European initiatives for data harmonization and the establishment of remote-sensing-based services aim at the production of up-to-date land-cover information according to generally valid standards for the accurate qualification of thematic classification results. This is particularly true since new satellite systems provide data of high temporal and geometric resolution. While methods for point-related thematic accuracy assessment have already been established for years, there is a need for a commonly accepted framework for the geometric quality of tematic maps. In this study, an open and extendable framework for the geometric accuracy assessment is presented. The workflow begins with the definition of basic geometric accuracy metrics, which are based on differences in area and position between samples of classified and reference objects. The combination of user-defined metrics enables both a geometric assessment of single objects as well as the total data set. In an example of thematically classified agricultural fields in a German test site, we finally show how object relations between classified and reference objects can be identified and how they affect the global accuracy assessment of the total data set.