Spatial Distribution and Influencing Factors of High-Level Tourist Attractions in China: A Case Study of 9296 A-Level Tourist Attractions

Abstract

The distribution pattern of high-level tourist attractions is crucial for the sustainable development of the tourism industry. However, few studies have explored the spatial distribution and dominant influencing factors of tourist attractions of different levels from a macro perspective in China. This study, which was based on large-scale multi-source data, involved the use of kernel density analysis, local spatial autocorrelation, and geographical detector analysis to explore the spatial distribution, spatial correlation, and dominant influencing factors of high-level tourist attractions in China. The study’s results show that the spatial distribution of tourist attractions of different levels is polarized and regionally clustered, and there exist some spatial correlation effects among attractions of the same level. Additionally, different influencing factors play a different role in determining the spatial distribution of attractions of different levels. Based on market demand and tourism resources, it is necessary to regulate attractions of different levels to promote the sustainable development of high-level tourist attractions and provide a reference for the development of China’s tourism industry.