Ian D.Bishop and Eckart Lange
The distinguishing features of visualization
As Jostein Gaarder (1996:127) wrote in the popular philosophical novel Sophie’s World:
We can even trace a particular word for ‘insight’ or
‘knowledge’ from one culture to another all over the Indo-European world. In Sanskrit it is vidya. The word is identical to the Greek word idea, which was so important in Plato’s philosophy. From Latin we have the word video, but on Roman ground this simply meant to see. For us, ‘I see’ can mean ‘I understand’.
This link between seeing and understanding was the basis for the adoption of the term
‘visualization’ by McCormick et al. (1987). This was a new use of the word. Earlier dictionary definitions were restricted to the process of forming a mental image of, or envisioning, something. The more recent usage involves the process of interpreting something in visual terms or, more particularly, putting into visible form. Tufte (1990), for example, provides a marvellous review of mechanisms to help people to envision information. In this chapter we are specifically concerned with the options for putting things (data, model outputs, landscapes) into visual form. The overriding purpose behind creation of these visual forms is to help people to envision. That is, to better understand the relationship between data or some condition of the environment.
More specifically, McCormick et al. (1987) defined visualization in this way:
Visualization is a method of computing. It transforms the symbolic into the geometric, enabling researchers to observe their simulations and computations. Visualization offers a method for seeing the unseen. It enriches the process of scientific discovery and fosters profound and unexpected insights. In many fields it is already revolutionizing the way scientists do science.
In the very same year (Zube et al. 1987) wrote:
For centuries it appears to have been assumed that a drawing—is a drawing—is a drawing, and that it probably means the same thing to all who view it. The evidence…suggests that the most realistic simulations, those that have the greatest similitude with the landscapes they represent, provide the most valid and reliable responses (p. 76).
Two different strands of meaning are now emerging. There is visualization of data, models and relationships, and there is visualization of landscape and changing environments. Within these broad categories there are divergent strands. A full understanding of visualization (in its modern meaning) requires close examination of the many options which continue to emerge with evolving technologies and applications.
An early attempt at identification of the major variables in visualization for cartographic purposes was proposed by MacEachren et al. (1994). Major axes of distinction were identified as:
• applications for presentation of known information versus the discovery of new knowledge;
• the level of interaction available with the data;
• the use in a private or public context.
Moving beyond the cartographic context, we recognize a number of other important distinctions that can be made within the realm of visualization. These include:
• abstract versus realistic presentation;
• dynamic versus static views;
• single versus multiple displays;
• immersive versus non-immersive display.
All of these differences in visualization options are reviewed in more detail below. With the addition of levels of abstraction, dynamism and immersion into the classification, examples within each division can all be of diverse character themselves. Almost all the examples could be made available in immersive or non-immersive environments.
Communicating versus discovering knowledge
Maps are a traditional mode of information communication. So are renderings of proposed buildings. Figure 2.1 shows examples of innovative visualization work aimed specifically at communication. Figure 2.1(a) shows the route taken by Lewis and Clark as they opened up what later became the Oregon Trail. The USGS mapmakers have taken great care in communication of known information in an easy-to-read format. The combination of the mapped path of discovery with the elevation-based shading also gives a clear idea of how the path was shaped by the geomorphology of the region. Architects have been rendering images of their designs for several years to show the public how the proposal will look (Figure 2.1 (b)).
Discovery of knowledge is clearly the objective in the exploratory, pathfinding work at the USA EPA visualization group. Figure 2.2, for example, shows a combination of three-dimensional representation of the modelling environment with innovative display
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of the output of a wind velocity modelling program. In the original you can see the combination of colour (for velocity) and icons (for direction) in the wind cross-section.
2.1 Example of visualization for public communication: (a) the line shows the route of Lewis and Clark as they opened the American west; (b) elaborate architectural rendering
2.2 A prime example of scientific
visualization for the purposes of
discovery
2.3 Interactive and dynamic mapping of population of the 100 largest cities and other urban places in the US 1790–1990
Static and dynamic display: spatial or temporal
‘Dynamic representation’ refers to the displays that change continuously, either with or without user intervention (Slocum et al. 2001). One form of dynamic representation is an animated map, in which a display changes continuously without any direction from the user. The other form is direct manipulation, which permits users to explore spatial data by interacting with mapped displays (described under ‘Levels of interactivity’ below).
Many different kinds of changes may be represented by dynamic displays. In the field of cartographic visualization it is temporal phenomena which are most commonly displayed dynamically. This includes the spatial distribution of data on population, pollution, sea surface temperature, mortality rate and so on. While in the early days of development of dynamic visualization it was a novelty to produce an animation, today the user typically has considerable control over functions such as map zoom and pan, changes of colour, sound, projection, animation speed and step size (Figure 2.3).
