Analysis of High-Quality Tourism Destinations Based on Spatiotemporal Big Data—A Case Study of Urumqi

Abstract

Although high-quality tourism destinations directly determine the tourism experiences of tourists and the management focuses of tourism management departments, existing studies have paid little attention to the relationship between tourism destinations of differing quality and tourist experiences. This study analyzed the spatiotemporal distribution of tourists and the quality of tourism destinations in Urumqi based on Tencent migration big data and Weibo sign-in big data and ultimately determined whether there are spatial correlations between the two. The results show that there are large differences in quality between different tourist destinations, and although the spatial and temporal distribution of tourists is not strongly correlated with the quality of tourist destinations, we can divide tourist destinations into four categories based on the correlations between the two (e.g., high-quality tourist destinations with a low number of tourists). The results of this study provide tourists with examples of high-quality tourist destinations, thus improving their holiday experiences, and they also provide a basis by which tourism management departments can manage and develop tourist destinations. The results of this study can also be extended to other regions and play a positive role in promoting the development of the tourism industry.