The measuring (or query) of the relationship between spatial features is of particular utility within a GIS. A spatial join combines represented geographic objects and their associated attributes based on a spatial relationship test (or predicate). The method of spatial join operation utilized depends on the relationship between the features represented and how those features are represented in the GIS. Regardless of the software implementation, the spatial join operation results are predicated on a test condition such as adjacency, proximity, or topology comparison among represented geographic data. This topic discusses how spatial join operations can be utilized for different geographic problems.
Adjacency and Connectivity are two fundamental spatial relationships that are used both descriptively and analytically in a wide range of spatial analyses and geographic contexts. These topologically invariant relationships have been instrumental in the development of data models for geographic information systems, most notably in the development of the vector data model. Adjacency provides a means of defining a neighborhood for the computation of many raster-based functions such as smoothing and surface flow analysis. Connectivity and adjacency also provide a means for defining neighborhoods for use in spatial statistics, and for guiding movement across transportation networks. These concepts are intrinsic to many spatial analytic techniques given that they strongly reflect the notion of spatial nearness.
Spatial information retrieval is fundamental in modern applications that enhance data analysis by enabling the representation, storage, and management of spatial data. Spatial database systems and Geographical Information Systems are essential tools for those applications, offering efficient spatial data representation and spatial query processing. Spatial data is usually represented by geometries in Euclidean space, such as points, lines, and regions. Spatial query processing mainly relies on the task of retrieving spatial objects meeting specific spatial conditions. These conditions are often defined by spatial relationships, which describe how spatial objects relate within a given space and have different semantics, such as topological relationships (e.g., overlap, inside), metric relationships (e.g., distance), and direction relationships (e.g., cardinal directions). A typical spatial query finds all objects in a specified relationship with a search object. This article systematically explores the design and definition of spatial queries by using spatial relationships as their main foundation. By introducing both intuitive and formal definitions of various types of spatial queries, it helps users to understand each query’s practical use and underlying mechanics.