A Geographic Knowledge Graph Approach to Identifying Cultural Diffusion Patterns: Integrating Cultural Similarity and Spatial Proximity

ABSTRACT The spatial diffusion of culture describes how cultural elements spread and evolve across regions over time, shaped not only by spatial proximity but also by shared meanings and symbolic connections. Existing geographic studies, however, have largely emphasized spatial patterns while overlooking the role of cultural similarity in this diffusion. To address this gap, this study proposed a geographic knowledge graph (GeoKG) approach for identifying cultural diffusion patterns by integrating semantic similarity and geographic proximity. Based on the field model, we first constructed a large language model (LLM)‐enhanced GeoKG of cultural elements, from which cultural similarity that encodes various cultural entities (e.g., historical figures and events, architectural components and styles) and their relationships was quantified. This similarity served as a weight in generating a cultural density surface, enabling the identification of cultural hearths, regions, and diffusion trajectories using spatial analyses and costdistance calculation. Applying this framework to Buddhist architectural culture in Shanxi Province, the results revealed that Mount Wutai functions as the cultural hearth and the Taiyuan–Linfen corridor forms a first‐level cultural region. A bidirectional expansion pattern was also identified, characterized by northward diffusion toward Datong and southward diffusion along the Mount Wutai–Taiyuan–Linfen–Yuncheng corridor. These patterns may reflect the interaction between political centrality and socioeconomic connectivity in shaping cultural diffusion. This study developed a GeoKG‐based framework for modeling cultural diffusion, integrating semantic similarity and spatial proximity to offer a generalizable approach for analyzing geographically anchored cultural elements.