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Further information
Review of Existing Methods of Landscape Assessment and
Evaluation
Introduction
Landscape should be recognised as a resource and is therefore a variable to
be considered in land use decisions (Dearden, 1985). When
evaluating landscapes one should use an interdisciplinary approach, communicate
with other evaluators and, importantly, recognise the academic respectability
of the elementary (Appleton, 1975).
"Just as the Brisbane wicket after rain used to be said to
reduce all batsmen to an equal level of incompetence, so this absence of
aesthetic theory brings the professional down to the same plane as the man in
the street. It is true that the theory underlying the judging of a fine wine or
a good piece of sculpture is probably as obscure as that which underlies the
evaluation of landscape. In those arts, however, we still have some faith -
possibly misplaced - in the ability of the expert to recognise excellence,
however defined (Appleton, 1975)."
A structured method of landscape assessment, linking description,
classification, analysis and evaluation, will provide an integrated framework
within which decisions on land use management and advice can be debated
(Cooper and Murray, 1992). One of the biggest problems in
developing quantitative assessment methods for scenic impacts is that of
measuring the contributions of specific landscape elements to overall
preference (Buhyoff and Riesenmann, 1979).
During the late 1960's through to the '70s, there was an emphasis in
landscape assessment to produce 'objective' and quantitative methods of
attaching a numerical value for the 'subjective' responses to aesthetic or
scenic quality. These methods were developed to act as evaluative tools to
enable an evaluation to be repeated by different observers, or carried out in
different areas and still produce comparable results (Robinson
et al., 1976) that is they were expected to give reliable and
consistent information about the observers' responses to landscape quality.
Unwin (1975) describes three phases of landscape
evaluation.
- Landscape measurement: an inventory of what actually exists in the
landscape;
- Landscape value: an investigation and measurement of value judgements or
preferences in the visual landscape;
- Landscape evaluation: an assessment of the quality of the objective visual
landscape in terms of individual or societal preferences for different
landscape types.
Definitions in landscape evaluation
Before the subject of landscape evaluation can be reviewed, it is necessary
to define several key words. In the course of this report the term "total
landscape" refers to the less tangible properties of the landscape as well
as the more obvious visual properties and should not be confused with
"landscape" which refers to the visual properties only.
Unfortunately, this differentiation is not always apparent in the literature.
Landscape
Hull and Revell (1989) define landscape and scenes as:
"The outdoor environment, natural or built, which can be
directly perceived by a person visiting and using that environment. A scene is
the subset of a landscape which is viewed from one location (vantage point)
looking in one direction ..."
The term landscape clearly focuses upon the visual properties or
characteristics of the environment, these include natural and man-made elements
and physical and biological resources which could be identified visually; thus
non-visual biological functions, cultural/historical values, wildlife and
endangered species, wilderness value, opportunities for recreation activities
and a large array of tastes, smells and feelings are not included
(Daniel and Vining, 1983; Amir and Gidalizon, 1990).
Landscape quality
Often landscape quality is defined as including a wide range of
environmental/ecological, socio-cultural and psychological factors. According
to Jacques (1980) the distinction between 'value' and
'quality' is meaningless, since both terms refer to the comparison of the
landscape in front of your eyes to an idealised landscape in one's mind.
Visual impact
Visual impact on landscape quality is concerned with physical changes
introduced to a site by a new development activity (Amir and
Gidalizon, 1990).
Objective definitions
Visual quality - a phrase synonymous with beauty, but intended to convey an
impression of objectivity; landscape evaluation - ascertaining of a single,
often numerical, measure of visual quality, more appropriately would be "
landscape quality survey"; judgement - the presumed ability by the design
professions to evaluate 'visual quality', as distinct from value (Jacques, 1980).
Subjective definitions
Landscape value - a personal and subjective assessment of aesthetic
satisfaction derived from a landscape type; landscape appraisal - the study of
the effect of landscape changes upon landscape value; preference - the liking
of one landscape type better than another (Jacques, 1980).
