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Relationship between Spatio-Temporal Travel Patterns Derived from Smart-Card Data and Local Environmental Characteristics of Seoul, Korea

Author

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  • Mi-Kyeong Kim

    (Department of Civil and Environmental Engineering, Yonsei University, Seoul 03722, Korea)

  • Sangpil Kim

    (Department of Civil and Environmental Engineering, Yonsei University, Seoul 03722, Korea)

  • Hong-Gyoo Sohn

    (Department of Civil and Environmental Engineering, Yonsei University, Seoul 03722, Korea)

Abstract

With the incorporation of an automated fare-collection system into the management of public transportation, not only can the quality of transportation services be improved but also that of the data collected from users when coupled with smart-card technology. The data collected from smart cards provide opportunities for researchers to analyze big data sets and draw meaningful information out of them. This study aims to identify the relationship between travel patterns derived from smart-card data and urban characteristics. Using seven-day transit smart-card data from the public-transportation system in Seoul, the capital city of the Republic of Korea, we investigated the temporal and spatial boarding and alighting patterns of the users. The major travel patterns, classified into five clusters, were identified by utilizing the K-Spectral Centroid clustering method. We found that the temporal pattern of urban mobility reflects daily activities in the urban area and that the spatial pattern of the five clusters classified by travel patterns was closely related to urban structure and urban function; that is, local environmental characteristics extracted from land-use and census data. This study confirmed that the travel patterns at the citywide level can be used to understand the dynamics of the urban population and the urban spatial structure. We believe that this study will provide valuable information about general patterns, which represent the possibility of finding travel patterns from individuals and urban spatial traits.

Suggested Citation

  • Mi-Kyeong Kim & Sangpil Kim & Hong-Gyoo Sohn, 2018. "Relationship between Spatio-Temporal Travel Patterns Derived from Smart-Card Data and Local Environmental Characteristics of Seoul, Korea," Sustainability, MDPI, vol. 10(3), pages 1-18, March.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:3:p:787-:d:135990
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    Cited by:

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    2. Yanyan Chen & Zheng Zhang & Tianwen Liang, 2019. "Assessing Urban Travel Patterns: An Analysis of Traffic Analysis Zone-Based Mobility Patterns," Sustainability, MDPI, vol. 11(19), pages 1-15, October.
    3. Su, Shiliang & Zhao, Chong & Zhou, Hao & Li, Bozhao & Kang, Mengjun, 2022. "Unraveling the relative contribution of TOD structural factors to metro ridership: A novel localized modeling approach with implications on spatial planning," Journal of Transport Geography, Elsevier, vol. 100(C).
    4. Lee, Hasik & Park, Ho-Chul & Kho, Seung-Young & Kim, Dong-Kyu, 2019. "Assessing transit competitiveness in Seoul considering actual transit travel times based on smart card data," Journal of Transport Geography, Elsevier, vol. 80(C).
    5. Liu, Yunzhe & Singleton, Alex & Arribas-Bel, Daniel, 2020. "Considering context and dynamics: A classification of transit-orientated development for New York City," Journal of Transport Geography, Elsevier, vol. 85(C).
    6. Christian Martin Mützel & Joachim Scheiner, 2022. "Investigating spatio-temporal mobility patterns and changes in metro usage under the impact of COVID-19 using Taipei Metro smart card data," Public Transport, Springer, vol. 14(2), pages 343-366, June.

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