Landscape visibility computation: necessary, but not sufficient

Environment and Planning B: Planning and Design 2003, volume 30, pages 757 ^ 766

DOI:10.1068/b2968

Landscape visibility computation: necessary, but not sufficient

Stephen Ervin, Carl Steinitz

Harvard Design School, 48 Quincy Street, Cambridge, MA 01238, USA; e-mail: [email protected], [email protected] Received 26 July 2002; in revised form 28 March 2003

Abstract. In this essay we review the major developments in the history and techniques of landscape visibility analysis, providing a number of examples and identifying a few critical challenges to the community of those who would seek to evaluate visibility öand related characteristics such as visual quality or preferenceöin landscapes. We argue that visibility per se is a necessary prerequisite, but insufficient in itself, as a basis for the common planning, design, and public policy questions in the context of which many visibility analyses are instigated.

Introduction The emergence of powerful analytic tools in GIS (geographic information system) software, coupled with computer graphics techniques such as ray-tracing, etc, has led to great advances in understanding the optical physics of intervisibility in landscapes, buildings, and urban environmentsöbut not correspondingly to any better understanding of ``what will be seen?'' or ``why?'' We are among those who are engaged in the process of using computer graphics (and other methods) to attempt to predictively assess landscape perception. And although we have used and performed visibility analyses, we are sure that, just because a GIS computer program says an area or feature of the landscape will be visible from a specified viewpoint, that does not mean that it will be seen, or remembered. We worry a lot about what, and why, to represent in a GIS or other computer system, not just how. And we are sure that the rules for visibility from a stationary point on a clear day will not be the same as those from a speeding train on a cloudy night. Hence we find ourselves asking `Àre we (personally, and as a research and practice community) engaged in visualizing, and predicting visibility, on the basis of available data and computational techniques, or on the basis of real perceptual understanding?''öand suspect that it is rather more of the former, in spite of our desire for more of the latter. Just as the proliferation of rendering software made more spurious designs look more appealing, and the ease of use of desktop mapping systems has led to a growth of questionable, but graphically well-composed, maps and map analyses, so the ready availability of viewshed mapping may have led to superficial answers to many questions about managing our visual resources, and deflected attention from the more difficult, dependent questions about what is `seen', and why. Visibility as a termöalong with some related terms, such as viewshed, visual quality, and visualizationöis very much evident in the literature and practice of landscape planners and designers. The linkage between landscape and scenery (or scenic value, etc) is deep and wide, with ancient roots in culture, painting, and poetry, and modern manifestations in computer graphics and environmental laws. What we see, and what we make of what we see, are questions that drive many, including researchers, planners, designers, computer programmers, cognitive psychologists, and others. This is so not just in the real world, with vistas and viewpoints, but also in communications and