Subjectivity versus objectivity
There is a fundamental, theoretical, divergence of opinion over the
question of whether landscapes have an intrinsic or objective beauty which may
in some way be measurable or comparable, or whether scenic beauty is a value
that can only be subjectively attributed to an area or specific landscape
(Shuttleworth, 1980b). While physical geographers have
devised ways of measuring landscape parameters to reflect visual quality; human
geographers have probed individual and societal attitudes toward landscape
(Dearden, 1985).
Orland et al. (1995) have described qualitative
approaches as those which focus upon the evaluation the complexity of landscape
using the judgements of panels of human subjects, and quantitative approaches
as those which measure physical characteristics of the visual field directly.
On the physical/objective side, Buhyoff and Riesenmann
(1979) have presented evidence that certain landscape dimensions can be
used successfully to prepare an evaluation, and that aesthetic impact can be
measured from specific landscape dimensions.
There is an increasing interest in the use of mapped data and geographic
information systems (GISs) to assess visual landscape variables using
reproducible methods over a wide area (Bishop and Hulse,
1994). Recent research efforts have shown that the public's scenic
preferences can be assessed objectively and quantitatively (Dearden, 1980). This research has also demonstrated that
public perceptions can be related to and, in fact, predicted from environmental
attributes of a more tangible nature (Buhyoff et al.,
1994).
The assessment and/or quantification of scenic quality is mandatory for
proper consideration of the aesthetic consequence of management actions
(Buhyoff et al., 1994). The Belgian experience with
landscape evaluation, especially in rural re-allotment projects, indicates, and
international literature from a great number of disciplines or research field
confirms, the necessity to speak of scenic or visual resource management
(Tips, 1984).
Landscape evaluation methods
Numerous techniques of landscape evaluation have been devised in recent
years (Crofts and Cooke, 1974). They form a spectrum in
which the extremes are represented on the one hand by techniques based
unequivocally on the subjective assessments of landscape quality by individuals
or groups (e.g. Shafer et al., 1969) and on the other
by techniques using physical attributes of landscape as surrogates for personal
perception (e.g. Linton, 1968; Land Use Consultants, 1971).
The various models can be subdivided several ways. Arthur
et al. (1977) splits them into descriptive inventories and public
preference models, both categories being further split into non-quantitative
and quantitative methods. Briggs and France (1980) use
direct and indirect methods to subdivide the models; Crofts
(1975) describe two sorts of techniques - preference and surrogate
component techniques; Daniel and Vining (1983) split the
methods into ecological, formal aesthetic, psychophysical, psychological and
phenomenological models. For this review the methods will be split into
descriptive inventories, public preference methods (after
Arthur et al., 1977) and a third category of
quantitative holistic techniques.
- Descriptive inventories include ecological and formal aesthetic models,
methods which are mostly applied by experts in an objective manner.
- Public preference models, such as psychological and phenomenological, are
often undertaken using questionnaires, and are unavoidably linked to the
problems of consensus among the public.
- Quantitative holistic techniques use a mixture of subjective and objective
methods and include psychophysical and surrogate component models.
It is important to examine the reliability and validity of landscape
evaluation models and to identify any assumptions central to the models.
Internal and external validity are of concern in the development of any
landscape visual assessment system. External validity reflects, in part, how
well the system-generated assessments correspond to other, known measures of
visual quality. Internal validity reflects how well the system's internal logic
withstands testing and violation of assumptions (Buhyoff et
al., 1995).
Descriptive inventories
Descriptive inventories comprise the largest category of techniques for
assessing scenic resources; they include both quantitative and qualitative
methods of evaluating landscapes by analysing and describing their components
(Arthur et al., 1977). Classification methods are
those which first attempt to classify the survey units on the basis of their
overall similarity, and then to grade or evaluate the resulting clusters -
formal aesthetic models are an example of this method. Non-classificatory
methods, such as ecological models, attempt to identify the relationships
between selected landscape components and environmental quality, then use these
relationships to predict landscape quality (Briggs and France,
1980).
