Spatio-temporal big data analysis of tourists: A Case Study of Hangzhou

With the transformation of urban functions and the development of tourism, the research on the temporal and spatial behavior characteristics of tourist flow and destination preference within cities has gradually attracted the attention of domestic and foreign scholars. Based on the digital footprint data, with the help of social network analysis and mathematical statistical analysis, the time and space distribution and network structure characteristics of the tourist flow of external tourists in Hangzhou are studied. The results show that: Hangzhou's tourist flows have strong seasonal time characteristics; it presents a "dual core" and gradually decreasing spatial distribution characteristics, as well as the spatial preference characteristics dominated by natural scenery and historical sites; the overall density of the tourist flow network is relatively loose.