IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v11y2022i9p1598-d917767.html
   My bibliography  Save this article

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

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/11/9/1598/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2073-445X/11/9/1598/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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).
    2. 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.
    3. 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.
    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. 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.
    6. Cui, Xuezhu & Li, Shaoying & Gao, Feng, 2020. "Examining spatial carbon metabolism: Features, future simulation, and land-based mitigation," Ecological Modelling, Elsevier, vol. 438(C).
    7. 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.
    8. 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).
    9. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Li Yuan & Jing Xu & Binrui Feng, 2024. "Evaluation and Prediction of Carbon Storage in the Qinghai-Tibet Plateau by Coupling the GMMOP and PLUS Models," Sustainability, MDPI, vol. 16(13), pages 1-19, July.
    2. 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.
    3. 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.
    4. Yang Zhang & Xiaojiang Xia & Jiandong Li & Luge Xing & Chengchao Yang & Haofeng Wang & Xiaoai Dai & Jue Wang, 2024. "Simulation of Urban Growth Boundary under the Guidance of Stock Development: A Case Study of Wuhan City," Land, MDPI, vol. 13(8), pages 1-22, July.
    5. Peian Wang & Chen Liu & Linlin Dai, 2024. "Spatiotemporal Variation and Prediction of Carbon Storage in Terrestrial Ecosystems at Multiple Development Stages in Beijing City Based on the Plus and Integrated Valuation of Ecosystem Services and ," Land, MDPI, vol. 13(9), pages 1-24, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jiaying Zhang & Yi Chen & Xuhong Yang & Wenyi Qiao & Danyang Wang, 2022. "The Demarcation of Urban Development Boundary Based on the Maxent-CA Model: A Case Study of Wuxi in China," Sustainability, MDPI, vol. 14(18), pages 1-21, September.
    2. Haitao Ji & Xiaoshun Li & Yiwei Geng & Xin Chen & Yuexiang Wang & Jumei Cheng & Zhuang Chen, 2023. "Delineation of Urban Development Boundary and Carbon Emission Effects in Xuzhou City, China," Land, MDPI, vol. 12(9), pages 1-16, September.
    3. Han, Wenjing & Zhang, Xiaoling & Zheng, Xian, 2020. "Land use regulation and urban land value: Evidence from China," Land Use Policy, Elsevier, vol. 92(C).
    4. Shuting Bai & Jiuchun Yang & Yubo Zhang & Fengqin Yan & Lingxue Yu & Shuwen Zhang, 2022. "Evaluating Ecosystem Services and Trade-Offs Based on Land-Use Simulation: A Case Study in the Farming–Pastoral Ecotone of Northern China," Land, MDPI, vol. 11(7), pages 1-17, July.
    5. Armands Auzins & Uchendu Eugene Chigbu, 2021. "Values-Led Planning Approach in Spatial Development: A Methodology," Land, MDPI, vol. 10(5), pages 1-19, April.
    6. Menzori, Ivan Damasco & Sousa, Isabel Cristina Nunes de & Gonçalves, Luciana Márcia, 2021. "Urban growth management and territorial governance approaches: A master plans conformance analysis," Land Use Policy, Elsevier, vol. 105(C).
    7. Zhang, Zhaolin & Zhai, Guocong & Xie, Kun & Xiao, Feng, 2022. "Exploring the nonlinear effects of ridesharing on public transit usage: A case study of San Diego," Journal of Transport Geography, Elsevier, vol. 104(C).
    8. Dadashpoor, Hashem & Sajadi, Afshin, 2024. "Principles of just urban land use planning," Land Use Policy, Elsevier, vol. 141(C).
    9. Chuanrong Zhang & Xinba Li, 2022. "Land Use and Land Cover Mapping in the Era of Big Data," Land, MDPI, vol. 11(10), pages 1-22, September.
    10. Wang, Jing & Wan, Feng & Dong, Chunjiao & Yin, Chaoying & Chen, Xiaoyu, 2023. "Spatiotemporal effects of built environment factors on varying rail transit station ridership patterns," Journal of Transport Geography, Elsevier, vol. 109(C).
    11. Zhenbao Wang & Jiarui Song & Yuchen Zhang & Shihao Li & Jianlin Jia & Chengcheng Song, 2022. "Spatial Heterogeneity Analysis for Influencing Factors of Outbound Ridership of Subway Stations Considering the Optimal Scale Range of “7D” Built Environments," Sustainability, MDPI, vol. 14(23), pages 1-21, December.
    12. Kikuko Shoyama, 2021. "Assessment of Land-Use Scenarios at a National Scale Using Intensity Analysis and Figure of Merit Components," Land, MDPI, vol. 10(4), pages 1-13, April.
    13. Langer, Sebastian & Korzhenevych, Artem, 2018. "The effect of industrial and commercial land consumption on municipal tax revenue: Evidence from Bavaria," Land Use Policy, Elsevier, vol. 77(C), pages 279-287.
    14. Yanan Li & Linghua Duo & Ming Zhang & Zhenhua Wu & Yanjun Guan, 2021. "Assessment and Estimation of the Spatial and Temporal Evolution of Landscape Patterns and Their Impact on Habitat Quality in Nanchang, China," Land, MDPI, vol. 10(10), pages 1-19, October.
    15. Mathur, Shishir, 2020. "Impact of transit stations on house prices across entire price spectrum: A quantile regression approach," Land Use Policy, Elsevier, vol. 99(C).
    16. Milne, Russell & Anand, Madhur & Bauch, Chris T., 2023. "Preparing for and managing crown-of-thorns starfish outbreaks on reefs under threat from interacting anthropogenic stressors," Ecological Modelling, Elsevier, vol. 484(C).
    17. Lixun Liu & Yujiang Wang & Robin Hickman, 2023. "How Rail Transit Makes a Difference in People’s Multimodal Travel Behaviours: An Analysis with the XGBoost Method," Land, MDPI, vol. 12(3), pages 1-23, March.
    18. Gao, Fan & Yang, Linchuan & Han, Chunyang & Tang, Jinjun & Li, Zhitao, 2022. "A network-distance-based geographically weighted regression model to examine spatiotemporal effects of station-level built environments on metro ridership," Journal of Transport Geography, Elsevier, vol. 105(C).
    19. Shouyi Ding & Shumi Liu & Mingxin Chang & Hanwei Lin & Tianyu Lv & Yujing Zhang & Chen Zeng, 2023. "Spatial Optimization of Land Use Pattern toward Carbon Mitigation Targets—A Study in Guangzhou," Land, MDPI, vol. 12(10), pages 1-19, October.
    20. Adewunmi, Yewande & Chigbu, Uchendu Eugene & Mwando, Sam & Kahireke, Uaurika, 2023. "Entrepreneurship role in the co-production of public services in informal settlements − A scoping review," Land Use Policy, Elsevier, vol. 125(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jlands:v:11:y:2022:i:9:p:1598-:d:917767. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.