Human-Computer Interaction in Geovisualization

Geovisualization and cartography are in a defining moment, as the technological and social change now makes maps and geospatial data visible – progressively costless – and useful for the most wicked problems as well as the most everyday human routines [1]. For many phenomena and problem contexts, it is nowadays possible to create maps that are updated in real-time. Volunteered geographic data compliment the supply of official geospatial data (e.g. OpenStreetMap). At the same time the border between map users and map markers is disappearing. More maps are made by people without any cartographic training than by trained cartographers. Additionally, the dynamism in the development of novel devices (e.g. smartphones, tablets, and wearables, multi-touch tabletops, VR-/AR glasses) and corresponding interaction technologies requires a deepened engagement with HCI issues in the context of geographical applications. The provision of appropriate user interfaces for casual usage scenarios as well professional visual analytics tools for exploiting the potential of contemporary geospatial (big) data sets is essential if they are to be used efficiently and effectively. In order to reach the overall goal of usable and pleasant maps and geovisualizations, it is necessary to foster exchange and collaboration between the disciplines in both geosciences and computer sciences as well as design and related humanities. The four articles we present in this special issue provide a paradigmatic view for future research at the intersection of geovisualization and human-computer interaction in light of crosscutting themes we describe above.

This issue begins with Tutzauer et al. addressing virtual 3D cities as important tools for the visual communication of diverse urban-related information. The article Perceptual rules for building enhancements in 3D virtual worlds presents an approach to adapt 3D building models in a way, that they become visually more comprehensible for humans. Tutzauer et al. develop a virtual reality framework that allows users to switch between different building representation types while moving in the VR world, thus enabling them to evaluate the potential and effect of a grammar-enhanced building model in an immersive environment.

Put simply, VR refers to any technology that completely replaces what your eyes can see with something else. When you see something in AR, you see something virtual positioned in the real world. Augmented reality as a medium for geovisualization promises to merge the interactive nature of computer generated user interfaces with real objects and environments that create the every-day experience of users. In the second article of this issue Fuhrman and Pettitt probes how an augmented reality (AR) application for mobile devices could aid in re-erecting history and thus provide accessible, user-friendly apps for educating about heritage sites. The article Re-erecting the Robinson House at the Manassas Battlefield National Park with augmented reality shows that AR is a powerful tool that can be harnessed to educate on heritage sites.

The third article Visualization and interaction with multiple devices. A case study on reachability of remote areas for emergency management by Tost and Heidmann explores the challenges of multiple devices for geovisualizations in disaster management scenarios. They present an approach for exploring and validating reachability of remote areas through novel visualization patterns on interactive tabletop and tablets. This set of visualization and interaction techniques facilitates the formation of risk scenarios for better planning, preparedness, and response activities.

The contribution by Meier and Glinka introduces the concept of personal relevance as one key factor to be taken into account when designing casual spatial data visualisations, which are meant for the communication with non-experts. The article The individual in the data – The aspect of personal relevance in designing casual data visualisations probes how the conceptual model of personal relevance can be combined and applied to an actual dataset regarding air pollution data from the city of London.