Task Two: Visualisation tools review

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Further information

Visualisation Tools

Introduction

Visualisation provides additional insights to results which would otherwise be displayed as text or numbers (Loh et al, 1992). It is a form of communication which is universal, and which has the ability to form an abstraction of the real world into a graphical representation which is comprehensible to a wide range of people. Increasingly, computer visualisation is used to communicate the implication of natural and management changes in biological systems in national parks and forests (Orland, 1995).

Necessity of visualisation

Since it would be difficult to obtain actual 'before' and 'after' construction photographs using complementary approach to investigate observer response to the impact of man-made structures on landscape quality, some technique of simulating such environments is clearly desirable. Killeen and Buhyoff (1983) stated that "from an experimental standpoint ... it would be desirable to be able to selectively manipulate a certain characteristic of a scene while holding all other constant".

Simulation tools

Literature reviews by Zube et al (1987) and Sheppard (1989) described a wide range of simulation techniques which are readily accessible to environmental designers to explore and communicate design ideas, and to present the potential effects of the project on its surrounding landscape.

Traditional tools for visual communication of resource issues have included simple graphic devices such as maps, line charts, sketches, photographs, and renderings. The new tools include coloured computer maps, 3-D models, animations, and interactive virtual reality environments used to explore design ideas (Imaging Systems Laboratory, 1995). Photomontage techniques use a combination of photographs, renderings and artistic license. Kennie and McLaren (1988) define photomontage as "a physical or image composite of photographs of the existing landscape with a registered computer generated image of the proposed design object(s)".

Computer graphics is incapable of substantiating all the details recognisable in the immediate surroundings. The visual simulation program must therefore be considered as a support system to help a designer to outline the basic features of the environment (Pukkala and Kellomaki, 1988), it will never be able to represent the landscape as it is in reality. The closest images will be produced by reproductions of the phenomena based on the laws of physics (Kennie and McLaren, 1988).

However, as Brabyn (1996) points out, the landscape people percieve cannot possibly contain all the information that exists in reality. The landscape they see is a generalisation of reality, and an impression from a distance can give an indication of this generalisation.

Zube et al (1987) classified computer simulations as static or dynamic simulations. As the name implies, dynamic simulations using computer animations and video techniques, illustrate the proposed development from the point of view of a moving observer. On the other hand, static simulations illustrate the proposed development as viewed by a stationary observer.

Dynamic simulations have the notable advantage over static simulations, in that the observer can move freely and is not restricted to predetermined viewpoints. However, they require fairly advanced and sophisticated computing equipment. Static simulations have the advantage that they can be realistically illustrated to near photograph quality and are far less expensive and labour intensive to produce than dynamic simulations. However, dynamic simulations are rapidly becoming feasible, with systems such as those desribed in the later section on dynamic simulation of landscapes.

Visualisation and Geographic Information Systems

GIS-based visualisation goes beyond the simple ability to discuss anticipated outcomes via traditional graphic tools. It offers the opportunity to visualise relationships across time and space, and to explore more comprehensive ranges of possibility (Orland, 1994). More flexible visualisation methods would enable users to select their own viewpoints and be free of weather, seasonal and other restrictions. Currently the emphasis for providing that flexibility is on GIS. However, GIS-driven image creation does not currently provide a means of integrating detailed, small-scale visualisation with large-scale regional views. The coarse grain of data sources such as digital elevation models and remote sensed imagery make GIS most appropriate for large-scale, synoptic, views of resource issues (Orland, 1995). It is as yet not so useful for small scale, detailed visualisations.

Currently, visualisation in GIS systems is generally limited to two-dimensional viewing either of individual GIS layers or of the results of GIS analyses. Pseudocolour representations of data variables are often used to identify different regions within a raster GIS whereas line styles, widths, colour and symbolisation are used for data representation for vector GIS. True colour combinations of multiple raster GIS layers can also be accomplished for viewing the spatial relationships between the layers (Faust, 1995).

Several GIS systems currently have the capability of creating three-dimensional perspective images by using elevation data for geographic areas overlaid with a GIS variables such as land cover or land use. In most cases this imagery is simply used for show, and there is little or no analytical work that can be accomplished with the perspective image. Measurements of size and shape are not valid in a perspective image without significant ancillary information being present along with the perspective image. In addition, these perspective images are generally well received as showing the relationships of the GIS data to the natural terrain; these factors have limited the usefulness of the perspective images to 'show and tell' type applications (Faust, 1995).

