Editing Geometric primitive (section)

== Application in GIS ==

A wide variety of vector data structures and formats have been developed during the history of [[Geographic information systems]], but they share a fundamental basis of storing a core set of geometric primitives to represent the location and extent of geographic phenomena. Locations of points are almost always measured within a standard Earth-based coordinate system, whether the spherical [[Geographic coordinate system]] (latitude/longitude), or a planar coordinate system, such as the [[Universal Transverse Mercator]]. They also share the need to store a set of attributes of each geographic feature alongside its shape; traditionally, this has been accomplished using the data models, data formats, and even software of [[relational database]]s.

Early vector formats, such as [[Harvard Laboratory for Computer Graphics and Spatial Analysis|POLYVRT]], the ARC/INFO Coverage, and the [[Shapefile|Esri shapefile]] support a basic set of geometric primitives: points, polylines, and polygons, only in two dimensional space and the latter two with only straight line interpolation. TIN data structures for representing terrain surfaces as triangle meshes were also added. Since the mid 1990s, new formats have been developed that extend the range of available primitives, generally standardized by the [[Open Geospatial Consortium]]'s [[Simple Features]] specification.<ref name="ogc-sf">Open Geospatial Consortium, [https://www.ogc.org/standards/sfa OpenGIS Implementation Specification for Geographic information - Simple feature access], Version 1.2.1</ref> Common geometric primitive extensions include: three-dimensional coordinates for points, lines, and polygons; a fourth "dimension" to represent a measured attribute or time; curved segments in lines and polygons; text annotation as a form of geometry; and polygon meshes for three-dimensional objects.

Frequently, a representation of the shape of a real-world phenomenon may have a different (usually lower) dimension than the phenomenon being represented. For example, a city (a two-dimensional region) may be represented as a point, or a road (a three-dimensional volume of material) may be represented as a line. This dimensional generalization correlates with tendencies in spatial cognition. For example, asking the distance between two cities presumes a conceptual model of the cities as points, while giving directions involving travel "up," "down," or "along" a road imply a one-dimensional conceptual model. This is frequently done for purposes of data efficiency, visual simplicity, or cognitive efficiency, and is acceptable if the distinction between the representation and the represented is understood, but can cause confusion if information users assume that the digital shape is a perfect representation of reality (i.e., believing that roads really are lines).