Study of the Spatial–Temporal Characteristics of College Students’ Activities Based on Mobile Phone Data

Mobile phone data is more frequently being applied in research to study the activity movements of different groups of people in cities. Involuntary mobile data with continuous trajectories generally lack social attributes, which makes classified crowd studies difficult to complete. However, college students who study in educational parks are especially suitable for involuntary mobile data to describe their activities due to their high residential concentration in the same geographic area. This paper explores the characteristics of college students’ daily activity patterns in Hangzhou by using mobile phone data in 2015 for a one-month period. We compared the students’ activity ranges at different times of the day as well as weekdays and weekends. In addition, we analyzed the weekend recreational activities of the students from colleges in different locations with distinct transportation infrastructures. The study results first showed that college students’ living patterns had a predictable schedule expressed by the three fixed activity peaks during the weekdays around 10 a.m., 3 p.m., and 8 p.m., with 8 p.m. being the time with the highest amount of activity at weekends. Then, when we focused on the differences in the travel distance and direction in disparate locations, we discovered the influence commercial centers and public transportation network had on travel patterns. A close mature commercial center can effectively reduce travel distance, while a well-developed public transportation network can improve accessibility allowing students to travel further along the public transportation lines.