IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i14p10917-d1192250.html
   My bibliography  Save this article

Analysis of Construction Networks and Structural Characteristics of Pearl River Delta and Surrounding Cities Based on Multiple Connections

Author

Listed:
  • Shengdong Nie

    (School of Civil and Surveying and Mapping Engineering, Jiangxi University of Science and Technology, Ganzhou 341000, China)

  • Hengkai Li

    (School of Civil and Surveying and Mapping Engineering, Jiangxi University of Science and Technology, Ganzhou 341000, China)

Abstract

The Pearl River Delta (PRD) is one of three world-class city clusters in China, which is important for the strategical deployment of the national “Belt and Road”. Based on nighttime lighting data, Baidu index, and train stopping times, this study analyzed the network of spatial patterns and structural evolution of the PRD and surrounding cities via social network analysis and dynamic network visualization, providing new perspectives and ideas for the study of intercity linkages and urban networks. The results provide decision support to the government for urban cluster planning. From 2014 to 2020, the economic network evolved from a uniaxial structure to an “inverted V” structure. The transportation network evolved from a uniaxial structure to a “△” structure. The information network did not show any obvious structural changes during its development, except for a star-shaped radial structure. The PRD city cluster and its surrounding cities exhibited a spatially non-uniform distribution in terms of spatial connections. The total connections between Guangzhou and Foshan and the surrounding cities in terms of economic, transportation, and information functions account for 30%, 28%, and 10% of the total urban connections, respectively. The graph entropy growth rates of the PRD city cluster and surrounding cities in economic, transportation, and information networks from 2014 to 2020 were 39.9%, 115.4%, and 5.1%, respectively. The network structures of economic and transportation networks stabilized eventually. The information network structures are stable.