Bishop and Hull (1991) have the following to say about GIS and visualisation in the future:

Criteria for good simulations

Sheppard (1989) proposed five criteria to achieve good simulations: representativeness, accuracy, visual clarity, interest and legitimacy. Representativeness was taken to mean that the simulation should represent key viewpoints of the project. Accuracy was taken to mean the similarity between the simulated image and project after construction. Visual clarity was taken to mean that details, parts and overall contents have to be clearly recognisable. Interest was taken to mean that the simulation should hold the attention of the viewer. Legitimacy was taken to mean that a simulation must be defensible in that it could be shown how it was produced and to what degree it is accurate.

Within the last few yeas, computers have been widely used by environmental designers to produce photo-realistic simulations of physical alterations to existing landscapes. Computer simulation techniques have amply been shown to achieve the criteria suggested by Sheppard (1989). There are a number of good reasons for its popularity. The costs of computer software and hardware are affordable. Most importantly, the technology has reached the stage where contextual realism is not difficult to achieve.

Simulations can be altered or amended easily. This flexibility offers the attractive opportunity of considering alternative designs or of viewing the design from different vantage viewpoints at a press of a button - which is an obvious advantage in Viewpoint Analysis. Computer simulation techniques are now commonly used as a medium for the presentation of design ideas and in assessment of visual impact (VIA) based on Viewpoint Analysis.

Simulation Techniques

Static simualtion techniques

Oh (1991) classified computer simulation methods commonly used in practice into four types:

Wire-frame (W-F) is the lowest of 3-dimensional modelling, the W-F model is composed solely of 3-D points connected by segments. W-F models cannot represent surface and volumetric properties and are often spatially ambiguous. To enhance the image, removal of hidden lines is often used.

Surface model (S-M) is an advanced form of 3-D modelling from the W-F, the S-M recognises not only vertices and edges but also closed polygonal surfaces of 3-D objects and allows properties of such faces to be specified. The image can be much more informative than W-F model by applying hidden surface removal, surface colour and texture, shading, shadow casting and even ray tracing.

Combination of surface model images with scanned photographic images (COMB). One reason why traditional computer-aided design (CAD) images have been recognised as being artificial and machine generated is the omission of the textural background (Greenberg, 1984). As a solution to this problem, the COMB method employs scanned photographic images of the existing landscape as the contextual background. For example, proposed objects (e.g. buildings, structures, etc.) that were simulated by the S-M method are superimposed onto the scanned photographs of the existing landscape where the proposed features do not exist. However, this method differs from the image processing (I-P) method in that it does not involve any 'touch-ups' other than scaling and superimposing them into the scanned backgrounds.

Image processing (I-P) method uses scanned photographic images of the existing landscapes as a basis for simulations and allows manipulation of those images using on-screen imaging tools. It can borrow realistic textures, colours, shades, etc., from various scanned images and superimpose them onto the simulated images to add more realism.

In recent years, advancements made in computer simulation technology including hardware and software have made it possible for proposed developments or modifications on landscapes to be illustrated with a very high degree of accuracy and realism. It is a tool which is now widely used in the presentation of visual impacts. The simulation techniques facilitate the control of variation in the visual stimuli, and to study and develop predictive models for, using psychophysics, the visual impact of particular landscape modifications on observers.

Methodological Issues

The use of the real environment can often be logistically difficult and impractical, especially if the studies involve a wide range of landscapes and large groups of observers. The obvious problems include the transportation of numerous observers, changing weather conditions, the difficulty for observer to make valid comparisons between one site and another. To overcome these problems many studies have used photographic simulations. Photographic simulation is essential in this research both as a medium for illustrating changes to landscapes (before and after the introduction of man-made structures), and a medium of presentation for eliciting peoples' reactions to these changes.

Dynamic Simulation Techniques and Rendering

It is possible to simulate landscapes as they might look as a result of environmental impacts such as building or forestry developments, or to test environmental models (Fisher et al, 1993). Terrain modelling is possible in a range of different guises from the simple vector (or wire-frame) surfaces displayed as rectangular or triangular matrices, to sophisticated colour perspectives generated from complex hidden-line and hill-shading algorithms (Moore, 1990).

