Spatial Task Performance in Virtual Geographic Environments

It is well documented that within Virtual Environments performance in cognitive tasks is diminished, and with the continued use of such environments to train people in various skillsets it is important that this problem be addressed. In this thesis, two areas of spatial cognition are addressed: navigation and distance estimation. Unlike many previous studies, the experiments conducted here are in a large-scale virtual rural environment which poses problems due to the large distances involved and the unrestricted movement of people through it. A virtual representation of the Sorbas region in Spain was produced using Blueberry3D, VegaPrime and ArcMap. Attempts to improve performance were made by the display of information to the user: an overview map to aid in distance estimations; and geo-located ‘factoids’, or info-marks, to aid in navigation. Analysis was also performed to extract rural environment features that could fall into the classifications of the Urban Image Theory, and a novel visio-analytic approach conducted to analyse track log data collected from the navigation task. Results indicate that neither of the two tools implemented had much effect on user performance. However, a key finding was that the use of both quantitative and qualitative analysis is important in such research, as although quantitative analysis indicated only some significant results, the qualitative analysis highlighted that when the tools were presented users felt far more confident in their results. The visio-analytical approach adopted proved to be extremely useful in identifying performance characteristics that would have been missed by using quantitative analysis alone.