The widespread use of location-aware technologies increases the importance of spatial data not only in decision processes of public and private institution but also in everyday life. Dealing with spatial data in distributed architectures requires to face with a complex environment where, it is quite common to find multiple representations of the same or overlapping spatial datasets. From a system point of view, this may lead to query processing and integration problems, since the same concepts can be represented in different ways and at different resolutions. From a user point of view, this may result in a gap between the available data and the user’s knowledge of such data during query specification, reducing user satisfaction in using a given application. To address this problem, this project investigates how multiresolution can be effectively exploited during query processing of vector spatial datasets. To this aim, issues related to the modelling of multi resolution datasets, the comparison of different multiresolution datasets based on qualitative information, and the semantic definition of relaxed spatial operators are addressed.