Spatial Data Types.

TL;DR: Spatial data types or geometric data types provide a fundamental abstraction for modeling the geometric structure of objects in space as well as their relationships, properties, and operations.

Abstract: DEFINITION Data types are a well known concept in computer science (for example, in programming languages or in database systems). A data type defines a set of homogeneous values and the allowable operations on those values. An example is a type integer representing the set of 32-bit integers and including operations such as addition, subtraction, and multiplication that can be performed on integers. Spatial data types or geometric data types provide a fundamental abstraction for modeling the geometric structure of objects in space as well as their relationships, properties, and operations. They are of particular interest in spatial databases [5, 8, 13] and Geographical Information Systems [14]. One speaks of spatial objects as values of spatial data types. Examples are two-dimensional data types for points (for example, representing the locations of lighthouses in the U.S.), lines (for example, describing the ramifications of the Nile Delta), regions (for example, depicting air-polluted zones), spatial networks (for example, representing the routes of the Metro in New York), and spatial partitions (for example, describing the 50 states of the U.S. and their exclusively given topological relationships of adjacency or disjointedness) as well as three-dimensional data types for surfaces (for example, modeling the shape of landscapes) or volumes (for example, representing urban areas). Operations on spatial data types include spatial operations like the geometric intersection, union, and difference of spatial objects, numerical operations like the length of a line or the area of a region, topological relationships checking the relative position of spatial objects to each other like overlap, meet, disjoint, or inside, and cardinal direction relationships like north or southeast.