Abstract
Representing, storing, quering, and manipulating spatial information is important for many non-standard database applications. Specialized systems like geographical information systems (GIS) and spatial database systems to a certain extent provide the needed technology to support these applications. So far, spatial data modeling has implicitly assumed that the extent and hence the borders of spatial phenomena are precisely determined, homogeneous, and universally recognized. From this perspective, spatial phenomena are typically represented by sharply described points (with exactly known coordinates), lines (linking a series of exactly known points), and regions (bounded by exactly defined lines which are called boundaries). Special data types called spatial data types (see [23] for a survey) have been designed for modeling these spatial data. We speak of spatial objects as instances of these data types. The properties of the space at the points, along the lines, or within the regions are given by attributes whose values are assumed to be constant over the total extent of the objects. Well known examples are especially manmade spatial objects representing engineered artifacts like highways, houses, or bridges and some predominantly immaterial spatial objects exerting social control like countries, districts, and land parcels with their political, administrative, and cadastral boundaries. We will denote this kind of entities as crisp or determinate spatial objects.
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Schneider, M. (2004). Fuzzy Spatial Data Types and Predicates: Their Definition and Integration into Query Languages. In: de Caluwe, R., de Tré, G., Bordogna, G. (eds) Spatio-Temporal Databases. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-09968-1_12
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DOI: https://doi.org/10.1007/978-3-662-09968-1_12
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