IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i22p15981-d1280998.html
   My bibliography  Save this article

Analyzing the Direction of Urban Function Renewal Based on the Complex Network

Author

Listed:
  • Jing Cheng

    (College of Civil and Transportation Engineering, Shenzhen University, Shenzhen 518060, China)

  • Xiaowei Luo

    (Department of Architecture and Civil Engineering, City University of Hong Kong, Kowloon, Hong Kong, China)

Abstract

Urban function renewal is essential for modern megacities’ urban planning and economic developments. This paper investigates the urban function renewal in Shenzhen, China based on a complex network method. According to the points of interest and the location quotient, the dominant urban functions in each district are discussed. After computing conditional probability, the interdependence of urban functions is analyzed. The complex networks of the functions and the corresponding clusters are presented to examine the relationship and the overall features of the functions, and the features of the function clusters, respectively. The average degree and average weighted degree of the main function categories of the functions are computed to explore the features of the function classification. The urban functions’ renewal potential index is calculated to show the potential of the non-dominant functions renewing to the dominant ones in the coming years. The difficulty index of the urban function renewal in each district is presented, and the difficulty degree of the original d-ominant function group renewing to a new one is obtained. The results show that more dominant urban functions have a significant probability of being dominant ones in a district; the functions of hotels and life services are essential in the planning and development in Shenzhen; and the districts with better economic levels have greater values of the difficulty of the urban function renewal. Then, the function renewal direction in Shenzhen is analyzed, and some policy implications are given.