In realistic visualization, the dynamics are more commonly spatial (i.e. changing view-point) and would normally be in the form of a flyover or walk-through. Again, this may be a pre-rendered animation or an interactive exploration. However, temporal change is also frequently included in the more realistic three-dimensional style of visualization. In the landscape this may involve the harvesting, burning and growth of trees (see Chapter 6, ‘Studying the acceptability of forest management practices using visual simulation of forest regrowth’, p. 112), the movement of animals through the landscape (Hehl-Lange 2001), or restoration of a mining environment (Hehl-Lange and Lange 1999).
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2.4 An example of a web browser accessing an interactive spatial data analyser CommonGIS: an abstract mapping system
Levels of interactivity
The ability to interact with a visualization is the key to its use for discovery, and may also be important in communication.
Some of the classic work by Gennady and Natalia Andrienko (e.g. Andrienko and Andrienko 1999) is illustrated in Figure 2.4. These maps of thematic data, available over the Internet, are highly interactive. The user can move sliders, change a number of display categories, zoom the map and so on. This is an example of visualization which supports both communication and discovery and is available to both the public and the professional.
The degree of interactivity in visualization depends in part on the nature of the controls provided by the user interface. However, another element of interactivity is the ability of the computer systems to redraw images quickly enough that the user sees an
‘instant’ response to their input. The issue of what constitutes real-time performance and how this is influenced by computer configurations is discussed further in Chapter 4.
Dimensionality
We recognize maps as two-dimensional graphics and rendered buildings as three-dimensional but there are more distinctions that can be made in terms of three-dimensionality.
Particularly in the landscape field, and when working with GIS, some representations are referred to as 2.5D (or two-and-a-half dimensions). This description comes primarily from the way terrain is modelled in many systems—as a single Z value for each X, Y pair
in the data set. While this can effectively model most terrain surfaces except caves and overhangs, it cannot be used for full three-dimensional modelling of buildings.
The dimensions of a three-dimensional visual representation do not have to match those of the real world at all. MacEachren et al. (2001) have created a distinction based on the extent to which the dimensions of the display environment match the dimensions of the real world. When there is concordance they define the visualization as spatially iconic. In other words, the situation is familiar to us, human perception and cognition are not strained, and real-world metaphors such as digging and flying are readily understood.
This is akin to the natural-scene paradigm defined by Robertson (1991). When one of the three dimensions, usually the vertical, is used for something other than the geographic dimension of height, the visualization may be described as spatially semi-iconic. Thus, X and Y may be normal spatial extent but Z is some other variable—population density, income, pollution level. The third option is that the axes of the display environment are quite unrelated to real world dimensions: e.g. various forms of statistical plot.
Levels of realism
Spatially abstract visualization requires a substantial degree of familiarity with both the subject matter and the display technique. Abstract display is therefore generally considered to fall within the expert and knowledge discovery domain. An exception is the familiar static two-dimensional map. However, times change and within the spatially iconic communications domain different levels of detail, realism and abstraction may also be appropriate to permit ready public consumption.
Part of the role of visualization for the public is to provide an opportunity for greater involvement in community decision making. Government, or consultant, reports are often designed for people with an existing knowledge of the issues or processes involved. To broaden the effective use of this information it needs to be in a format (or language) that can be widely consumed. Haughton (1999) has warned of the dangers of ‘technocratic capture of information by dint of its poor presentation for interpretation by ordinary citizens’ (p. 54). Environmental management now covers a very wide range of issues and the public are concerned with a great many of these. At the same time as technology has advanced the opportunity for visualization, public interest has increased the need.
Langendorf (2001) makes four assumptions about the role of visualization in planning:
1 in our complex world, to understand nearly any subject of consequence it is necessary to consider it from multiple viewpoints, using a variety of information;
2 we are rapidly moving from an information-poor to an information -rich society;
3 the understanding of complex information may be greatly extended if visualized; and 4 problem solving and commitment to action in a complex world requires communication
and collaboration among many participants, and visualization aids this interaction (p.
309).
The easiest form of visualization for the public to associate with and understand is realistic portrayal of visual landscape change. Bishop (1994), Lange (1994) and others have argued that realism is of great importance in effective and legitimate communication of change. Realistic presentation of alternative futures is clearly appropriate when immediate aesthetic issues are uppermost in people’s concerns but this form of
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presentation can also be effective for broader issues. Communication of flood risk, traffic volumes, forest succession (Figure 2.5), visual pollution levels and other factors influenced by environmental management can all be represented with high levels of realism. The approach to communication through realistic images of a real or proposed environment is often referred to as Environmental Visualization (encompassing visual simulation of both built and natural environmental features).
There are clearly environmental management impacts which either cannot be represented realistically (non-visual pollution, regions of influence) or are more easily interpreted by a more schematic form. Figure 2.6 is an example from a landscape planning project where realism was not attempted (see also Chapter 7, ‘Designing, visualizing and evaluating sustainable agricultural landscapes’, p. 136). The important point was that the geometry was based entirely on existing or proposed terrain and surface features derived from a GIS. Krause (2001) also used a semi-realistic approach but added further information using entirely abstract icons (Figure 2.7). Coupling realistic