Modern localization techniques are based on the Global Positioning System (GPS). In general, the accuracy of the measurement depends on various uncertain parameters. In addition, despite its relevance, a number of localization approaches fail to consider the modeling of uncertainty in geographic information system (GIS) applications. This paper describes a new verified method for uncertain (GPS) localization for use in GPS and GIS application scenarios based on Dempster-Shafer theory (DST), with two-dimensional and interval-valued basic probability assignments. The main benefit our approach offers for GIS applications is a workflow concept using DST-based models that are embedded into an ontology-based semantic querying mechanism accompanied by 3D visualization techniques. This workflow provides interactive means of querying uncertain GIS models semantically and provides visual feedback.