Commercially available, generic toolkits, such as PV Wave, AVS and Explorer, can be used for the production of visual displays of different types of data. This generation of dedicated graphics software epitomise the visualisation revolution in computer graphics (Fisher et al, 1993), however, they require powerful hardware, such as Sun or Silicon Graphics workstations. Less powerful PCs and Apple Macintoshes have an increasing potential for visual display and can be used as effectively in developing new visualisation strategies.

Combinations of modelling software and rendering software (such as MultiGen and Iris Performer for the Silicon Graphics platform) can produce three-dimensional landscapes which may be walked or flown through in real-time. With the addition of virtual reality visioning equipment (such as goggles or helmets) these systems can produce a high degree of realism. Examples of models created using MultiGen may be seen in Task Four.

The potential for viewing three-dimensional landscapes has increased enormously in recent years with the growth of the World Wide Web and the ability to view models written in virtual reality modelling language (VRML) on many computer systems.

Degree of realism is dependent on several factors including nature of the application, the objective of the visualisation, the capabilities of the visualisation, capabilities of available software/hardware package and the amount of detail required and/or available (Kennie and McLaren, 1988).

The majority of computer graphics techniques have been developed to address the visualisation of objects that have their geometry defined using a mesh of planar surfaces such as triangles. This can lead to jagged edges on curves, this is often solved using anti-aliasing techniques (Kennie and McLaren, 1988). The anti-aliasing for montage methods should be different from other usual ones because the background scene includes pixels which change pixel by pixel, and image overlay operation is performed several times (Nakamae et al, 1986). The aliasing problem also occurs when foregrounds are superimposed onto the computer-generated images.

Special problems are posed by the realistic rendering of landscape because of the amount of detail required. Fractal methods have been proposed to allow database amplification, which is the generation of controlled random detail from a fairly sparse description. An alternative approach is to use texture mapping methods on a few simple primitives. The texturing is defined procedurally, which may be expanded without loss of high frequency detail, or shrunk without the occurrence of aliasing artefacts (Miller, 1986). Fractal subdivision methods are slow and generate defects due to what is known as the 'creasing problem'. The texture map methods, on the other hand, display visible discontinuities in texture gradient where two surfaces intersect.

An accurate representation of each detail in the scenery is not possible and also not necessary (Gross, 1991). Using only satellite data, observer positions close to the ground or narrow fields of views result in large quadrilaterals in the foreground due to perspective foreshortening. Therefore, resolution should be high towards the foreground or local zone, but the resolution should decrease towards the background (Graf et al, 1994). Far away from the observer it is sufficient to present the scenery at a low level of detail using hierarchical data sets in order to limit the corresponding data. Photo-realistic rendering is provided with great success by texture mapping of remote sensing data on the digital terrain model. This method is useful for great distances from the observer (Gross, 1991).

Due to scattering effects by water molecules, dust and pollution, objects appear to lose their colour and intensity with increasing distance. The reduction rate of colour and tone depends on the various factors such as seasons, weather conditions and time. The colour and tone become grey as the distance becomes large. The hazing affect created due to the atmospheric moisture content leads objects to undergo exponential decay of contrast with respect to distance from the viewpoint (Kennie and McLaren, 1988; Nakamae et al, 1986; Graf et al, 1994).

The human eye relies on colour fading for correct depth perception. Therefore in order to enhance realism and to maintain the estimation of distance, atmospheric effects must be modelled. (Graf et al, 1994). The fog effect increases the sense of perspective in the montages. The shading and shadows of the computer generated images help a montage match to the background scene (Nakamae et al, 1986).

There are several other factors which must be considered when rendering landscapes. Both earth curvature and atmospheric refraction must be taken into account in a simuation (Aylward and Turnbull, 1977; Kennie and McLaren, 1988). In order to use satellite images and aerial photographs for perspective viewing, the images must refer to the same geometric reference as the digital terrain model (Graf et al, 1994).

Validity of Photographic Simulations

A question to address in producing photo-realistic simulations is: how good is good enough? A good enough image is one that has a high degree of perceived realism, conveys maximum quality, contains enough data, yet is efficient in terms of equipment costs, storage and management. Perceived realism may not necessarily vary directly with image quality. Image quality may be very high in technical terms, while perceived realism is not (Perkins, 1992), although image quality will affect perceived realism, so will the content of the image, the viewpoint of the image and the receptivity of the viewer. Daniel (1992) suggests that image quality is sufficient when additional inputs to improve image quality do not result in an increase in image validity, or indeed, in perceived realism.

