Updating maps is a process where the main goal is to bring the content of spatial databases in their electronic and hardcopy versions up to the most current state. The three main tasks undertaken in updating maps are change detection, image interpretation, and metadata and geographic correction (i.e., georeferencing). However, an analysis of map update technology shows that the most time consuming and difficult in the process of detecting changes is the map itself. When raw aerial or orthophoto imagery is deployed the main method is photointerpretation that uses photogrammetric instruments and tools, as well as a variety of thematic maps and data from geodetic measurements. In the last decade, a number of studies have developed methods for automatic and semi-automatic identification of terrain changes. This paper describes a research effort in establishing a novel approach for geospatial data actualization. We performed a series of experiments where multiple geospatial data sets were superimposed in real-time in a dynamic window driven by the analyst's attention as detected by an eyetracking system. Specifically, edge detection and edge matching tasks were performed. Area-based or feature-based image matching (I2i) can be performed within specific windows (i.e., areas of interest) rather than globally. This paper describes the experiments in more detail and contains an initial comparison of this method's accuracy and productivity to other state-of-the-art updating techniques.