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Extract the Spatiotemporal Distribution of Transit Trips from Smart Card Transaction Data: A Comparison Between Shanghai and Singapore

Chapter
Part of the Advances in Geographic Information Science book series (AGIS)

Abstract

This chapter provides a preliminary analysis and comparison of a week’s transit smart card transaction data of Shanghai and Singapore. The data provide a potential to extract continuous profiles of transit use of different types of card holders in their daily lives. Although the overall temporal pattern of transit trips appears to be similar among weekdays, there is considerable spatial variability of the trips as evidenced by the low trip repetitiveness rate. However, when the trips are aggregated to the station level, the overall spatial distributions of the boarding and alighting passengers appear to be alike in the most time of a day. In a nut shell, the exploration helps the researchers to form a general knowledge of the transit card data like the formats of the data, the types of information contained, as well as the strength and the weakness of the data. The general spatiotemporal patterns of transit trips exposed in this chapter provide a good foundation for further analysis and modeling in the future. Meanwhile, it is recognized that the interpretation of observed patterns at this step is mostly superficial and hypothetical. In order to have a profound understanding of these patterns and the underlying activity-travel behaviors, it is necessary to couple the transit smart card transaction data with other datasets.

Keywords

Spatiotemporal pattern Transit trips Smart card transaction data 

Notes

Acknowledgments

The chapter is partially supported by the Major Program of National Natural Science Foundation of China (project id 16ZDA048). I also aknowledge the partial support from the Singapore National Research Foundation through the Future Urban Mobility program of the Singapore-MIT Alliance for Research and Technology (SMART) Center.

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Department of International Shipping and Transportation EngineeringShanghai Jiao Tong UniversityShanghaiChina

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