Hierarchical Differentiation and Driving Factors of the Spatial Distribution of A-Level Tourist Attractions in China

Understanding the spatial hierarchy, distribution patterns, and driving mechanisms of A-level tourist attractions is essential for optimizing tourism resource allocation and promoting sustainable regional development. This study integrates core–periphery theory with a sustainability perspective to examine hierarchical differentiation of China’s A-level tourist attractions, using 15,699 POI data points collected in 2024 and applying the nearest neighbor index (NNI), kernel density estimation, spatial autocorrelation analysis, and the geographical detector model. The results indicate that these attractions exhibit an unbalanced spatial distribution characterized by a “dense east and sparse west” pattern, with the Hu Huanyong Line (Hu Line) as an important spatial boundary, showing east–west hierarchical disparities. The attractions demonstrate a clustered distribution pattern, although the degree of agglomeration decreases as attraction grades increase. Spatial associations exhibit a pattern of coordination in eastern regions and polarization in western regions, forming a three-tier spatial hierarchy of core–sub-core–periphery. Population density exhibits the strongest explanatory power. Interaction detector results reveal grade-dependent differences. 2A attractions show weak factor associations, whereas 5A attractions are more strongly linked to resource endowment, population density, and economic development. These findings advance the theoretical understanding of the hierarchical spatial structure and differentiated development mechanisms of tourist attractions.