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The Interconnectivity and Spatio-Temporal Evolution of Rail Transit Network Based on Multi-Element Flows: A Case Study of Beijing-Tianjin-Hebei Urban Agglomeration, China

Author

Listed:
  • Xinyu Luan

    (School of Management Science and Real Estate, Chongqing University, Chongqing 400040, China
    Construction Economics and Management Research Center, Chongqing University, Chongqing 400045, China)

  • Pengcheng Xiang

    (School of Management Science and Real Estate, Chongqing University, Chongqing 400040, China
    Construction Economics and Management Research Center, Chongqing University, Chongqing 400045, China
    International Research Center for Sustainable Built Environment, Chongqing University, Chongqing 400045, China)

  • Fuyuan Jia

    (Antai College of Economics and Management, Shanghai Jiao Tong University, Shanghai 200030, China)

Abstract

For intercity transportation within urban agglomerations, rail transit interconnectivity not only stimulates city-to-city interactions but also facilitates the networking of urban spaces. Crucially, comprehending the spatial network of urban agglomerations needs a focus on rail transit interconnectivity. Drawing on the space of flows theory, this study establishes a framework to evaluate rail transit interconnectivity and the spatial structure of urban agglomerations, utilizing the Beijing-Tianjin-Hebei urban agglomeration as a case study. The objective of this study is to explore the impact of rail transit interconnectivity on the spatial structure in the urban agglomeration. Firstly, it establishes a coupled concept of urban quality and line quality to elucidate the interaction between rail transits and urban development. Secondly, it employs the AHP-CRITIC-TOPSIS and modified gravity model to evaluate the interconnectivity degree of rail transits and visualize the network. Thirdly, based on the multi-element flows facilitated by rail transit interconnectivity, the evolution of the spatial structure within the urban agglomeration is quantified using social network analysis. The study findings are as follows: (1) From 2010 to 2021, the interconnectivity degree of rail transit in the Beijing-Tianjin-Hebei urban agglomeration experienced substantial growth, emphasizing the correlation between interconnectivity and the city hierarchy within the urban agglomeration. (2) The interconnectivity degree of the Beijing-Tianjin-Hebei urban agglomeration shows an uneven pattern of “three cores and numerous weak links,” characterized by spatial polarization. (3) Rail transit interconnectivity contributes to shaping the spatial structure of urban agglomerations in terms of interconnectivity, polycentricity, and integration, although the enhancement of polycentricity is limited. The framework developed in this study can be extensively employed to investigate the interplay between rail transit interconnectivity and the spatial structure of urban agglomerations, thereby promoting the sustainability of regional planning.

Suggested Citation

  • Xinyu Luan & Pengcheng Xiang & Fuyuan Jia, 2024. "The Interconnectivity and Spatio-Temporal Evolution of Rail Transit Network Based on Multi-Element Flows: A Case Study of Beijing-Tianjin-Hebei Urban Agglomeration, China," Land, MDPI, vol. 13(2), pages 1-30, February.
  • Handle: RePEc:gam:jlands:v:13:y:2024:i:2:p:249-:d:1340734
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    References listed on IDEAS

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    1. Komei Sasaki & Tadahiro Ohashi & Asao Ando, 1997. "High-speed rail transit impact on regional systems: does the Shinkansen contribute to dispersion?," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 31(1), pages 77-98.
    2. Daniel (Jian) Sun & Shukai Chen & Chun Zhang & Suwan Shen, 2016. "A bus route evaluation model based on GIS and super-efficient data envelopment analysis," Transportation Planning and Technology, Taylor & Francis Journals, vol. 39(4), pages 407-423, June.
    3. Feifei Tan & Qunxi Kong, 2020. "Uncovering the driving mechanism of regional synergistic development based on Haken model: case of the Bohai Rim region," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(4), pages 3291-3308, April.
    4. Ma, Jian & Fan, Zhi-Ping & Huang, Li-Hua, 1999. "A subjective and objective integrated approach to determine attribute weights," European Journal of Operational Research, Elsevier, vol. 112(2), pages 397-404, January.
    5. Hong, Inho & Jung, Woo-Sung, 2016. "Application of gravity model on the Korean urban bus network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 48-55.
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