The elicited contour semantics comprises four key concepts â€“ contour regions, contour lines, contour values, and contour sets â€“ and their subclasses and associated relations, which are grounded in an existing qualitative spatial ontology.

This paper analyses and formalizes contour semantics in a first-order logic ontology that forms the basis for enabling computational common sense reasoning about contour information. What is in a contour map? A region-based logical formalization of contour semantics This new approach can be used for spatial data mining and knowledge discovering, such as the automatic extraction of terrain features and construction of multi-resolution digital elevation model. It has advantages over existing methods such as the point-in-polygon method and the region growing-based method. The immediate interior adjacency set is employed to identify all of the children contours of each contour without contour elevations. A new approach for generating contour trees by introducing a Voronoi-based interior adjacency set concept is proposed in this paper. The new system reduces the time required for mapping and staking, and can monitor the amount of soil moved.Ī Voronoi interior adjacency-based approach for generating a contour treeĪ contour tree is a good graphical tool for representing the spatial relations of contour lines and has found many applications in map generalization, map annotation, terrain analysis, etc. Igel and Company and the Ohio State University Center for Mapping advanced the technology for use in determining the contours of a construction site. While driving, the users can map an area from the sophisticated mapping van equipped with satellite signal receivers, video cameras and computer systems for collecting and storing mapping data. In the early 1990s, the Ohio State University Center for Mapping, a NASA Center for the Commercial Development of Space (CCDS), developed a system for mobile mapping called the GPSVan.

Contour map generator calculus