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virtual worlds, where creating the right visual artifact (drawing, photograph, computer rendering) is an act of high art and often high stakes. The dominance of the visual field for human perception is well known, and so it is no surprise that so much effort goes into both using, and trying to predict the impacts upon, our visual fields in so many activities, ranging from making regional development plans to positioning an armchair for the best view of the seashore. Much of our knowledge is based upon vision (Arnheim, 1969). Even in ordinary English, `to see' can mean to understand; one's `view' means both what is immediately in the visual field, and also a broader philosophical and psychological conception; and `vision' is both immediate and limited by optics, and also metaphysical and unbounded in scope. This duality between simple view and vision (based on optical physics), and more metaphorical views and visions (transcending physical limitations), is parallel to a duality between what is `visible', and what is `seen', in the landscape. The first is fairly easy to compute (under a set of simplifying assumptions), the second is not. In this brief paper we review some of the developments to date in the area of computing what is visible; compare that with some work on understanding better what is `seen' (and so remembered, preferred, protected, etc); and conclude with some questions which remain interesting areas for investigationöperhaps some of the `real' questions, for which visibility is a reassuring surrogate. Landscape visibility computation Visibility analysis in landscape planning and design is a relatively recent undertaking (last forty years). However, awareness, whether unconscious or articulate, of visual qualities and lines of sight has been part of human activity, settlement building, military defense, hunting, and agriculture since prehistory. Evidence is suggestive than ancient civilizations constructed important edifices with respect to various lines of sight and visual access. The construction of the city of Rome and early Italian hill-towns has been theorized to have been influenced by established lines of sight, and the development of visual prominent locations. Contemporary archaeological investigations have used various computer-mapping techniques to analyze prehistoric constructions for line-of-sight determinants in the landscape, theorizing that site locations were at least partly based on visibility of other monuments or prominent landscape features (Christopherson and Guertin, 1996; Wheatley, 1995). Axial views, entry sequences, optical illusions, camouflage systems, and other artifices of visual appreciation in a landscape, were highly developed in the past two centuries of landscape and garden design. The `ha-ha' of 18th-century English garden design is one such device: a raised berm of earth hiding a depressed cart path below and behind it, so that animals, laborers, and commercial vehicles could come and go, unseen in the visual field of the aristocratic landowner's mansion (Newton, 1971). The utopian agricultural landscape of the Gartenreich Wo«rlitz in Dessau, Germany, like other contrived landscapes, uses a series of axial views from location to location, as well as a prominent central chapel spire to aid in orientation, as organizing devices for the layout (Steinitz, 1998). More current landscape planning and design is concerned with public landscapes and visual character, rather than just the gardens and estates of the privileged few, and the evaluation and protection of public visual resources. In seminal and highly influential work in the 1960s, the landscape planner Phil Lewis introduced the term ènvironmental corridors' (Lewis, 1964) describing the confluence of ecological, scenic, and recreational assets (often following hydrological corridors). In the intervening years, landscape planners have used the terms `view corridors' and `visual corridors' to describe open, linear views in the urban and natural landscape, usually with an eye to evaluation, improvement, or protection.

Landscape visibility computation

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Most recently, landscape architects have adopted computational techniques for `seen-area' mapping, or `viewshed' delineation (by analogy to the hydrologic watershed, the viewshed is that area of land all of which is visible by unimpeded line of sight, from a single point, analogous to the spill-point of the watershed) (Felleman, 1979). The origin of this term was apparently with the Forest Service in the 1970s, and seems to have become widespread through the legal requirements of the National Environmental Protection Act of 1969, which mandated among other things the evaluation and protection of scenic resources. In addition, the National Wild and Scenic Rivers Act also extended legal status to the visual and scenic resources of selected rivers throughout the USA. The questions of ``what are scenic resources?'' and ``how might they be protected?'' naturally gave rise to a wide range of theoretical inquiries and practical applications, including computer software, dealing with visibility and evaluation. The computer program VIEWIT (Amidon and Elsner, 1968), promulgated by the US Forest Service in the 1970s, and used by many natural resource planners, landscape architects, engineers, and others, seems to have been a principal vector for the dissemination of the idea and capability of viewshed analysis, if not the term itself. Modern usage, especially in landscape planning law, has come to mean generally `the scenic view from a place' where place may include a linear feature such as a road or a river. Technically, viewshed calculations are usually performed with GIS software, based on raster (gridded) or triangulated (TIN) terrain surfaces, specified viewer-position(s), and some number of parameters which may include viewer height, and height and opacity of intervening objects or land uses. Several commercial GIS software packages offer this function in a simple operation or command, with optional control over various parameters. The most common result is a (raster) map showing binary visibility (that is, 1 visible, 0 not visible) for some number of locations (usually all cells in a raster map) in the study area. Two common interpretations of these maps, often assumed to be equivalent, are as answers to the questions ``what areas of the landscape can a viewer at this position see?'' and ``from what areas of the landscape can an object located here be seen?'' When more than one viewpoint is analyzed, the results may also be summed, answering the question ``from how many locations (in this area, or along a path, for example) can this location be seen?'', enabling an evaluation of more visually prominent locations or objects. Clearly, the validity of these answers is highly dependent upon a number of variables, and subject to several kinds of error. As Fisher (1991; 1992; 1993; 1995) and others have pointed out in a series of publications, visibility should more realistically be described as a probabilistic outcome, rather than a binary one, giving rise to `fuzzy' or `probable' viewsheds, in which intervisibility between two points is given a probability, say between 0 and 1, rather than a binary deterministic answer. This is because of the various sources of error and uncertainty in the source data, including the necessary simplification and aggregation in raster elevation data to start with, compounded by the complexity and uncertain visual properties of intervening land uses, atmosphere, and physical elements (the tree branch in the foreground which effectively obscures 50% of the visual field, and so on). Even the curvature of the earth must be taken into account in landscape-scale visibility analyses. Many digital terrain models record elevations as if they were from a plane, rather than a sphere, and not all computer software is designed to calculate the subtle, but real, effect of the earth's curvature (a curvature of just 1 in 10 000, only a fraction of a percent, but even one meter can make a difference in some visual assessments). Recent studies comparing computed viewsheds with field observations concluded that viewshed computations were in some cases less than 50% accurate (no better than a random map!) (Maloy and Dean, 2001).

