch-generating land-use simulation (PLUS) model to propose a framework for the LULC change simulation and UGBs delineation in the county area. Multi-source big data such as points of interest (POIs), night-time light (NTL) data and Tencent user density (TUD) were integrated to analyze the driving forces of LULC change. The validation results indicate that the coupled model received high accuracy both in the land-use demand projection and LULC distribution simulation. The combination of multi-source big data can effectively describe the influence of human socio-economic factors on the expansion of urban land and industrial land. The UGBs delineation results have similar spatial patterns with the LULC change simulation results, which indicates that the proposed UGBs delineation method can effectively transform the LULC simulation results into available UGBs for the county area. It has been proven that the proposed framework in this study is effective for the LULC change simulation and UGBs delineation in the county area, which can provide insight on territorial spatial planning in the county area.

Suggested Citation

  • Zhipeng Lai & Chengjing Chen & Jianguo Chen & Zhuo Wu & Fang Wang & Shaoying Li, 2022. "Multi-Scenario Simulation of Land-Use Change and Delineation of Urban Growth Boundaries in County Area: A Case Study of Xinxing County, Guangdong Province," Land, MDPI, vol. 11(9), pages 1-18, September.
  • Handle: RePEc:gam:jlands:v:11:y:2022:i:9:p:1598-:d:917767
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    References listed on IDEAS

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    1. Dan Yi & Xi Guo & Yi Han & Jie Guo & Minghao Ou & Xiaomin Zhao, 2022. "Coupling Ecological Security Pattern Establishment and Construction Land Expansion Simulation for Urban Growth Boundary Delineation: Framework and Application," Land, MDPI, vol. 11(3), pages 1-18, March.
    2. Mathur, Shishir, 2019. "Impact of an urban growth boundary across the entire house price spectrum: The two-stage quantile spatial regression approach," Land Use Policy, Elsevier, vol. 80(C), pages 88-94.
    3. Lei, Yayuan & Flacke, Johannes & Schwarz, Nina, 2021. "Does Urban planning affect urban growth pattern? A case study of Shenzhen, China," Land Use Policy, Elsevier, vol. 101(C).
    4. Li, Shaoying & Lyu, Dijiang & Huang, Guanping & Zhang, Xiaohu & Gao, Feng & Chen, Yuting & Liu, Xiaoping, 2020. "Spatially varying impacts of built environment factors on rail transit ridership at station level: A case study in Guangzhou, China," Journal of Transport Geography, Elsevier, vol. 82(C).
    5. Uchendu Eugene Chigbu & Anna Schopf & Walter T. de Vries & Fahria Masum & Samuel Mabikke & Danilo Antonio & Jorge Espinoza, 2017. "Combining land-use planning and tenure security: a tenure responsive land-use planning approach for developing countries," Journal of Environmental Planning and Management, Taylor & Francis Journals, vol. 60(9), pages 1622-1639, September.
    6. Michael Ball & Melek Cigdem & Elizabeth Taylor & Gavin Wood, 2014. "Urban Growth Boundaries and their Impact on Land Prices," Environment and Planning A, , vol. 46(12), pages 3010-3026, December.
    7. Xia Li & Guangzhao Chen & Xiaoping Liu & Xun Liang & Shaojian Wang & Yimin Chen & Fengsong Pei & Xiaocong Xu, 2017. "A New Global Land-Use and Land-Cover Change Product at a 1-km Resolution for 2010 to 2100 Based on Human–Environment Interactions," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 107(5), pages 1040-1059, September.
    8. Cui, Xuezhu & Li, Shaoying & Gao, Feng, 2020. "Examining spatial carbon metabolism: Features, future simulation, and land-based mitigation," Ecological Modelling, Elsevier, vol. 438(C).
    9. Chen, Chengjing & Liu, Yihua, 2021. "Spatiotemporal changes of ecosystem services value by incorporating planning policies: A case of the Pearl River Delta, China," Ecological Modelling, Elsevier, vol. 461(C).
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    Cited by:

    1. Zhenzhi Jiao & Shaoying Li & Zhangping Lin & Zhipeng Lai & Zhuo Wu & Lin Liu, 2023. "Incorporating High-Speed Rail Development Scenario for Tourism Land Use Simulation: A Case Study of Xinxing County, China," Land, MDPI, vol. 12(6), pages 1-18, June.
    2. 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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