Spatial differentiation and integrated tourism development of China's traditional heritage villages

Traditional villages in China serve as important carriers of rural cultural heritage but are increasingly threatened by rapid urbanisation and uneven regional development. Understanding their spatial distribution and integration within cultural-tourism networks is essential for developing effective conservation and regional planning strategies.

Using a national dataset of 8,157 officially designated traditional villages, combined with city-level tourism indicators and three categories of cultural heritage carriers (A-level scenic spots, intangible cultural heritage, and protected cultural relics), this study developed an integrated analytical framework based on spatial statistical analysis, spatial correlation analysis, and K-means clustering to evaluate spatial differentiation and cultural-tourism integration patterns.

The results reveal a pronounced "south-dense, north-sparse" spatial distribution with persistent regional inequality. Traditional villages exhibit weak correlations with overall tourism performance but strong spatial coupling with A-level scenic spots, moderate associations with protected cultural relics, and limited integration with intangible cultural heritage, indicating a selective and uneven embedding structure. Based on these relationships, Chinese cities can be classified into four development types: comprehensive leading areas, scenic-village integration areas, balanced development areas, and potential development areas, each characterised by distinct cultural-tourism integration pathways.

The findings demonstrate that traditional villages function as selectively embedded nodes within China's cultural-tourism network rather than uniformly integrated tourism resources. This typology provides a practical basis for differentiated conservation policies, cultural heritage management, and place-based tourism planning while offering new insights into the spatial organisation of cultural heritage systems at the national scale.