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If we take the rosy view that these data errors can be minimized, and reliability of visibility maps improved, such maps are potentially valuable indicators of landscape qualities. Secondary measurements of the viewshed, such as its total area, its longest reach, the roughness measure of its perimeter, the presence and number of ìslands', and the aspect ratio of its major and minor axes, can be used to infer aspects of the visual experience and `structure' of the landscape. Given a viewshed from a single point, the area of the viewshed can be interpreted as ``how good a lookout position is the viewpoint'', and can also be interpreted in reverse, as the number of locations from which an object at the viewpoint can be seen, or a measure of its visual prominence. As the viewshed itself is effectively a first derivative of the terrain surface, these measurements may be called second derivatives, akin to the measure of the change of slope (or concavity or convexity) where slope is also a first derivative of terrain. These aggregate second-order characterizations may be very interesting to landscape planners and designers, as they may be the most likely to correlate with human perception and preference. (The human eye ^ brain, after all, does not compute areas or angles with any precision, but potentially does recognize `linear', or ìnterrupted', or èxpansive' views.) Atmospheric factors in landscape perception represent an additional substantial complication to visibility calculations. Naturally occurring haze, fog, and weather conditions, combined with anthropogenic pollution and aerosol particles, can substantially impact visibility over distances of several miles, and even shorter distances (Environmental Protection Agency, 2002). In aviation and navigation, `visibility' is used to refer to the distance of unimpeded visual range, because of atmospheric factors, as in `visibility of 1000 feet'. Furthermore, the impact of atmosphere on visibility is not simply quantitative, but qualitative also; landscapes seen through distant haze may suffer from coloration and contrast modifications, so that textured green hillsides in the midground become hazy blue-gray forms in the background, before fading from visibility altogether. Finally, lighting conditions of all kinds greatly influence visibilityö from the glare of sunshine in the viewer's eyes, to the lack of lighting at nightöalthough these are rarely accounted for in most visibility computations. The viewer position is often taken to be simply a point location öor a specified z-elevation above the center of some raster cellöbut in fact the characteristics of the viewer position may affect the perception of the area seen. Three qualitatively different conditions exist when the viewer is above, below, or just at eye-level with the majority of the seen area (as when looking down into a valley, or looking up out of it) (Litton, 1968). The local microconditions of vegetative cover and other visual obstacles in the viewer's immediate area will have a significant impact on the actual field of view and area of surrounding landscape seen. Even the apparent equivalence of `where the viewer can see' and `from where the viewer can be seen' in such maps is questionable, because of the typical difference between the elevation of the viewer (eye-level) and the elevation of the landscape seen (given elevation, possibly modified by land cover). For extreme cases, such as evaluating the visibility of cell-phone towers, the premise of floating a camera attached to a large red balloon, and assuming that any place the camera can see, can also see the red balloon (or top of cell-tower), is probably justified. For more subtle intervisibility, involving concealed human observers in natural landscapes, as in military, intelligence, and surveillance situations, the reciprocity of viewer and target should not be so easily assumed (Fisher, 1996). The basic idea of connecting objects by straight lines of sight (`rays') from a viewer position (èye-point'), at the heart of viewshed analysis, is the same geometric technique used in architectural rendering by so-called `ray tracing'. This technique is


