Abstract
The treatment of uncertainty in spatial data is a problem that has been studied from a theoretical point of view (notably, [1]). The various models have never been developed in enough depth to become operational and, till now, the management of uncertainty in current spatial database systems is not supported. The main problem about spatial objects that are stored in spatial databases is that it is impossible to reason about the degree of indetermination of a result, since the data have lost the information about all the uncertainty that added up after having undertaken several transformations. An adequate modeling of geometric uncertainty in spatial data is essential for the assessment of data quality, and, consequently, for helping any process related to dataset acquisition and integration [12, 13, 17].
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