The construction of tourism characteristics towns is conducive to comprehensively playing the industrial radiation function of tourism and promoting the coordinated development of urban and rural areas. This study takes 216 tourism characteristic towns among the national characteristic towns as the research object, uses the GIS spatial analysis method to deeply analyze the spatial distribution type, spatial distribution direction, and spatial pattern of different types of tourism characteristic towns, and uses geographical detectors to reveal the influencing factors that promote the formation of this spatial pattern. The research shows that: ① Tourism characteristic towns generally show a spatial agglomeration distribution, in which the resource support and characteristic industries are evenly distributed, and the other four types are clustered; ② The spatial distribution direction is “southwest-northeast”, among which the types of resource support, folk customs, health resort and vacation are similar to the general trend; ③ The spatial pattern is dominated by one high-density agglomeration area and three sub-aggregates, with large differences; ④ Tourism resources, traffic conditions and government support play an important role in the spatial distribution of tourism characteristic towns. The influence of various influencing factors on the spatial distribution of different types of tourism characteristic towns is significantly different, especially in the historical and cultural categories. The research results can provide strong support for the optimization of spatial structure and reasonable layout of regional tourism characteristic towns.

Exploring the coordination effect and interactive response between tourism development and urban-rural integration holds significant theoretical and practical value for establishing an integrated development pattern where urban and rural areas mutually promote each other’s prosperity and coexist harmoniously. The entropy method is used to measure the level of tourism development and urban-rural integration in 31 provinces in China from 2010 to 2022, the coupling model is used to explore the coordination effect of the two systems, and the kernel density estimation and exploratory spatial-temporal data analysis (ESTDA) are used to reveal the spatial-temporal dynamics of the level of the two systems’ coupling and coordination. On this basis, the panel vector autoregression (PVAR) model is used to analyze the interactive response relationship between the two systems. The study found that: ① the coupling and coordination level of tourism development and urban-rural integration has improved over time, and there is no polarization phenomenon. The level of coupling and coordination between the two systems shows a spatial distribution pattern of "east > central > west", with strong non-equilibrium and spatial spillover effects. ② There is a significant positive spatial correlation between the coupling and coordination levels of the two systems, and the spatial agglomeration trend is gradually weakened over time; the local spatial structure and direction of dependence are relatively stable, presenting significant transfer inertia and path dependence characteristics. ③ Tourism development and urban-rural integration affect and link each other, showing a significant interactive response relationship.