Spatial heterogeneity and driving mechanisms of tourism resources vary across county types in Central China

This paper selects Xinxian County (mountainous revolutionary heritage area), Linzhou City (mountainous complex landscape), and Huaxian County (plain-linear heritage) in Henan Province as representative cases exhibiting pronounced geomorphic and cultural contrasts. The study systematically applies four spatial analytical methods: the Voronoi polygon coefficient of variation, kernel density estimation, standard deviation ellipse, and the Geodetector model. Through this integrated methodological framework, the study reveals the distinct spatial differentiation patterns of tourism resources across the three counties and uncovers their underlying, context-specific driving mechanisms. The findings demonstrate that: (1) While tourism resources in all three counties are spatially concentrated, their configurations diverge markedly: Xinxian County manifests a balanced “multi-core network” structure; Linzhou City is characterized by a terrain-constrained “mountain strip” pattern; and Huaxian County follows a “canal-radiation” corridor structure shaped by historical waterway infrastructure. (2) The dominant spatial drivers differ, representing distinct evolutionary pathways: Xinxian’s development is strongly associated with capital and transportation support; the distribution pattern of Linzhou is closely related to its rugged terrain and ecology; and Huaxian’s distribution is highly correlated with historical heritage inertia coupled with high-density population adherence. (3) Factor interactions exhibit significant synergistic enhancement. By introducing a multidimensional analytical framework comprising a “foundational natural basis,” a “socioeconomic supporting guarantee,” and an “animating socio-cultural core,” this study offers a contribution to the literature beyond single-factor determinism. It suggests that county-level tourism spatial configurations are the outcome of non-linear spatial coupling among geographic constraints, economic investments, and historical legacies. The findings provide empirically grounded, place-sensitive insights that may inform spatial governance to support the differentiated, high-quality development of county-level human-environmental systems.