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used especially to simulate optical characteristics such as transparency, reflection, and shadowing, which all depend upon the bouncing of light rays in the environment. The development of computer hardware and efficient algorithms for performing what is essentially a combinatorially repetitive (and in the case of ray-tracing, sometimes recursive) calculation has made the possibility of performing viewsheds analysis, and ray-traced renderings, in reasonable time on ordinary computers, with digital models of not-too-enormous magnitude, a reality in modern research and practice. Architectural theorists in the 1980s developed the technique of viewshed with respect to architectural spaces and floorplans, following the work of Benedikt (1979) who borrowed the term ìsovist' (from earlier landscape-analysis literature) to describe those areas of visibility to a viewer in two dimensions. This work harkened back to an early computational geometry puzzle known as the àrt gallery theorem' (O'Rourke, 1987). Simply put, given a polygonal floor plan of arbitrary complexity (a presumed art gallery), and assuming no visual obstruction other than the walls, how many guards (with 3608 visual fields) would be required, and where should they be stationed, to provide visual coverage of all the walls of the floorplan? This problem, and some of the results, were important in the development of computer graphics and robotic vision techniques, and presumably with some application to actual surveillance systems. Researchers have attempted to demonstrate how various measures of isovists, such as compactness, clustering, minimum and maximum angles, and so on, can be related to `spaciousness', `sense of enclosure', and other perceived or geometric qualities of space (at least as represented in two-dimensional plans) (Turner and Penn, 1999). Following the work of March and Steadman (1971), Hillier and Hanson (1984), and others, other researchers have continued to use intervisibility computations as an analytical device for inferring second-order properties of architecture and landscapes. Turner and O'Sullivan (Turner et al, 2001) have developed the idea of `visibility graphs'öessentially exhaustive intervisibility computations between all combinations of locations (however defined) in an environmentöas another way of describing and analyzing spatial environments. Like isovists, these visibility graphs, it is argued, can be used to identify visually connected spaces, important vistas, and other visual or spatial characteristics. Computation and analysis of visibility are increasingly important for robotics research, as well (Cohen-Or et al, 2000), because both rapid estimation of field of view, and intelligent interpretation of visual scenes are essential parts of machine vision. Researchers have also explored techniques for improving the efficiency of visibility algorithms by using various techniques, for example taking clues from the inherent topographic features of terrain such as ridges and valleys (Rana and Morley, 2002). `Visible' versus `seen' All of these above discussions and developments have been concerned with the objective calculation of the visibility (whether deterministic or probablistic, based on optical science and trigonometric calculations) of points on a terrain (usually a coarsely discretized raster surface). Although these analyses may have, even in spite of the possibilities of error and uncertainty in their calculations, some value such as in locating microwave transmission towers requiring line-of-sight connections (De Floriani, et al, 1994), they may or may not have much bearing on what is really `seen' in the landscape. Although the basis for most intervisibility algorithms in most commonly used GIS software is effectively strictly geometric, relying upon trigonometric calculations from interpolated height fieldsöeven when these calculations have been made fuzzy using various statistical techniques öthey may or may not reflect what a human viewer would actually `see'. For human perception is a combination of optical physics, atmospheric effects, and other more psychological and cultural factors.

