An analysis on movement patterns between zones using smart card data in subway networks

Identifying zones and movement patterns of people is crucial to understanding adjacent regions and the relationship in urban areas. Most previous studies addressed zones or movement patterns separately without analysing simultaneously the two issues. In this paper, we propose an integrated approach to discover directly both zones and movement patterns among the zones, referred to as movement patterns between zones (MZPs), from historical boarding behaviours of passengers in subway networks by using an agglomerative clustering method. In addition, evaluation measures of MZPs are suggested in terms of coverage and accuracy. The effectiveness of the proposed approach is finally demonstrated through a real-world dataset obtained from smart cards on a subway network in Seoul, Korea.