Smartphone-based spatiotemporal behavior analysis on college students in Chinese newly developed campus: A case study for Henan university

Abstract

Much research on spatiotemporal activity-travel to date has been conducted largely on the difference of human mobility patterns and accessibility within a week, and relatively little is used to guide the spatiotemporal sharing of infrastructure. This study attempts to fill this gap through examining the spatiotemporal behavior of college students. The paper used a random 1% proportional sample of students in the Jinming Campus of Henan University, and collected the activity-travel diary and 7-day GPS tracking data. The day-to-day variability in activity-travel behavior was analyzed by standard deviation confidence ellipse analysis, kernel density analysis, a GIS based 3D geovisualisation method, and so on. The results reveal significant differences for activity and travel in time rhythm and time allocation both in one day and in a week. Hence, the infrastructure can be shared with surrounding residents by avoiding the daily peaks of college students' activities. The results also suggest significant differences in activity tracks and activity space both in one day and in a week. The sharing potential can be improved through the spatial adjustment to network structure. Besides, the results shows that the spatiotemporal behavior can be measured by spatiotemporal trajectory data from smart-phones, which are powerful tools for uncovering the spatiotemporal model of infrastructure.