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Research on the Coupling Relationship Between Park and Metro Station Space in Qingdao

Author

Listed:
  • Peng Dai

    (College of Civil Engineering and Architecture, Shandong University of Science and Technology, Qingdao 266590, China)

  • Lufang Bi

    (College of Civil Engineering and Architecture, Shandong University of Science and Technology, Qingdao 266590, China)

  • Shi Cen

    (College of Civil Engineering and Architecture, Shandong University of Science and Technology, Qingdao 266590, China)

  • Guannan Fu

    (College of Civil Engineering and Architecture, Shandong University of Science and Technology, Qingdao 266590, China)

  • Hui Fang

    (College of Civil Engineering and Architecture, Shandong University of Science and Technology, Qingdao 266590, China)

  • Yanjun Wang

    (College of Civil Engineering and Architecture, Shandong University of Science and Technology, Qingdao 266590, China)

Abstract

As indispensable elements of public space in the city, metro stations and parks have the dual characteristics of “node” and “place”. Based on the “node–place” theoretical framework, the spatial evaluation and detailed classification of Qingdao metro station is carried out by integrating ArcGIS technology and diversified data sources. On this basis, an innovative metro station spatial coupling evaluation model is constructed, which takes into account the station carrying capacity, park accessibility, land use degree, and other factors, while evaluating the economic and environmental benefits. This study deeply explores the complex coupling relationship between the surrounding metro stations and park space in Qingdao. According to the results of the evaluation model, corresponding strategies for different types of station space are proposed. By taking measures, such as focusing on fine development strategies, stimulating the vitality of stations and implementing guided renewal, and enhancing the mutual suitability of rail transit and surrounding park space, the great potential of combining green ecology with urban space optimization is demonstrated.

Suggested Citation

  • Peng Dai & Lufang Bi & Shi Cen & Guannan Fu & Hui Fang & Yanjun Wang, 2025. "Research on the Coupling Relationship Between Park and Metro Station Space in Qingdao," Sustainability, MDPI, vol. 17(7), pages 1-18, March.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:7:p:3029-:d:1623173
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    References listed on IDEAS

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    1. Ciyun Lin & Kang Wang & Dayong Wu & Bowen Gong, 2020. "Passenger Flow Prediction Based on Land Use around Metro Stations: A Case Study," Sustainability, MDPI, vol. 12(17), pages 1-22, August.
    2. 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).
    3. 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.
    4. Shimei Li & Xueyan Zeng & Xiaoguang Zhang & Jiancheng Jiang & Furong Wang & Tianci Zhang & Jiacheng Zhang, 2024. "Spatial Justice of Urban Park Green Space under Multiple Travel Modes and at Multiple Scales: A Case Study of Qingdao City Center, China," Sustainability, MDPI, vol. 16(4), pages 1-13, February.
    5. Bertolini, L. & le Clercq, F. & Kapoen, L., 2005. "Sustainable accessibility: a conceptual framework to integrate transport and land use plan-making. Two test-applications in the Netherlands and a reflection on the way forward," Transport Policy, Elsevier, vol. 12(3), pages 207-220, May.
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    1. Xu Lu & Mengqin Zhu & Zeting Li & Qingyu Li & Shan Huang, 2025. "Urban Renewal Strategy Guided by Rail Transit Development Based on the “Node–Place–Revenue” Model: Case Study of Shenyang Metro Line 1," Land, MDPI, vol. 14(6), pages 1-23, June.

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