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For one thing, the human visual system does not simply work on straight lines of sight; the human visual system has a cone of vision, with highly resolved (`foveal') vision at the center, and more aggregate, but equally important to perception, peripheral vision at the edges. Second, humans can usually only look in one direction at a time, though the eyes can pan and roam even as the head is moving in another direction; and are often in motion, whether walking a path or driving along a highway, when viewing a landscape. Third, we need to consider some of the nontrigonometric determinants of perception, including cognitive, cultural, and other psychological factors. Assuming that all of a scene is objectively visible, what stands out, or is rememberedöand so, presumably, what may become preferred or valued or photographedöis only some subset of the elements of the scene. Some strictly visual attributes are important in this process. Coloration, contrast, and texture can affect visual prominence. (A single red-foliaged tree will stand out, and so be seen, against a forest of visible but unseen ordinary green trees. Similarly, an unusually smooth area of water in a sea of waves and ripples will be noticed; as will an artificially straight or angular artifact in a naturally curved or irregular context.) A single tall tree, located on the ridge and so silhouetted against the evening sky will be `seen' more readily than its equally visible neighbors just downslope. So too will the psychology of the human viewer, and the context, determine what is seen: a hunter and a painter and an airplane pilot and a real-estate developer will all tend to `see' different aspects of a single scene. Psychologists such as the Kaplans and others have explored what makes for selective vision, and a number of causal, or at least associative, factors have been suggested, ranging from sex and age to occupation and cultural context (Kaplan and Kaplan, 1982). These cause variation not just in what is noticed, but especially in what is valued and preferred. What we see and prefer to see is also a question of aesthetics. In part because of national legislation which mandates protection of `scenic quality', a number of researchers, environmental psychologists, and several national agencies including the US Forest Service, Park Service, and Bureau of Land Management have developed a wide array of tools and metrics for characterizing landscape visual qualities. These include descriptive, qualitative terminology-based systems and point-based, quantitative systems (Daniel and Boster, 1976; Tetlow and Sheppard, 1979). These systems implicitly attempt to answer the question `òf all that is visible, what is seen, and how is it valued?'' A number of researchers in the last thirty years have attempted to simulate these rating systems using GIS and other computational techniques, so as to achieve the goal of predicting or assessing scenic qualities without recourse to a human observer (Bishop and Hulse, 1994). Such systems need to be coupled with strict visibility analyses (what scenic value has a beautiful landscape if it is never visible?) and often employ a weighting system to make scenic value related to some measure of amplitude of visibility (such as by how many people, or from how many locations, a feature is visible) (Litton, 1974). A variety of analytic and evaluation systems have been developed to attempt to quantify visual quality and scenic value, based on intrinsic landscape features, such as presence or absence of water, forest edge, or sky and skyline; or visual compositional features such as shape, line, color, and texture (Smardon, 1986). Other, more difficult to describe characteristics which may be sought after include enclosure, mystery, legibility, and diversity (Zube et al, 1982). These implicitly or explicitly link to measurements of visibility (a feature may only have scenic value if it is visible, and its value may depend on degrees of visibility, however computed). In an attempt to quantify the effects of atmospheric pollution on visibility, and hence on visual quality, researchers with the


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National Park Service have proposed a measurement called the `deciview', to measure change in visual quality as a result of atmospheric haze [by analogy to the auditory decibel, a one deciview change ``represents a change in scenic quality that would be noticed by most people regardless of the initial visibility conditions'' (National Park Service, 1997). What we see among what is visible may also depend on purpose and preconceptions. If we are looking for something in particular, we may well overlook many other things. And we may misidentify landscape features and elements, on the basis of our internal biases. The context of a view has as much to do with the viewer, and his or her situation, mental state, and expectations, as with the landscape itself. Perception of visible elements is just one part of a chain of human cognitive states, which may go something like: purpose expectation preconception context [environment] movement [mode, speed, conditions] VISIBILITY perception [scanning] seeing [understanding] evaluating [meaning and affect] acting [or not] remembering recalling [repeating] ... Of course, this chain need not be linear; there may be feedback loops of various sorts, and so on. The point is just that the viewer's mental and physical state are determinants of the perception as much as the physical layout and optics of the situation (Gibson, 1979). That visibility is part of a sequence is especially important in architectural and landscape design and planning, because the sequence of spaces, structures, and views can be controlled and manipulated. Benedikt and others have used isovist analyses to demonstrate characteristics of different kinds of sequences; Steinitz (1990) has demonstrated that the order in which a set of views is experienced directly affects preferences for scenic landscapes, as in the example of the public generally preferring to drive in one direction, rather than the opposite, of a two-way scenic loop road. If the sequence of movements and spaces, and hence of visibility ^ seeing ^ perceptions, can indeed be controlled, then it can perhaps also be predicted. Modeling the cognitive response of the viewerönot just objectively assessing the landscape öis an open area of research (Baldwin et al, 1996). These questions of selection, of interpretation, and of preference are complex and difficult to quantify or simplify; yet they are often the heart of the matter for landscape planners and designers concerned with visual attributes of the landscape. Raw visibility per se is not often the principal concern. Yet there are special cases where an expanded form of three-dimensional viewshed, or isovist, analysis may be helpful. Consider the real-estate developer's query: ``where should structures be located to maximize the number of patios which have privacy from other patios, but also a view of the sea to the west?'' Or the security official's query ``from which windows of uninhabited buildings is the motorcade route visible with a direct line of sight (or line of fire!)?'' Answers to these questions are partially available with typical GIS software

