IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v13y2024i2p161-d1329704.html
   My bibliography  Save this article

Deciphering Urban Land Use Patterns in the Shenzhen–Dongguan Cross-Boundary Region Based on Multisource Data

Author

Listed:
  • Likun Wu

    (School of Geography and Planning, Sun Yat-sen University, Guangzhou 510006, China
    China Regional Coordinated Development and Rural Construction Institute, Sun Yat-sen University, Guangzhou 510275, China)

  • Wei Lang

    (School of Geography and Planning, Sun Yat-sen University, Guangzhou 510006, China
    China Regional Coordinated Development and Rural Construction Institute, Sun Yat-sen University, Guangzhou 510275, China)

  • Tingting Chen

    (School of Geography and Planning, Sun Yat-sen University, Guangzhou 510006, China
    China Regional Coordinated Development and Rural Construction Institute, Sun Yat-sen University, Guangzhou 510275, China)

Abstract

Against the backdrop of coordinated development and regional integration in the Guangdong–Hong Kong–Macao Greater Bay Area, China, the integration of Shenzhen and Dongguan has received increasing attention from both academia and the government. The cross-boundary area of the two cities has also shifted from being categorized as the development edge to becoming a key area, presenting more complex spatial and functional characteristics. This paper applies multi-source data to analyze the spatial characteristics and factors of influence in the Shenzhen–Dongguan cross-boundary region from the perspective of urban land use pattern evolution. The results showed that from 2008 to 2022, (1) the spatial structure presented a development trend from multi-core to axial, then to network, gradually breaking down the development barriers in the central region; (2) the function of regional land was transformed from a single type to a composite and mixed type, and the layout of commercial, public, green, and transportation land became more dispersed and balanced; (3) the cross-administrative boundaries of commercial land were exaggerated, and industrial land was widely transformed into composite industrial and commercial land, forming an integrated industrial belt; and (4) the overall increase in the mixing degree of land use functions indicated that the two regions were interconnected and integrated with each other, and the functional structure of the cross-boundary region was relatively more complete.

Suggested Citation

  • Likun Wu & Wei Lang & Tingting Chen, 2024. "Deciphering Urban Land Use Patterns in the Shenzhen–Dongguan Cross-Boundary Region Based on Multisource Data," Land, MDPI, vol. 13(2), pages 1-24, January.
    • Handle: RePEc:gam:jlands:v:13:y:2024:i:2:p:161-:d:1329704
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/13/2/161/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2073-445X/13/2/161/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kim Dovey & Elek Pafka, 2017. "What is functional mix? An assemblage approach," Planning Theory & Practice, Taylor & Francis Journals, vol. 18(2), pages 249-267, April.
    2. Wei Lang & Muzhe Pan & Jiemin Wu & Tingting Chen & Xun Li, 2021. "The patterns and driving forces of uneven regional growth in ASEAN countries: A tale of two Thailands' path toward regional coordinated development," Growth and Change, Wiley Blackwell, vol. 52(1), pages 130-149, March.
    3. Wang, Chenglong & Liu, Hui & Zhang, Mengtian & Wei, Zongcai, 2018. "The border effect on urban land expansion in China: The case of Beijing-Tianjin-Hebei region," Land Use Policy, Elsevier, vol. 78(C), pages 287-294.
    4. Yan Huang & Wei Lang & Tingting Chen & Jiemin Wu, 2023. "Regional Coordinated Development in the Megacity Regions: Spatial Pattern and Driving Forces of the Guangzhou-Foshan Cross-Border Area in China," Land, MDPI, vol. 12(4), pages 1-27, March.
    Full references (including those not matched with items on IDEAS)

