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Using POI Data to Identify the Demand for Pedestrian Crossing Facilities at Mid-Block

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  • Weifeng Li

    (Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, 4800 Cao’an Road, Shanghai 201804, China)

  • Jiawei He

    (Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, 4800 Cao’an Road, Shanghai 201804, China)

  • Qing Yu

    (Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, 4800 Cao’an Road, Shanghai 201804, China
    Center for Spatial Information Science, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa 277-8568, Japan)

  • Yujiao Chang

    (College of Transportation Engineering, Chang’an University, Middle-Section of Nan’er Huan Road, Xi’an 710064, China)

  • Peng Liu

    (Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, 4800 Cao’an Road, Shanghai 201804, China)

Abstract

In Chinese cities, the widespread problem of the low density of the road network has seriously damaged the convenience of pedestrian crossing, resulting in an unfriendly pedestrian experience and restricted development of non-motorized traffic within the city. Only by accurately capturing the crossing needs of pedestrians can we adopt a targeted approach to improve the pedestrian crossing experience. In this paper, the demand and supply are considered synthetically, and a method of using point of interest (POI) data to analyze the demand for pedestrian crossing facilities at the mid-block is proposed. First, we developed the method of calculating the pedestrian crossing demand intensity based on POI data. Secondly, based on the appropriate length threshold and pedestrian crossing demand intensity threshold, a series of road sections with strong demand for pedestrian crossing facilities are identified in the study area. Finally, we use mobile phone data to obtain the intensity of residents’ activity in different areas, and find that the distribution of the areas with more activity is basically the same as that of the target road sections. The result shows that the method proposed in this paper can effectively identify the road sections with strong demand for crossing facilities at mid-block, and can provide support for the improvement of urban non-motorized traffic.

Suggested Citation

  • Weifeng Li & Jiawei He & Qing Yu & Yujiao Chang & Peng Liu, 2021. "Using POI Data to Identify the Demand for Pedestrian Crossing Facilities at Mid-Block," Sustainability, MDPI, vol. 13(23), pages 1-13, November.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:23:p:13256-:d:691583
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    Cited by:

    1. Wen Liang & Yahaya Ahmad & Hazrina Haja Bava Mohidin, 2024. "Spatial pattern and influencing factors of tourism based on POI data in Chengdu, China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(4), pages 10127-10143, April.
    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. Yao Chang & Dongbing Li & Zibibula Simayi & Shengtian Yang & Maliyamuguli Abulimiti & Yiwei Ren, 2022. "Spatial Pattern Analysis of Xinjiang Tourism Resources Based on Electronic Map Points of Interest," IJERPH, MDPI, vol. 19(13), pages 1-18, June.

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