[Objective] This paper visualizes the big data of festival visitors, aiming to analyze their movement patterns and influencing factors. [Methods] We used the GIS tools to analyze the tourist flow data of 80 scenic spots during Shanghai Tourism Festival, and constructed metrological model to examine the influencing factors. [Results] We found that initiation tourism resources, which broke the obstacles facing event tourists, included the motivation of tourists gathering and rapid flows. The number of tourists declined from the multiple event centers to surrounding areas. The time distribution of tourist flow did not follow the classic “inverted U-shape”, and then led to more agglomeration effects. Tourism resource endowment, traffic conditions, competitiveness of tourism products, and tourism reception could all promote tourists gathering, while facilities (i.e. capacity) was no longer the key element in attracting visitors. [Limitations] More research is needed to discuss the dynamic path of tourist flow. [Conclusions] GIS and big data technology can be used to present the visitors’ flow.
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Wang Ling,Dai Qianjin,Wu Xiaojun. The Study on the Temporal and Spatial Distribution of Event Tourism Based on Large-scale Tourism Early Warning Platform. Data Analysis and Knowledge Discovery, 2018, 2(8): 31-40.
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