Geovisualization

Geovisualization, sometimes called cartographic visualization, is a set of tools and techniques for analyzing geographic data with interactive visuals. Unlike traditional static maps, which offer limited room for exploration because their graphics are locked to the underlying geography, geovisualization lets users work with dynamic, computer-based maps. These maps allow people to switch between layers, zoom in and out, and change how the map looks in real time, thanks to modern microprocessors that can instantly update the display. The goal is to build knowledge rather than just store or transmit information, combining geospatial data with human insight to support exploration and decision-making.

The term "visualization" first appeared in cartography in 1953, in a paper by geographer Allen K. Philbrick. A 1987 National Science Foundation report later redefined it, placing visualization at the intersection of computer graphics, image processing, computer vision, computer-aided design, signal processing, and user interface studies, and highlighting its role in creating knowledge and generating hypotheses. Geovisualization itself emerged as a research field in the early 1980s, largely inspired by French graphic theorist Jacques Bertin. His work on cartographic design and information visualization, like the NSF report, focused on using dynamic visual displays to spark scientific insight and on methods that leverage perception and cognition to aid scientific thinking. The International Cartographic Association formed a Commission on Visualization & Virtual Environments in 1995, and the field has continued to grow in both practice and research.

Geovisualization is closely tied to scientific visualization and information visualization. Because of its roots in cartography, it contributes to these fields through the map metaphor, which has been widely used to visualize non-geographic data in information visualization and domain knowledge visualization. It also relates to urban simulation.

Geovisualization has been applied in various real-world settings that require decision-making and knowledge creation. In wildland firefighting, firefighters have long used sandbox environments to physically model terrain and fire for incident command planning. The SimTable, a 3D interactive fire simulator, brings these sandtable exercises to life by using advanced computer simulations to model fires in any area—including local neighborhoods—based on actual slope, terrain, wind speed and direction, vegetation, and other factors. SimTable models were used during Arizona’s largest recorded fire, the Wallow Fire.

In forestry, geovisualizers worked with European foresters to use CommonGIS and the Visualization Toolkit (VTK) to visualize large sets of spatio-temporal data about European forests, making the data explorable by non-experts over the Internet. The project’s report highlighted fundamental issues for both geovisualization and information visualization research. Two major problems emerged: the geovisualizers could not convince the foresters that geovisualization was useful for their work, and the foresters were uneasy about non-experts having uncontrolled access to the dataset. While the geovisualizers emphasized knowledge construction, the foresters preferred the information-communication role of traditional cartographic maps.

In archaeology, geovisualization offers a way to map unearthed environments and to access and explore archaeological data in three dimensions. Its implications go beyond theory and exploration, fostering new collaborations between archaeologists and computer scientists.

For environmental studies, geovisualization tools help multiple stakeholders make balanced decisions by accounting for the complex, interacting factors involved in environmental change. Users can work with georeferenced models to explore complicated datasets and test different scenarios or policy options to find the best fit.

In urban planning, both professionals and the public can use geovisualization to explore real-world environments and model "what if" scenarios based on spatio-temporal data. This field can be split into two domains: a private one where professionals explore data and generate hypotheses, and a public one where the broader community engages with the information.