Understanding the tourists’ spatio-temporal behavior using open gps trajectory data: A case study of yuanmingyuan park (Beijing, China)

Abstract

The visit paths, dwell time, and taking pictures are all variables of great significance to our understanding of tourists’ spatio-temporal behavior. Does having a large number of visitors mean that tourists are interested in a tourist location? What is the relationship between the dwell time and taking pictures? Are there differences in tourist behavior in different seasons? These issues are of great significance to tourism research but they have not been rigorously analyzed yet. This paper aims to understand the relationship between tourists’ visit path, dwell time, and taking pictures, and test whether there are differences in tourist behavior in different seasons. We used open global positioning systems (GPS) trajectory data at Yuanmingyuan Park from January 2014 to August 2020. Using Python and ArcGIS tools, we found hot spots of tourist passing, hot spots of tourist gathering, high average dwell time areas, and tourist interest areas. It is further found that: (1) passenger flow strongly explains dwell time, while the correlation between passenger flow and average dwell time is weak. (2) There was a close relationship between tourists’ stay and photo-taking behavior, which provided a theoretical basis for defining tourist photo behavior as tourists’ stay behavior. (3) Seasons did not significantly affect tourist behavior in Yuanmingyuan Park. This study presents a grid-based open GPS trajectory data processing framework that clarified the potential of an open GPS trajectory in tourist behavior research. Furthermore, our study explored the relationship between essential indicators and found that there is a strong consistency in tourist behavior across seasons.