NARA: Anchor-Conditioned Relation-Aware Contextualization of Heterogeneous Geoentities

ArXi:2605.12276v1 Announce Type: new Geospatial foundation models have primarily focused on raster data such as satellite imagery, where self-supervised learning has been widely studied. Vector geospatial data instead represent the world as discrete geoentities with explicit geometry, semantics, and structured spatial relations, including metric proximity and topological relationships.