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The Spatiotemporal Matching Relationship between Metro Networks and Urban Population from an Evolutionary Perspective: Passive Adaptation or Active Guidance?

Author

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  • Kexin Lei

    (School of Architecture, Chang’an University, Xi’an 710061, China
    Department of City and Regional Planning, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA)

  • Quanhua Hou

    (School of Architecture, Chang’an University, Xi’an 710061, China
    Engineering Research Center of Collaborative Planning of Low-Carbon Urban Space and Transportation, Universities of Shaanxi Province, Xi’an 710061, China)

  • Yaqiong Duan

    (School of Architecture, Chang’an University, Xi’an 710061, China
    Engineering Research Center of Collaborative Planning of Low-Carbon Urban Space and Transportation, Universities of Shaanxi Province, Xi’an 710061, China)

  • Yafei Xi

    (School of Architecture, Chang’an University, Xi’an 710061, China)

  • Su Chen

    (School of Architecture, Chang’an University, Xi’an 710061, China)

  • Yitong Miao

    (School of Architecture, Chang’an University, Xi’an 710061, China)

  • Haiyan Tong

    (School of Architecture, Chang’an University, Xi’an 710061, China)

  • Ziye Hu

    (School of Architecture, Chang’an University, Xi’an 710061, China)

Abstract

With the operation of the first route in Xi’an City, the matching relationship between the metro networks and the urban population is a root factor affecting the utilization of rail transit facilities. The mismatch between the metro networks and the urban population has led to an imbalance between the supply and demand for rail transport, resulting in wasted urban infrastructure. Based on this issue, the research objective is to focus on the spatiotemporal variations of the matching relationship. Firstly, the topological network model abstractly extracted metro spatial distribution features, and the spatial autocorrelation model was adopted to identify the evolution characteristics of the metro networks and urban population. Secondly, this paper adopted a time-lagged regression model to demonstrate the action relationship from 2011 to 2021. Then, the compositive coordination index was utilized to assess the variation of the global matching relationship. Finally, the paper explored spatial heterogeneity through the coupling coherence degree attached to grid cells. The research results indicate that the Moran’s I value of metro elements decreased from 0.782 to 0.510 with the further complexity of topological networks, while the population was consistently high in spatial dependence with a Moran’s I value of around 0.75 during the decade. Based on the regression coefficients and significance, this paper verified the hypothesis that the metro networks and urban population had a positive time-lagged feedback effect in urban development. From 2011 to 2021, the compositive coordination index symbolizing the global matching relationship increased from 0.29 to 0.90, but the coupling coherence degree shows significant spatial heterogeneity in different grid units. Differentiated spatial planning strategies were proposed for varied areas to efficiently utilize rail transit, which may provide a reference for other cities with the same reality problem.

Suggested Citation

  • Kexin Lei & Quanhua Hou & Yaqiong Duan & Yafei Xi & Su Chen & Yitong Miao & Haiyan Tong & Ziye Hu, 2024. "The Spatiotemporal Matching Relationship between Metro Networks and Urban Population from an Evolutionary Perspective: Passive Adaptation or Active Guidance?," Land, MDPI, vol. 13(8), pages 1-23, August.
    • Handle: RePEc:gam:jlands:v:13:y:2024:i:8:p:1200-:d:1449836
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    References listed on IDEAS

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    1. Jiang, Bin, 2007. "A topological pattern of urban street networks: Universality and peculiarity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 384(2), pages 647-655.
    2. Jingming Liu & Xianhui Hou & Chuyu Xia & Xiang Kang & Yujun Zhou, 2021. "Examining the Spatial Coordination between Metrorail Accessibility and Urban Spatial Form in the Context of Big Data," Land, MDPI, vol. 10(6), pages 1-20, May.
    3. Seaton, Katherine A. & Hackett, Lisa M., 2004. "Stations, trains and small-world networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 339(3), pages 635-644.
    4. Zhang, Jianhua & Wang, Shuliang & Wang, Xiaoyuan, 2018. "Comparison analysis on vulnerability of metro networks based on complex network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 72-78.
    5. Ouyang, Xiao & Tang, Lisha & Wei, Xiao & Li, Yonghui, 2021. "Spatial interaction between urbanization and ecosystem services in Chinese urban agglomerations," Land Use Policy, Elsevier, vol. 109(C).
    6. Meng, Yangyang & Tian, Xiangliang & Li, Zhongwen & Zhou, Wei & Zhou, Zhijie & Zhong, Maohua, 2020. "Comparison analysis on complex topological network models of urban rail transit: A case study of Shenzhen Metro in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 559(C).
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    1. Yun Liu & Zhiqiang Xie & Ping Wen & Chunhou Ji & Ling Zhu & Qisheng Wang & Zheng Zhang & Zhuoqian Xiao & Bojin Ning & Quan Zhu & Yan Yang, 2024. "Risk Evaluation of Urban Subway Site Selection: Balance, Attractiveness, and Financing Models," Land, MDPI, vol. 13(12), pages 1-27, November.

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