A Classification of Augmented Reality Approaches for Spatial Data Visualization

The field of Augmented Reality (AR) has seen a rapid expansion within the past decades, with many sectors nowadays applying AR methodologies for their own particular visualization needs. One field in particular that has adopted AR visualization techniques is the geospatial sciences, as they have identified the inherent spatial nature of AR as particularly applicable for visualizing (geo)spatial relationships in systems of interest. However, while we can find multiple classification schemes for AR applications in AR literature, to our knowledge no such classification exists that focuses specifically on the spatial aspects of AR applications, namely the visualization size, scale, and acknowledgement of and alignment with the user’s physical environment. Therefore no AR classification exists that is specifically applicable to the geospatial sciences. In this paper we present an initial classification of AR approaches for spatial data visualization, highlighting the different spatial characteristics that are of particular relevance to the geospatial sciences. We expect that the initial classification presented here will help researchers working with AR visualizations in organizing their application design with regard to its spatial characteristics.