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

Author

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  • 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
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    References listed on IDEAS

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    1. 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.
    2. 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.
    3. 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).
    4. 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.
    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
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