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and data, though these systems and data usually have limited three-dimensional capability. Some hybrid between GIS and three-dimensional computer-aided design modeling and rendering system may be required. (A ray-traced rendering from a location looking out a window, for example, is a surrogate for a visibility analysis from that window; it just usually cannot be queried in reverse to identify the locations, faces, or polygons in the model that are responsible for a particular pixel in the rendering.) Another way that viewshed calculations may be expanded to become more interesting and useful to landscape planners and designers is to consider the ways in which views from not just points, but also from lines, sequences, and areas, may be computed and characterized. It seems possible that the best description of a `view from the road' may not be just the aggregate sum of individual viewsheds from points at some suitable spacing along its centerlineöa common approachöbut may call for an entirely different representation, as yet undeveloped. The landscape experience along a path requires a form of narrative for which a static, polygonal viewshed may not suffice (Carr and Schissler, 1969). And there may be other kinds of viewsheds which are worthy of development. Fisher, for example, describes the `horizon viewshed' which records the presence of both distant (skyline) horizons and interior horizons, or local ridge lines, behind which invisible land lies, as an interesting variant on the usual viewshed calculation (Fisher, 1996). And there may be others: what about the viewshed of an animal species, which `sees' in terms of shelter, edges, and open sky? Such a viewshed might be a valuable part of some ecological habitat model (Hehl-Lange, 2001). The more that one assumes uniformity of conditions (both in scenes and among viewers)öas opposed to expecting diversity, and group and individual differences öand the more one can accept a `statistical average', the more `visibility' per se, rather than `seeing', will be a useful assessment. However, if one recognizes group and individual differences then a much more complex analysis of `seeing' is required (and `visibility' is a necessary, but insufficient, part of the calculation). In this vein, a visibility analysis might be concerned, at one end, with anything that at least one observer might ever see (the physical ^ optical viewshed); or, at the other end, with only those things that all or most observers would surely see (the psychological ^ cultural viewshed). Summary We have reviewed some of the recent past approaches to the question of visibility in landscape planning and design, and by extension in architectural and urban design. From a simple model of straight lines of sight over a discrete landscape giving rise to a binary visibility measure on a raster map, the idea of viewshed can be extended to multiple kinds of calculations, with probabilistic measurements, which might on the one hand account for atmospheric haze and use rules of composition and landscape perception to modify predicted visibility of landscape areas; and on the other hand, might be coupled to geometric models and databases to connect three-dimensional visibility calculations with logical queries and other database operations. Though the latter are not yet widely available in commercial GIS software, they are possible, and would likely be useful. Is the question of landscape visibility one of physics, or physiology, or psychology? Surely it is all three combined in various ways. Can we build computational models that account for all three? Surely, we can at least make progress in that direction, and in order for computational visibility analysis to become truly useful as a basis for the common planning, design, and public policy questions in the context of which many such analyses are instigated, we need to do so.


