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Identifying Urban Traveling Hotspots Using an Interaction-Based Spatio-Temporal Data Field and Trajectory Data: A Case Study within the Sixth Ring Road of Beijing

Author

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  • Disheng Yi

    (College of Resources Environment and Tourism, Capital Normal University, Beijing 100048, China
    Beijing Laboratory of Water Resources Security, Capital Normal University, Beijing 100048, China
    3D Information Collection and Application Key Lab of Education Ministry, Capital Normal University, Beijing 100048, China
    Beijing State Key Laboratory Incubation Base of Urban Environmental Processes and Digital Simulation, Capital Normal University, Beijing 100048, China)

  • Yusi Liu

    (College of Resources Environment and Tourism, Capital Normal University, Beijing 100048, China
    Beijing Laboratory of Water Resources Security, Capital Normal University, Beijing 100048, China
    3D Information Collection and Application Key Lab of Education Ministry, Capital Normal University, Beijing 100048, China
    Beijing State Key Laboratory Incubation Base of Urban Environmental Processes and Digital Simulation, Capital Normal University, Beijing 100048, China)

  • Jiahui Qin

    (College of Resources Environment and Tourism, Capital Normal University, Beijing 100048, China
    Beijing Laboratory of Water Resources Security, Capital Normal University, Beijing 100048, China
    3D Information Collection and Application Key Lab of Education Ministry, Capital Normal University, Beijing 100048, China
    Beijing State Key Laboratory Incubation Base of Urban Environmental Processes and Digital Simulation, Capital Normal University, Beijing 100048, China)

  • Jing Zhang

    (College of Resources Environment and Tourism, Capital Normal University, Beijing 100048, China
    Beijing Laboratory of Water Resources Security, Capital Normal University, Beijing 100048, China
    3D Information Collection and Application Key Lab of Education Ministry, Capital Normal University, Beijing 100048, China
    Beijing State Key Laboratory Incubation Base of Urban Environmental Processes and Digital Simulation, Capital Normal University, Beijing 100048, China)

Abstract

Exploring urban travelling hotspots has become a popular trend in geographic research in recent years. Their identification involved the idea of spatial autocorrelation and spatial clustering based on density in the previous research. However, there are some limitations to them, including the unremarkable results and the determination of various parameters. At the same time, none of them reflect the influences of their neighbors. Therefore, we used the concept of the data field and improved it with the impact of spatial interaction to solve those problems in this study. First of all, an interaction-based spatio-temporal data field identification for urban hotspots has been built. Then, the urban travelling hotspots of Beijing on weekdays and weekends are identified in six different periods. The detected hotspots are passed through qualitative and quantitative evaluations and compared with the other two methods. The results show that our method could discover more accurate hotspots than the other two methods. The spatio-temporal distributions of hotspots fit commuting activities, business activities, and nightlife activities on weekdays, and the hotspots discovered at weekends depict the entertainment activities of residents. Finally, we further discuss the spatial structures of urban hotspots in a particular period (09:00–12:00) as an example. It reflects the strong regularity of human travelling on weekdays, while human activities are more varied on weekends. Overall, this work has a certain theoretical and practical value for urban planning and traffic management.

Suggested Citation

  • Disheng Yi & Yusi Liu & Jiahui Qin & Jing Zhang, 2020. "Identifying Urban Traveling Hotspots Using an Interaction-Based Spatio-Temporal Data Field and Trajectory Data: A Case Study within the Sixth Ring Road of Beijing," Sustainability, MDPI, vol. 12(22), pages 1-20, November.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:22:p:9662-:d:447818
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    References listed on IDEAS

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    Cited by:

    1. Alexandre B. Gonçalves, 2021. "Spatial Analysis and Geographic Information Systems as Tools for Sustainability Research," Sustainability, MDPI, vol. 13(2), pages 1-3, January.
    2. Dokuz, Ahmet Sakir, 2022. "Weighted spatio-temporal taxi trajectory big data mining for regional traffic estimation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 589(C).
    3. Dokuz, Yesim & Dokuz, Ahmet Sakir, 2023. "Time-persistent regions discovery of taxi trajectory big datasets based on regional spatio-temporal velocity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 623(C).

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