    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. Zhang, Pengyan & Yang, Dan & Qin, Mingzhou & Jing, Wenlong, 2020. "Spatial heterogeneity analysis and driving forces exploring of built-up land development intensity in Chinese prefecture-level cities and implications for future Urban Land intensive use," Land Use Policy, Elsevier, vol. 99(C).
    2. Jianwei Li & Yun Chen & Dan Zhao & Jiagang Zhai, 2024. "The Impact of Built Environment on Mixed Land Use: Evidence from Xi’an," Land, MDPI, vol. 13(12), pages 1-19, December.
    3. Zhang Zhang & Huimin Zhou & Shuxian Li & Zhibin Zhao & Junbo Xu & Yuansuo Zhang, 2024. "Study on the Spatiotemporal Evolution of Urban Land Use Efficiency in the Beijing–Tianjin–Hebei Region," Sustainability, MDPI, vol. 16(7), pages 1-27, April.
    4. Hiranya Sritart & Somchat Taertulakarn & Hiroyuki Miyazaki, 2022. "Disparities in Childhood Obesity Prevalence and Spatial Clustering Related to Socioeconomic Factors in Isaan, Thailand," IJERPH, MDPI, vol. 20(1), pages 1-18, December.
    5. Kim Dovey & Elek Pafka, 2020. "What is walkability? The urban DMA," Urban Studies, Urban Studies Journal Limited, vol. 57(1), pages 93-108, January.
    6. Xiaxuan He & Qifeng Yuan & Yinghong Qin & Junwen Lu & Gang Li, 2024. "Analysis of Surface Urban Heat Island in the Guangzhou-Foshan Metropolitan Area Based on Local Climate Zones," Land, MDPI, vol. 13(10), pages 1-34, October.
    7. Francesc Valls & Josep Roca, 2021. "Visualizing Digital Traces for Sustainable Urban Management: Mapping Tourism Activity on the Virtual Public Space," Sustainability, MDPI, vol. 13(6), pages 1-20, March.
    8. Liu Liu & Huang Huang & Jiali Yang, 2024. "Enhancing Detailed Planning from Functional Mix Perspective with Spatial Analysis and Multiscale Geographically Weighted Regression: A Case Study in Shanghai Central Region," Land, MDPI, vol. 13(12), pages 1-22, December.
    9. Haiyang Qiu & Xin Li & Long Zhang, 2023. "Influential Effect and Mechanism of Digital Finance on Urban Land Use Efficiency in China," Sustainability, MDPI, vol. 15(20), pages 1-21, October.
    10. Hechang Cai & Zhijun Feng & Wen Zhou & Jinghan Chen & Zinan Chen, 2023. "Understanding the spatial polarization pattern of technology transfer network in the Guangdong–Hong Kong–Macao Greater Bay area," Growth and Change, Wiley Blackwell, vol. 54(1), pages 4-25, March.
    11. Uddin, Gazi Salah & Hasan, Md. Bokhtiar & Phoumin, Han & Taghizadeh-Hesary, Farhad & Ahmed, Ali & Troster, Victor, 2023. "Exploring the critical demand drivers of electricity consumption in Thailand," Energy Economics, Elsevier, vol. 125(C).
    12. Kim Dovey & Ian Woodcock & Lucinda Pike, 2017. "Isochrone Mapping of Urban Transport: Car-dependency, Mode-choice and Design Research," Planning Practice & Research, Taylor & Francis Journals, vol. 32(4), pages 402-416, August.
    13. Cefang Deng & Dailin Zhou & Yiming Wang & Jie Wu & Zhe Yin, 2024. "Association between Land Use and Urban Vitality in the Guangdong–Hong Kong–Macao Greater Bay Area: A Multiscale Study," Land, MDPI, vol. 13(10), pages 1-17, September.
    14. Wang, Chenglong & Liu, Hui & Zhang, Mengtian, 2020. "Exploring the mechanism of border effect on urban land expansion: A case study of Beijing-Tianjin-Hebei region in China," Land Use Policy, Elsevier, vol. 92(C).
    15. Yuchen Qin & Yikang Zhang & Minfeng Yao & Qiwei Chen, 2023. "How to Measure the Impact of Walking Accessibility of Suburban Rail Station Catchment Areas on the Commercial Premium Benefits of Joint Development," Sustainability, MDPI, vol. 15(6), pages 1-29, March.
    16. Carles Crosas & Eulàlia Gómez-Escoda & Enric Villavieja, 2024. "Interplay between Land Use Planning and Functional Mix Dimensions: An Assemblage Approach for Metropolitan Barcelona," Sustainability, MDPI, vol. 16(17), pages 1-20, September.
    17. Zhang, Wenxi & Wang, Bo & Wang, Jian & Wu, Qun & Wei, Yehua Dennis, 2022. "How does industrial agglomeration affect urban land use efficiency? A spatial analysis of Chinese cities," Land Use Policy, Elsevier, vol. 119(C).
    18. Wu, Changyan & Huang, Xianjin & Chen, Bowen, 2020. "Telecoupling mechanism of urban land expansion based on transportation accessibility: A case study of transitional Yangtze River economic Belt, China," Land Use Policy, Elsevier, vol. 96(C).
    19. Elek Pafka & Kim Dovey & Gideon DPA Aschwanden, 2020. "Limits of space syntax for urban design: Axiality, scale and sinuosity," Environment and Planning B, , vol. 47(3), pages 508-522, March.
    20. Muzhe Pan & Yaofu Huang & Yawen Qin & Xun Li & Wei Lang, 2022. "Problems and Strategies of Allocating Public Service Resources in Rural Areas in the Context of County Urbanization," IJERPH, MDPI, vol. 19(21), pages 1-20, November.

    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:13:y:2024:i:2:p:161-:d:1329704. 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.