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In this vein, we conclude with some open-ended questions which we believe should drive continued investigation into visibility in the landscape. Some questions What are appropriate applications of binary versus probabilistic viewshed calculations? What second-and-higher-order measurements of viewsheds are useful and interesting, for what purposes? What are variants of `visibility' analyses that could use perception, not just geometry? What useful metricsöqualitative or quantitativeöcan be used to describe visibility from a line or an area, not just from a point? What about visibility of a line or an area? What other kinds of `viewsheds' might be computed, beside simple line-of-sight ones? How can characteristics of the `viewer-position' be used to inform the computation of visibility? What about viewer predisposition, or purpose? Can we characterize anything about the invisible or ùnseen' parts of the landscape? Do they too somehow influence perception, behavior or preference? Pursuit of these kinds of questions, further research into the feasibility of predicting or modeling cognitive and perceptual responses, and the development of second-order visibility analyses such as visibility graphs, sequence notations, and others, are the obvious next step once we have robust intervisibility algorithmsöwhich, in this view, are necessary, but not in themselves sufficient. References Amidon E, Elsner G, 1968, ``Delineating landscape view areas ... a computer approach'', RN PSW-180, USDA Forest Service, Pacific Southwest Forest and Range Experiment Station, Berkeley, CA Arnheim R, 1969 Visual Thinking (University of California Press, Berkeley, CA) Baldwin J, Fisher P, Wood J, Langford M, 1996, ``Modeling environmental cognition of the view with GIS'', in Proceedings of the Third International Conference on Integrating GIS and Environmental Modeling, Santa Fe, NM, 21 ^ 26 January (National Center for Geographic Information and Analysis, Santa Barbara, CA) on CD and at http://www.ncgia.ucsb.edu/ conf/SANTA FE CD-ROM/sf_papers/fisher_peter/baldwin.html Benedikt M L, 1979, ``To take hold of space: isovists and isovist fields'' Environment and Planning B 6 47 ^ 65 Bishop I, Hulse D, 1994, ``Prediction of scenic beauty using mapped data and geographic information systems'' Landscape and Urban Planning 30 59 ^ 70 Carr S, Schissler D, 1969, ``The city as a trip: perceptual selection and memory in the view from the road'' Environment and Behavior 1(1) 7 ^ 35 Christopherson G, Guertin D, 1996, ``Visibility analysis and ancient settlement strategies in the region of Tall al-Umayri, Jordan'', in Proceedings of The Annual Meeting of the American Schools of Oriental Research New Orleans, LouisianaöMarriot Hotel http://www.casa.arizona.edu/MPP/ viewshed/vspaper.html Cohen-Or D, Chrysanthou Y, Silva C T, 2000, `À survey of visibility for walkthrough applications'', in Proceedings of EUROGRAPHICS'00, course notes, http://citeseer.nj.nec.com/cohen-or00survey.html Daniel T, Boster R S, 1976, ``Measuring landscape aesthetics: the scenic beauty estimation method'', RM-167, USDA Forest Service, Rocky Mountain Forest and Range Experiment Station, Fort Collins, CO 80521, http://www.fs.fed.us/rm/value/docs/scenic beauty estimation.pdf De Floriani L, Marzano P, Puppo E, 1994, ``Line-of-sight communication on terrain models'' International Journal of Geographical Information Systems 8 329 ^ 342 Environmental Protection Agency, 2002, ``Special Interagency Project on Measurement of Haze and Visual Effects'', http://www.epa.gov/region09/air/mohave.html Felleman J P, 1979 Landscape Visibility Mapping: Theory and Practice School of Landscape Architecture, State University of New York, College of Environmental Forestry, Syracuse, NY Fisher P F, 1991, ``First experiments in viewshed uncertainty: the accuracy of the viewshed area'' Photogrammetric Engineering and Remote Sensing 57 1321 ^ 1327 Fisher P F, 1992, ``First experiments in viewshed uncertainty: simulating fuzzy viewsheds'' Photogrammetric Engineering and Remote Sensing 58 345 ^ 352

