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Exploring Spatial-Temporal Patterns of Urban Human Mobility Hotspots

Author

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  • Xiping Yang

    (State Key Laboratory of Information Engineering in Surveying, Mapping, Remote and Sensing, Wuhan University, Wuhan 430079, China)

  • Zhiyuan Zhao

    (State Key Laboratory of Information Engineering in Surveying, Mapping, Remote and Sensing, Wuhan University, Wuhan 430079, China)

  • Shiwei Lu

    (State Key Laboratory of Information Engineering in Surveying, Mapping, Remote and Sensing, Wuhan University, Wuhan 430079, China)

Abstract

Understanding human mobility patterns provides us with knowledge about human mobility in an urban context, which plays a critical role in urban planning, traffic management and the spread of disease. Recently, the availability of large-scale human-sensing datasets enables us to analyze human mobility patterns and the relationships between humans and their living environments on an unprecedented spatial and temporal scale to improve decision-making regarding the quality of life of citizens. This study aims to characterize the urban spatial-temporal dynamic from the perspective of human mobility hotspots by using mobile phone location data. We propose a workflow to identify human convergent and dispersive hotspots that represent the status of human mobility in local areas and group these hotspots into different classes according to clustering their temporal signatures. To illustrate our proposed approach, a case study of Shenzhen, China, has been conducted. Six typical spatial-temporal patterns in the city are identified and discussed by combining the spatial distribution of these identified patterns with urban functional areas. The findings enable us to understand the human dynamics in a different area of the city, which can serve as a reference for urban planning and traffic management.

Suggested Citation

  • Xiping Yang & Zhiyuan Zhao & Shiwei Lu, 2016. "Exploring Spatial-Temporal Patterns of Urban Human Mobility Hotspots," Sustainability, MDPI, vol. 8(7), pages 1-18, July.
    • Handle: RePEc:gam:jsusta:v:8:y:2016:i:7:p:674-:d:74101
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    References listed on IDEAS

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    Cited by:

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    3. Jincheng Jiang & Jinsong Chen & Wei Tu & Chisheng Wang, 2019. "A Novel Effective Indicator of Weighted Inter-City Human Mobility Networks to Estimate Economic Development," Sustainability, MDPI, vol. 11(22), pages 1-18, November.
    4. Zuoxian Gan & Min Yang & Tao Feng & Harry Timmermans, 2020. "Understanding urban mobility patterns from a spatiotemporal perspective: daily ridership profiles of metro stations," Transportation, Springer, vol. 47(1), pages 315-336, February.
    5. Chengyue Zhang & Minmin Li & Ding Ma & Renzhong Guo, 2021. "How Different Are Population Movements between Weekdays and Weekends: A Complex-Network-Based Analysis on 36 Major Chinese Cities," Land, MDPI, vol. 10(11), pages 1-14, October.
    6. Shiwei Lu & Chaoyang Shi & Xiping Yang, 2019. "Impacts of Built Environment on Urban Vitality: Regression Analyses of Beijing and Chengdu, China," IJERPH, MDPI, vol. 16(23), pages 1-16, November.
    7. Qirui Li & Cyrus Samimi, 2023. "Assessing Human Mobility and Its Climatic and Socioeconomic Factors for Sustainable Development in Sub-Saharan Africa," Sustainability, MDPI, vol. 15(15), pages 1-16, July.
    8. Claudio Gariazzo & Armando Pelliccioni & Maria Paola Bogliolo, 2019. "Spatiotemporal Analysis of Urban Mobility Using Aggregate Mobile Phone Derived Presence and Demographic Data: A Case Study in the City of Rome, Italy," Data, MDPI, vol. 4(1), pages 1-25, January.
    9. Jiao, Hongzan & Huang, Shibiao & Zhou, Yu, 2023. "Understanding the land use function of station areas based on spatiotemporal similarity in rail transit ridership: A case study in Shanghai, China," Journal of Transport Geography, Elsevier, vol. 109(C).
    10. Xiping Yang & Zhixiang Fang & Ling Yin & Junyi Li & Yang Zhou & Shiwei Lu, 2018. "Understanding the Spatial Structure of Urban Commuting Using Mobile Phone Location Data: A Case Study of Shenzhen, China," Sustainability, MDPI, vol. 10(5), pages 1-14, May.
    11. Mateusz Ciski & Krzysztof Rząsa & Marek Ogryzek, 2019. "Use of GIS Tools in Sustainable Heritage Management—The Importance of Data Generalization in Spatial Modeling," Sustainability, MDPI, vol. 11(20), pages 1-21, October.

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