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Research on Urban Street Network Structure Based on Spatial Syntax and POI Data

Author

Listed:
  • Luxiao Yang

    (Guangxi Key Laboratory of Green Building Materials and Construction Industrialization, School of Civil Engineering, Guilin University of Technology, Guilin 541004, China)

  • Qizhi Jin

    (Guangxi Key Laboratory of Green Building Materials and Construction Industrialization, School of Civil Engineering, Guilin University of Technology, Guilin 541004, China)

  • Feng Fu

    (Department of Engineering, School of Science and Technology, University of London, London EC1V OHB, UK)

Abstract

The rapid development of cities has led to increasingly problems in the road network structure of urban streets. Combining emerging big data technology with traditional street network analysis methods has become a new way to tackle it. Guilin is a famous international tourist city, and the “Two Rivers and Four Lakes” scenic area is an iconic symbol of Guilin’s scenery. Its streets connect various tourist spots. This study focused on the street’s layout of the “Two Rivers and Four Lakes” scenic area, and used a combination of spatial syntax and POI big data to analyse their spatial structure. The research results indicated that: (1) there was a positive correlation between the global integration value of the street and the POI value; (2) by combining functional density indicators with global integration analysis, streets that significantly deviate from the overall trend can be identified, and classified according to their characteristics to reveal the reasons for their contradictions; (3) we needed to propose three plans for optimizing the proportion of high street, enhancing street functions, and “improving street space” for different types of streets to ultimately realize the purpose of sustainable development of streets and cities.

Suggested Citation

  • Luxiao Yang & Qizhi Jin & Feng Fu, 2024. "Research on Urban Street Network Structure Based on Spatial Syntax and POI Data," Sustainability, MDPI, vol. 16(5), pages 1-22, February.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:5:p:1757-:d:1342866
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    References listed on IDEAS

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    2. Boeing, Geoff, 2017. "OSMnx: New Methods for Acquiring, Constructing, Analyzing, and Visualizing Complex Street Networks," SocArXiv q86sd, Center for Open Science.
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