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Fisher P F, 1993, `Àlgorithm and implementation uncertainty in viewshed analysis'' International Journal of Geographical Information Systems 7 331 ^ 347 Fisher P F, 1995, `Àn exploration of probable viewsheds in landscape planning'' Environment and Planning B: Planning and Design 22 527 ^ 546 Fisher P F, 1996, `Èxtending the applicability of viewsheds in landscape planning'' Photogrammetric Engineering and Remote Sensing 62 1297 ^ 1302 Gibson J J, 1979 The Ecological Approach to Visual Perception (Houghton Mifflin, Boston, MA) Hehl-Lange S, 2001, ``Structural elements of the visual landscape and their ecological functions'' Landscape and Urban Planning 54 105 ^ 113 Hillier B, Hanson J, 1984 The Social Logic of Space (Cambridge University Press, Cambridge) Kaplan S, Kaplan R, 1982 Cognition and Environment: Functioning in an Uncertain World (Praeger, New York) Lewis P, 1964,``Quality corridors in Wisconsin'' Landscape Architecture Quarterly January, 101 ^ 108 Litton R B Jr, 1968, ``Forest landscape description and inventoriesöa basis for land planning and design'', RN PSW-49, USDA Forest Service, Pacific Southwest Forest and Range Experiment Station, Berkeley, CA Litton R B Jr, 1974, ``Visual vulnerability of forest landscapes'' Journal of Forestry 72 392 ^ 397 Maloy M, Dean D J, 2001, `Àn accuracy assessment of various GIS-based viewshed delineation techniques'' Photogrammetric Engineering and Remote Sensing 67 1293 ^ 1302 March L, Steadman P, 1971 Geometry of Environment (RIBA Press, London) National Park Service, 1997, ``Visibility Monitoring Program'', http://www2.nature.nps.gov/ard/vis/ vishp.html Newton N T, 1971 Design on the Land (Belknap Press, Cambridge, MA) O'Rourke J, 1987 Art Gallery Theorems and Algorithms (Oxford University Press, New York) Rana S, Morley J, 2002, `Òptimising visibility analyses using topographic features on the terrain'', WP 44, Centre for Advanced Spatial Analysis, University College London, London Smardon R, 1986, ``Historical evolution of visual resource management within three federal agencies'' Journal of Environmental Management 22 301 ^ 317 Steinitz C, 1990, ``Toward a sustainable landscape with high visual preference and high ecological integrity: the Loop Road in Acadia National Park, USA'' Landscape and Urban Planning 19 213 ^ 250 Steinitz C, 1998, `Àlternative futures for the Gartenreich Dessau-Worlitz'', http://www.gsd.harvard.edu/studios/worlitz/index.html Tetlow R J, Sheppard S R J, 1979, ``Visual unit analysis: a descriptive approach to landscape assessment'', in Proceedings of Our National Landscape: A Conference on Applied Techniques for Analysis and Management of the Visual Resource general technical report PSW-35, Pacific Southwest Forest and Range Experiment Station, Berkeley, CA Turner A, Penn A, 1999, ``Making isovists syntactic: isovist integration analysis'', in Proceedings of the Second International Symposium on Space Syntax Brasilia, Brazil, 29 Marchö 3 April, Universidade de Brazilia, http://www.vr.ucl.ac.uk/people/alasdair/publications Turner A, Doxa M, O'Sullivan D, Penn A, 2001, ``From isovists to visibility graphs: a methodology for the analysis of architectural space'' Environment and Planning B: Planning and Design 28 103 ^ 121 Wheatley D, 1995, ``Cumulative viewshed analysis: a GIS-based method for investigating intervisibility, and its archaeological application'', in Archaeology and Geographical Information Systems: A European Perspective Eds G Lock, Z Stancic (Taylor and Francis, London) pp 171 ^ 185 Zube E H, Sell J L, Taylor J G, 1982, ``Landscape perception: research, application and theory'' Landscape Planning 9 1 ^ 33

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