Exploiting Illusory Grid Lines for Object-Location Memory Performance in Urban Topographic Maps

Abstract

In order to be successful in spatial orientation tasks, people need to recall locations and configurations of spatial objects from their memory. This understanding of geographic space often arises from experience with cartographic media representing topographic and topological information by graphic symbols. Learning spatial information from graphic media is influenced by different perception-based grouping effects distorting the accuracy of spatial object-positions and their relations. Such geometric inaccuracies can be softened by adding a grid layer, which regionalizes the map and can be used as an additional orientation pattern. This grid layer usually consists of solid lines and overlays semantic information. The present paper reports the results of two empirical studies on object-location memory (OLM) performance. In these studies, the amount of visual detail of the grid layer was reduced. By positioning the grid layer below specific urban topographic objects (study 1), the grid pattern was graphically interrupted. These interrupted grid lines were completed by cognitive completion mechanisms (illusory grid lines) described in the Gestalt principles of closure and continuation. The second experiment examined the maximum grid line gap that is closed by cognitive line completion and keeps an advantage for OLM (study 2).

Keywords:

• cartography
• cognitive cartography
• empirical cartography
• spatial cognition
• spatial memory
• object-location memory
• Gestalt principle of closure
• Gestalt principle of continuation
• grid lines
• cognitive line completion
• grids
• recall
• topographic maps

Acknowledgements

This study was funded by the German Research Foundation (DFG, DI 771/7–1) to F.D. and L.K. The authors are deeply grateful to the district government of Cologne (‘Bezirksregierung Köln’), for providing the ATKIS^® data sets used in this study, and for their kind permission to publish the map excerpts contained in the Figures 2, 4, 5, 7 and 8.

Additional information

Notes on contributors

Frank Dickmann

Frank Dickmann is Professor of Cartography and Geo-Information Science at the Ruhr-University Bochum (Germany), where he is in charge of the Masters in Geography. He joined Ruhr University in 2007 after spending a number of years as a research assistant at the Universities of Göttingen, Cologne and Dresden. His major research interests are the application of modern visualization techniques to thematic mapping, cognitive cartography and the exploration of map efficiency using integrated media.