The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLII-2/W13
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W13, 1375–1382, 2019
https://doi.org/10.5194/isprs-archives-XLII-2-W13-1375-2019
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W13, 1375–1382, 2019
https://doi.org/10.5194/isprs-archives-XLII-2-W13-1375-2019

  05 Jun 2019

05 Jun 2019

EXPLORING THE RELATIONSHIP BETWEEN TRAVEL PATTERN AND SOCIAL-DEMOGRAPHICS USING SMART CARD DATA AND HOUSEHOLD SURVEY

Y. Zhang, T. Cheng, and N. S. Aslam Y. Zhang et al.
  • SpaceTimeLab for Big Data Analytics, Dept. of Civil, Environmental & Geomatic Engineering, University College London, Gower Street, London, WC1E 6BT, UK

Keywords: Smart card data, Travel pattern, Social-demographics, Household survey, Relationships, Clustering

Abstract. Understanding social-demographics of passengers in public transit systems is significant for transportation operators and city planners in many real applications, such as forecasting travel demand and providing personalised transportation service. This paper develops an entire framework to analyse the relationship between passengers’ movement patterns and social-demographics by using smart card (SC) data with a household survey. The study first extracts various novel travel features of passengers from SC data, including spatial, temporal, travel mode and travel frequency features, to identify long-term travel patterns and their seasonality, for the in-depth understanding of ‘how’ people travel in cities. Leveraging household survey data, we then classify passengers into several groups based on their social-demographic characteristics, such as age, and working status, to identify the homogeneity of travellers for understanding ‘who’ travels using public transit. Finally, we explore the significant relationships between the travel patterns and demographic clusters. This research reveals explicit semantic explanations of ‘why’ passengers exhibit these travel patterns.