Topographic analysis supported by a knowledge graph: A case of ridge landscape recognition

Abstract

The intrinsic connections between geographical elements are important for uncovering hidden geo-scientific laws. However, current research on terrain and landform analysis mainly focuses on the landscapes themselves, with insufficient attention to the connections between them. Therefore, this study proposes a knowledge graph approach based on geographical units (TUKG). Specifically, fi-negrained geographical units are extracted based on three types of data: remote sensing images, DEM, and contour lines. These units serve as entity nodes in the TUKG and are described by their slope and aspect. Additionally, point-based and line-based connections between geographical units are proposed based on spatial topological relationships, serving as connections between entity nodes in the TUKG. Finally, inference rules for ridge landscape problems are extracted from typical cases of ridge land-scapes to support reasoning in the TUKG. Experimental results conducted in the Yarlung Zangbo Grand Canyon in southwest China demonstrate that the TUKG can accurately infer ridge landscapes and has the potential to identify more complex terrain landscapes.