Suggested Citation

  • Jing Cheng & Xiaowei Luo, 2023. "Analyzing the Direction of Urban Function Renewal Based on the Complex Network," Sustainability, MDPI, vol. 15(22), pages 1-22, November.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:22:p:15981-:d:1280998
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/22/15981/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/15/22/15981/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yu, Zidong & Zhu, Xiaolin & Liu, Xintao, 2022. "Characterizing metro stations via urban function: Thematic evidence from transit-oriented development (TOD) in Hong Kong," Journal of Transport Geography, Elsevier, vol. 99(C).
    2. Changwei Yuan & Yaxin Duan & Xinhua Mao & Ningyuan Ma & Jiannan Zhao, 2021. "Impact of the mixed degree of urban functions on the taxi travel demand," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-21, March.
    3. Qingke Gao & Jianhong Fu & Yang Yu & Xuehua Tang, 2019. "Identification of urban regions’ functions in Chengdu, China, based on vehicle trajectory data," PLOS ONE, Public Library of Science, vol. 14(4), pages 1-17, April.
    4. Guowei Luo & Jiayuan Ye & Jinfeng Wang & Yi Wei, 2023. "Urban Functional Zone Classification Based on POI Data and Machine Learning," Sustainability, MDPI, vol. 15(5), pages 1-18, March.
    5. Meead Saberi & Hani S. Mahmassani & Dirk Brockmann & Amir Hosseini, 2017. "A complex network perspective for characterizing urban travel demand patterns: graph theoretical analysis of large-scale origin–destination demand networks," Transportation, Springer, vol. 44(6), pages 1383-1402, November.
    6. repec:asg:wpaper:1001 is not listed on IDEAS
    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. Jing Cheng & Pei Yin, 2022. "Analysis of the Complex Network of the Urban Function under the Lockdown of COVID-19: Evidence from Shenzhen in China," Mathematics, MDPI, vol. 10(14), pages 1-20, July.
    2. Jiao, Hongzan & Huang, Shibiao & Zhou, Yu, 2023. "Understanding the land use function of station areas based on spatiotemporal similarity in rail transit ridership: A case study in Shanghai, China," Journal of Transport Geography, Elsevier, vol. 109(C).
    3. Jiangjun Wan & Chunchi Ma & Tian Jiang & Andrew Phillips & Xiong Wu & Yanlan Wang & Ziming Wang & Ying Cao, 2024. "A spatial econometric investigation into road traffic accessibility and economic growth: insights from the Chengdu-Chongqing twin-city economic circle," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-9, December.
    4. Lin, Yi & Zhang, Jianwei & Yang, Bo & Liu, Hong & Zhao, Liping, 2019. "An optimal routing strategy for transport networks with minimal transmission cost and high network capacity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 551-561.
    5. Ting Liu & Gang Cheng & Jie Yang, 2023. "Multi-Scale Recursive Identification of Urban Functional Areas Based on Multi-Source Data," Sustainability, MDPI, vol. 15(18), pages 1-24, September.
    6. Su, Shiliang & Wang, Zhuolun & Li, Bozhao & Kang, Mengjun, 2022. "Deciphering the influence of TOD on metro ridership: An integrated approach of extended node-place model and interpretable machine learning with planning implications," Journal of Transport Geography, Elsevier, vol. 104(C).
    7. Chan, Lok Shun, 2023. "Transition from fossil fuel propelled transport to electrified mass transit railway system - Experience from Hong Kong," Energy Policy, Elsevier, vol. 173(C).
    8. Guo, Shengyu & Zhou, Xinyu & Tang, Bing & Gong, Peisong, 2020. "Exploring the behavioral risk chains of accidents using complex network theory in the construction industry," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 560(C).
    9. Curado, Manuel & Tortosa, Leandro & Vicent, Jose F., 2021. "Identifying mobility patterns by means of centrality algorithms in multiplex networks," Applied Mathematics and Computation, Elsevier, vol. 406(C).
    10. Wei Yu & Xiaofei Ye & Jun Chen & Xingchen Yan & Tao Wang, 2020. "Evaluation Indexes and Correlation Analysis of Origination–Destination Travel Time of Nanjing Metro Based on Complex Network Method," Sustainability, MDPI, vol. 12(3), pages 1-21, February.
    11. Yang, Yitao & Jia, Bin & Yan, Xiao-Yong & Zhi, Danyue & Song, Dongdong & Chen, Yan & de Bok, Michiel & Tavasszy, Lóránt A. & Gao, Ziyou, 2023. "Uncovering and modeling the hierarchical organization of urban heavy truck flows," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 179(C).
    12. Guolei Zhou & Chenggu Li & Jing Zhang, 2020. "Identification of urban functions enhancement and weakening based on urban land use conversion: A case study of Changchun, China," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-14, June.
    13. Lei Pang & Yuxiao Jiang & Jingjing Wang & Ning Qiu & Xiang Xu & Lijian Ren & Xinyu Han, 2023. "Research of Metro Stations with Varying Patterns of Ridership and Their Relationship with Built Environment, on the Example of Tianjin, China," Sustainability, MDPI, vol. 15(12), pages 1-18, June.
    14. Mirco Nanni & Leandro Tortosa & José F Vicent & Gevorg Yeghikyan, 2020. "Ranking places in attributed temporal urban mobility networks," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-25, October.
    15. Guiwen Liu & Cheng Li & Taozhi Zhuang & Yuhan Zheng & Hongjuan Wu & Jian Tang, 2022. "Determining the Spatial Distribution Characteristics of Urban Regeneration Projects in China on the City Scale: The Case of Shenzhen," Land, MDPI, vol. 11(8), pages 1-27, July.
    16. Zhu, Lichao, 2023. "Comparative evaluation of CO2 emissions from transportation in countries around the world," Journal of Transport Geography, Elsevier, vol. 110(C).
    17. Shao, Fengjing & Sui, Yi & Yu, Xiang & Sun, Rencheng, 2019. "Spatio-temporal travel patterns of elderly people – A comparative study based on buses usage in Qingdao, China," Journal of Transport Geography, Elsevier, vol. 76(C), pages 178-190.
    18. Mohaddese Ghadiri & Robert Newell, 2024. "Rethinking Public Transit Networks Using Climate Change Mitigation and Social Justice Lenses: Great Victoria Area Case Study," Sustainability, MDPI, vol. 16(6), pages 1-23, March.
    19. Xinyu Zhuang & Li Zhang & Jie Lu, 2022. "Past—Present—Future: Urban Spatial Succession and Transition of Rail Transit Station Zones in Japan," IJERPH, MDPI, vol. 19(20), pages 1-35, October.
    20. Wei, Sheng & Zheng, Wei & Wang, Lei, 2021. "Understanding the configuration of bus networks in urban China from the perspective of network types and administrative division effect," Transport Policy, Elsevier, vol. 104(C), pages 1-17.

    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:22:p:15981-:d:1280998. 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.