Human Mobility Datasets in the Complex Metro System of Shanghai
Abstract The growing role of metro systems in urban mobility calls for high-quality metro transit datasets. Derived from over 700 million smart card records, an open-sourced, city-scale metro flow dataset was constructed, covering the period of May-August 2017 and 302 metro stations in Shanghai, Chi...
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| Main Authors: | , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-06-01
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| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-025-05416-8 |
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| Summary: | Abstract The growing role of metro systems in urban mobility calls for high-quality metro transit datasets. Derived from over 700 million smart card records, an open-sourced, city-scale metro flow dataset was constructed, covering the period of May-August 2017 and 302 metro stations in Shanghai, China. The in-out flow counts of each station and OD flow between stations were offered at a 10-minute temporal resolution. By leveraging the mobility patterns of each passenger, metro flows were categorized into commuting flows, home-based-other flows, and none-home-based flows, providing a more comprehensive perspective towards urban mobility dynamics. Supplemental metadata, including station attributes, network topology, and meteorological records further support potential applications. This city-scale metro flow dataset could be utilized in advancing research in transportation modeling, spatio-temporal data mining, and urban mobility analysis. |
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| ISSN: | 2052-4463 |