relations are the basis for many selections users perform when they query geographic information systems (GISs). Although such query languages use natural-language-like terms, the formal definitions of those spatial relations rarely reflect the same meaning people would apply when they communicate among each other. To bridge the gap between computational models for spatial relations and people's use of spatial terms in their natural languages, a model for the geometry of spatial relations was calibrated for a set of 59 English-language spatial predicates. The model distinguishes topological and metric properties. The calibration from sketches that were drawn by 34 human subjects identifies ten groups of spatial terms with similar properties and provides a mapping from spatial terms onto significant geometric parameters and their values. The calibration's results reemphasize the importance of topological over metric properties in the selection of English-language spatial terms. The model provides a basis for high-level spatial query languages that exploit natural-language terms and serves as a model for processing such queries.
Stored only when both papers are in the corpus — 160 citations exist upstream.