Analysing Interlinked Urban Functions through Mobility Motifs

This paper presented a work on mining mobility patterns using smart-card data. In particular, we investigated the interlinked urban functions from sequences of individuals’ daily trips. A spatiotemporal network approach is introduced with workflow and related data analysis specified. Using London Underground as a case study, the analytical result shows a universal pattern and spatial heterogeneity. Statistically, there is a universal pattern of mobility motif distribution, which is consistent with previous works using mobile and surveyed data. When extend the analysis to spatial dimension, relations between motifs and urban functions can be identified.