Representing the Spatiotemporal State Evolution of Geographic Entities as a Multi-Level Graph

The geographic knowledge graph offers a structured framework for mining and discovering spatiotemporal knowledge, which is of great significance for understanding geographic dynamics. However, existing geographic knowledge graphs still encounter significant challenges in comprehensive expression of spatiotemporal elements and understanding the intricate relationships and dynamic evolution among geographic entities, space, and time. Therefore, a Spatiotemporal Evolution Hierarchical Representation Graph (STEHRG) is proposed, which consists of three layers: a spatiotemporal ontology layer, a spatiotemporal evolution layer, and a feature situation layer. The STEHRG characterizes the multidimensional state transitions of spatiotemporal entities across various scales and abstraction levels, enabling a comprehensive representation of geographic spatiotemporal evolution. Additionally, this paper introduces a graph data structure-based approach for managing the state features of spatiotemporal entities and their lifecycle dependencies. Finally, through comparative experiments with existing knowledge graphs (GeoKG, GEKG, and STOKG), the results indicate that the STEHRG has significant advantages in accuracy, completeness, and reproducibility.