Google Scholar, researchGate
Human mobility, travel behavior, activity pattern analysis
- Su, R., Goulias, K.G. Untangling the relationships among residential environment, destination choice, and daily walk accessibility. Journal of Transport Geography, 2023. [link]
- Su, R., Xiao, J., McBride, E.C., Goulias, K.G. Understanding senior’s daily mobility patterns in California using human mobility motifs. Journal of Transport Geography, 2021. [link]
- Su, R., McBride, E.C., Goulias, K.G. Unveiling daily activity pattern differences between telecommuters and commuters using human mobility motifs and sequence analysis. Transportation Research Part A: Policy and Practice, 2021. [link]
- Su, R., Goulias, K.G. Evolution of the Chinese Spring Festival Travel network during the COVID-19 early outbreak. Transportation letters: the International Journal of Transportation Research, 2021. [link]
- Su, R., McBride, E.C., Goulias, K.G. Pattern recognition of daily activity patterns using human mobility motifs and sequence analysis. Transportation Research Part C: Emerging Technologies, 2020. [link]
- Su, R., Fang, Z., Xu, H., and Huang, L. Uncovering spatial inequality in taxi services in the context of a subsidy war among e-hailing apps. ISPRS International Journal of Geo-Information, 2018.
- Su, R., Fang, Z., Luo, N., and Zhu, J. Understanding the dynamics of the pick-up and drop-off locations of taxicabs in the context of a subsidy war among e-hailing apps. Sustainability, 2018.
- Shi, H.,Su, R., Xiao, J., Goulias, K. Spatiotemporal analysis of activity-travel fragmentation based on spatial clustering and sequence analysis. Journal of Transport Geography, 2022. [link]
- Xiao, J., Su, R., McBride, E.C., Goulias, K.G. Exploring the correlations between spatiotemporal daily activity-travel patterns and stated interest and perception of risk with self-driving cars. AGILE GIScience, 2020. [link]
- Fang, Z., Su, R., and Huang, L. Understanding the effect of an e-hailing app subsidy war on taxicab operation zones. Journal of Advanced Transportation, 2018.
- Goulias, K.G., McBride, E.C., Su, R. Life cycle stages, daily contacts, and activity travel time allocation for the benefit of self and others. In: Scheiner, J. and Rau, H. (eds) Mobility Across the Life Course, Publisher: Edward Elgar, 2020.
Movement analysis, interaction analysis, movement data science, time geography, scale
- Su, R., Dodge, S., Goulias, K. A classification framework and computational methods for human interaction analysis using movement data. Transactions in GIS, 2022. [link]
- Su, R., Dodge, S., Goulias, K. Understanding the impact of temporal scale on human movement analytics. Journal of Geographical Systems, 2022. [Editors’ choice article] [link]
- Su, R., Dodge, S., & Goulias, K. A time-geographic approach to quantify the duration of interaction in movement data. In Proceedings of the 1st ACM SIGSPATIAL International Workshop on Animal Movement Ecology and Human Mobility (pp. 18-26), 2021. [Best paper award] [link]
- Dodge, S., Su, R., Johnson, J., Simcharoen, A., Goulias, K.G., Smith, J., Ahearn, S. ORTEGA: an object-oriented time-geographic analytical approach to trace space-time contact patterns in movement data. Computers, Environment and Urban Systems, 2021. [link]
