Title :
A medium complexity discrete model for uncertain spatial data
Author :
Tossebro, Erlend ; Nygård, Mads
Abstract :
This paper presents a method for representing uncertainty in spatial data in a database. The model presented requires moderate amounts of storage space. To compute the probability that an object is at a particular place, the representation employs probability functions that can be computed quickly and efficiently. This is different from an advanced model presented by the same authors. This medium complexity model is less powerful, but requires much less storage space, and computing probabilities is much less complicated.
Keywords :
computational complexity; database theory; probability; spatial data structures; uncertainty handling; visual databases; computational complexity; data model; data representation; medium complexity discrete model; probability function; spatial database; spatial object position measurement; spatial object shape measurement; spatiotemporal database; storage space; uncertain spatial data; Cities and towns; Reservoirs; Rivers; Roads; Shape measurement; Space technology; Spatial databases; Spatiotemporal phenomena; Uncertainty; Water resources;
Conference_Titel :
Database Engineering and Applications Symposium, 2003. Proceedings. Seventh International
Print_ISBN :
0-7695-1981-4
DOI :
10.1109/IDEAS.2003.1214959