Some basic understanding of the factors that influence the perception of image quality is therefore needed to increase the 'fit' between computer-generated images and real world conditions (Perkins, 1992). Public perception studies have been conducted with images and they indicate that simulations are achieving a high degree of validity (Orland, 1995).

If the intent is to convey the potential impact of proposed management actions, with the goal of informing public review and approval processes, then more realism and detail may be demanded in the visualisation. Techniques include photo-realistic simulations, and hand-crafted graphic renderings and models (Orland, 1994).

Computer image editing methods can be more realistic than hand rendering and less expensive than photo-retouching and they do much to convey a realistic visual experience of the planned new environment. The realism and transparency of the medium to a non-expert viewer is high, but the accuracy and validity less easy to defend (Orland and Daniel, 1995). In the study by Oh (1994) only image processing was successful in separating the visual attractiveness of one landscape from another in simulations; the other methods used were wire frame, surface modelling and combined surface modelling and scanned photographic images.

Many studies have tended to focus on the realism or accuracy of simulation. But simulation cannot reproduce that reality completely. Rather, it selects critical aspects of that reality for the particular purpose at hand (Oh, 1994). In practice the simplification or abstraction of detail is directly related to the savings of effort, time and costs of simulation.

In many ways, schematic images, those which do not attempt photo-realism, are as useful as the more realistic images. They do not require the technical complications of photo-realistic visual simulation and do not have the theoretical problems associated with defining realism. These views are approximations - more realistic than just plan views, but more schematic than photorealistic renderings or presentation drawings (Ervin, 1993).

In schematic renderings the images are rough; colours are shaded, the ground is broken up into half-acre coloured triangles, and all trees and buildings are alike and rather diagrammatic. There is no provision for subtleties of texture or curved surfaces. These representational conventions are no more limiting than any others commonly encountered in design, and they are no more difficult to understand (Ervin, 1993).

For some purposes, the visualisation media may intentionally be highly abstract and intended to convey information most effectively to experts within the same discipline. In this category are coloured maps, where the need is primarily to represent single issues such as the extent or locations of an impact, or statistical displays of simulation models where the purpose of the visualisation is to prompt further modification of resource models and hence to understand better the underlying physical system (Orland, 1994).

Oh (1994) compared computer simulations using four techniques described earlier, of building/site construction project at University of California campus against photographs of actual post-construction site. His study found that I-P simulations were the most effective in portraying reality, followed by COMB, S-M, then W-F simulations.

Bishop and Hull (1991) cited three different studies to support the validity of using computer simulations as surrogates of the actual environment (Bishop and Leahy, 1989; Orland, 1987; Vining and Orland, 1989). Bishop and Leahy (1989) reported the validity of substituting computer generated images for photographs of landscapes. They showed a moderately strong relationship between photographs and computer simulations of landscapes based 256 colours and medium resolution. Vining and Orland (1989) reported good correlations between computer simulated images and photographs of three different environments. The authors did not indicate the hardware standards employed.

Orland (1987) found very good correlation between preference for photographs and computer simulated images using a 16-bit (32,000 colours or high colour) low resolution (256 x 240 pixel) system for urban scenes. Orland reported that high level colour fidelity is more important than low resolution quality for simulating built environments.

The validity of using photographs as surrogates of actual environments has been an interesting topic of debate particularly during early studies in landscape research. Objections are often raised in the sense that photographs are less complex, less multi-dimensional and offer less interaction than do real scenes (Abello et al, 1986). This methodological issue has largely been resolved following the findings of numerous studies mentioned in reviews by Shuttleworth (1980), Nassauer (1983), Zube et al (1987) and Bosselmann et al(1989). These studies have tended to show that people's responses to real environments are similar to their responses to photographs.

Obtaining Observer Responses

The use of rankings is simple and straightforward. The procedure requires that all landscape scenes are presented simultaneously. This is to enable the respondent to make valid comparisons between all the photographs. According to Daniel and Boster (1976), few observers can be expected to judge and rank more than 10 photographs at one time.

The last two methods, SBE and LCJ, have been extensively used in studies involving people's preferences especially of forested environments. The advantage of these two methods is that they try to account for any potential variability between individual observers and produce measurements of interval scale quality (Buhyoff and Leuschner, 1978).

Like rankings, the use of aggregate or average ratings is also simple and straightforward. There is no need to transform or standardise and aggregate the ratings of many individual observers using complex statistical formulae into a single interval quality. The ratings procedure allows a much larger number of landscapes to be evaluated.

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