Imprecision and Spatial Uncertainty

Abstract

Spatial uncertainty is defined as the difference between the contentsof a spatial database and the corresponding phenomena in the realworld. Because all contents of spatial databases are representationsof the real world, it is inevitable that differences will exist betweenthem and the real phenomena that they purport to represent. Spatialdatabases are compiled by processes that include approximation, measurementerror, and generalization through the omission of detail. Many spatialdatabases are based on definitions of terms, classes, and valuesthat are vague, such that two observers may interpret them in differentways. All of these effects fall under the general term of spatialuncertainty, since they leave the user of a spatial database uncertainabout what will be found in the real world. Numerous other termsare partially synonymous with spatial uncertainty. Data quality isoften used in the context of metadata, and describes the measuresand assessments that are intended by data producers to characterizeknown uncertainties. Vagueness, imprecision, and inaccuracy all implyspecific conceptual frameworks, ranging from fuzzy and rough setsto traditional theories of scientific measurement error, and whetheror not it is implied that some true value exists in the real worldthat can be compared to the value stored in the database.