Suggested Citation

  • Shengdong Nie & Hengkai Li, 2023. "Analysis of Construction Networks and Structural Characteristics of Pearl River Delta and Surrounding Cities Based on Multiple Connections," Sustainability, MDPI, vol. 15(14), pages 1-26, July.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:14:p:10917-:d:1192250
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/14/10917/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/14/10917/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Roberta Capello, 2000. "The City Network Paradigm: Measuring Urban Network Externalities," Urban Studies, Urban Studies Journal Limited, vol. 37(11), pages 1925-1945, October.
    2. Qiaowen Lin & Mengyu Xiang & Lu Zhang & Jinjiang Yao & Chao Wei & Sheng Ye & Hongmei Shao, 2021. "Research on Urban Spatial Connection and Network Structure of Urban Agglomeration in Yangtze River Delta—Based on the Perspective of Information Flow," IJERPH, MDPI, vol. 18(19), pages 1-20, September.
    3. Chengzhuo Wu & Li Zhuo & Zhuo Chen & Haiyan Tao, 2021. "Spatial Spillover Effect and Influencing Factors of Information Flow in Urban Agglomerations—Case Study of China Based on Baidu Search Index," Sustainability, MDPI, vol. 13(14), pages 1-17, July.
    4. Jinliang Jiang & Zhensheng Xu & Jiayi Lu & Dongqi Sun, 2022. "Does Network Externality of Urban Agglomeration Benefit Urban Economic Growth—A Case Study of the Yangtze River Delta," Land, MDPI, vol. 11(4), pages 1-19, April.
    5. Yubo Zhao & Gui Zhang & Hongwei Zhao & Anirban Chakraborti, 2021. "Spatial Network Structures of Urban Agglomeration Based on the Improved Gravity Model: A Case Study in China’s Two Urban Agglomerations," Complexity, Hindawi, vol. 2021, pages 1-17, February.
    6. Narisra Limtanakool & Tim Schwanen & Martin Dijst, 2009. "Developments in the Dutch Urban System on the Basis of Flows," Regional Studies, Taylor & Francis Journals, vol. 43(2), pages 179-196.
    7. Wang, Wei & Cai, Kaiquan & Du, Wenbo & Wu, Xin & Tong, Lu (Carol) & Zhu, Xi & Cao, Xianbin, 2020. "Analysis of the Chinese railway system as a complex network," Chaos, Solitons & Fractals, Elsevier, vol. 130(C).
    8. Wang, Feng & Wei, Xianjin & Liu, Juan & He, Lingyun & Gao, Mengnan, 2019. "Impact of high-speed rail on population mobility and urbanisation: A case study on Yangtze River Delta urban agglomeration, China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 127(C), pages 99-114.
    9. Qipeng Sun & Sijie Wang & Kaiqi Zhang & Fei Ma & Xiaozhuang Guo & Tingzhen Li, 2019. "Spatial Pattern of Urban System Based on Gravity Model and Whole Network Analysis in Eight Urban Agglomerations of China," Mathematical Problems in Engineering, Hindawi, vol. 2019, pages 1-17, August.
    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. Ma, Wen & Fang, Zhuoqiong & Zhang, Xiangfeng, 2023. "Comparative analysis of structural characteristics of China's 18 typical urban agglomerations based on flows of various elements," Ecological Modelling, Elsevier, vol. 479(C).
    2. Yang, Xiaolan & Wang, Rui & Guo, Dongmei & Sun, Weizeng, 2020. "The reconfiguration effect of China's high-speed railway on intercity connection ——A study based on media attention index," Transport Policy, Elsevier, vol. 95(C), pages 47-56.
    3. Wenfang Fu & Chuanjian Luo & Modan Yan, 2023. "Does Urban Agglomeration Promote the Development of Cities? Evidence from the Urban Network Externalities," Sustainability, MDPI, vol. 15(12), pages 1-20, June.
    4. You He & Alex de Sherbinin & Guoqing Shi & Haibin Xia, 2022. "The Economic Spatial Structure Evolution of Urban Agglomeration under the Impact of High-Speed Rail Construction: Is There a Difference between Developed and Developing Regions?," Land, MDPI, vol. 11(9), pages 1-17, September.
    5. Sujuan Li & Xiaohui Zhang & Xueling Wu & Erbin Xu, 2022. "Exploration of Urban Network Spatial Structure Based on Traffic Flow, Migration Flow and Information Flow: A Case Study of Shanxi Province, China," Sustainability, MDPI, vol. 14(23), pages 1-18, December.
    6. Cui, Wenyue & Tang, Jie, 2023. "Innovation convergence clubs and their driving factors within urban agglomeration," Economic Modelling, Elsevier, vol. 121(C).
    7. de Goei, B. & Burger, M.J. & van Oort, F.G. & Kitson, M., 2009. "Functional Polycentrism and Urban Network Development in the Greater South East UK: Evidence from Commuting Patterns, 1981-2001," ERIM Report Series Research in Management ERS-2009-038-ORG, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    8. Jiao, Jingjuan & Wang, Jiaoe & Jin, Fengjun, 2017. "Impacts of high-speed rail lines on the city network in China," Journal of Transport Geography, Elsevier, vol. 60(C), pages 257-266.
    9. Naoki FUJIWARA, 2019. "International City Network and Public-Private Cooperation Japanese Public Water Services’ Overseas Expansion," CIRIEC Working Papers 1909, CIRIEC - Université de Liège.
    10. Shuai Shi & Kathy Pain, 2020. "Investigating China’s Mid-Yangtze River economic growth region using a spatial network growth model," Urban Studies, Urban Studies Journal Limited, vol. 57(14), pages 2973-2993, November.
    11. Lan, Xiujuan & Hu, Zheneng & Wen, Chuanhao, 2023. "Does the opening of high-speed rail enhance urban entrepreneurial activity? Evidence from China," Socio-Economic Planning Sciences, Elsevier, vol. 88(C).
    12. Chen, Qifei & Wang, Meng, 2022. "Opening of high-speed rail and the consumer service industry: Evidence from China," Economic Analysis and Policy, Elsevier, vol. 76(C), pages 31-45.
    13. José Miguel Navarro-Azorín & Andrés Artal-Tur, 2017. "How much does urban location matter for growth?," European Planning Studies, Taylor & Francis Journals, vol. 25(2), pages 298-313, February.
    14. Chen, Yu & Zhao, Changyi & Chen, Shan & Chen, Wenqing & Wan, Kunyang & Wei, Jia, 2023. "Riding the green rails: Exploring the nexus between high-speed trains, green innovation, and carbon emissions," Energy, Elsevier, vol. 282(C).
    15. Evert Meijers & Martijn Burger & Roberto Camagni & Roberta Capello & Andrea Caragliu, 2016. "Static vs. dynamic agglomeration economies. Spatial context and structural evolution behind urban growth," Papers in Regional Science, Wiley Blackwell, vol. 95(1), pages 133-158, March.
    16. Yi Liu & Senbin Yu & Chaoyang Zhang & Peiran Zhang & Yang Wang & Liang Gao, 2022. "Critical Percolation on Temporal High-Speed Railway Networks," Mathematics, MDPI, vol. 10(24), pages 1-8, December.
    17. Jing Tao & Ying Wang & Rong Wang & Chuanmin Mi, 2019. "Do Compactness and Poly-Centricity Mitigate PM 10 Emissions? Evidence from Yangtze River Delta Area," IJERPH, MDPI, vol. 16(21), pages 1-18, October.
    18. Laurent Scaringella & Jean-Jacques Chanaron, 2016. "Grenoble–GIANT Territorial Innovation Models," Grenoble Ecole de Management (Post-Print) hal-01472878, HAL.
    19. Xiaodong Chen & Anda Guo & Jiahao Zhu & Fang Wang & Yanqiu He, 2022. "Accessing performance of transport sector considering risks of climate change and traffic accidents: joint bounded-adjusted measure and Luenberger decomposition," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 111(1), pages 115-138, March.
    20. Jaume Masip Tresserra, 2012. "Identifying the Employment and Population Centers at regional and metropolitan scale: The Case of Catalonia and Barcelona," ERSA conference papers ersa12p70, European Regional Science Association.

    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:jsusta:v:15:y:2023:i:14:p:10917-:d:1192250. 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.