Descriptive inventory methods rely on combinatorial functions (such as
addition, subtraction and multiplication) to value, compare and aggregate
landscape components which have been identified and measured by an individual
expert or team of experts. The components in the inventory may consist of
physical landscape elements (Tandy, 1971) or design elements
(Bureau of Land Management (BLM), 1980). Implicit in the
quantitative design inventories approach to landscape evaluation is the
assumption that scenic quality of the whole landscape can be explained in terms
of aggregation of the values of the landscape components.
Although these surrogate methods of landscape evaluation can provide
general assessments of landscape quality and a landscape inventory based on
subjectively-selected but objectively-applied criteria, the objectivity of
their application, and their precise, often quantitative, results disguise
their underlying subjectivity (Crofts and Cooke, 1974).
The descriptive inventory approach contains several assumptions. One is
that the value of a landscape can be explained in terms of the values of its
components. Another is that scenic beauty is embedded in the landscape
components, that it is a physical attribute of the landscape; however, scenic
beauty depends on the observer as well as that which is being observed
(Arthur et al., 1977). Descriptive inventories
methods have been criticised for the way landscape components are arbitrarily
identified then subjectively scored by the design professionals, and the lack
of empirical research to justify the inclusion of these components as
determinants of scenic quality (Robinson et al., 1976,
Arthur et al., 1977).
Formal aesthetic models
The basic theory of the formal aesthetic model is that aesthetic values are
inherent in the formal properties of the landscape. These properties are
defined as basic forms, lines, colours and textures and their
interrelationships. The relationships between these elements are then inspected
to classify each area in terms of variety, unity, integrity or other complex
formal characteristics. Due to the formal training required for this, the
method is almost always applied by an expert, usually a landscape architect
(Daniel and Vining, 1983).
Because the landscape-quality assessment results in ordered categories, and
not in cardinal or interval measures, it is difficult to relate these
assessments to economic or trade-off types of valuation processes. Thus,
valuing landscape quality relative to other social values is rather restricted.
The models have been found to be seriously deficient with regard to the
fundamental criteria of sensitivity and reliability (Daniel and
Vining, 1983).
Ecological models
Within the ecological model, the environmental features that are relevant
to landscape quality are primarily biological or ecological. The landscape is
characterised in terms of species of plants and animals present, ecological
zones, successional stage or other indicators of ecological processes. In the
context of such modelling humans are characterised as users of the landscape
(Daniel and Vining, 1983).
Ecological models tend to be designed for specific areas and are therefore
difficult to apply to landscapes in general; they are also more sensitive in
distinguishing between natural and human-influenced environments than in making
distinctions within either of those classes. If the alternatives for land
management are to manipulate or not manipulate the environment, the ecological
models will almost invariably indicate against any manipulation (Daniel and Vining, 1983).
A major underlying assumption of the ecological model is that landscape
quality is directly related to naturalness, or ecosystem integrity. The
validity of this model depends upon the assumption that "natural"
areas undisturbed by humans are highest in landscape quality. Reliability
depends on the consistency and accuracy of the individual applying the method
as the assessments are usually carried out by an "ecological expert"
(Daniel and Vining, 1983).
Examples
An example of a formal aesthetic model is the Visual Management System
(VMS) developed by the USDA Forest Service. It has the purpose of evaluating
scenic resources within a land-management framework and assumes that scenic
quality is directly related to landscape diversity or variety (Daniel and Vining, 1983). VMS uses character classification
(such as gorges, mountains, foothills and plateaus), variety classification
(form, line, colour and texture) and sensitivity level (referring to the
relative importance of the landscape as a visual or recreational resource). In
some cases VMSs are more quantitative holistic techniques that descriptive
inventories.
Leopold's "uniqueness ratio" illustrates a landscape assessment
methodology based primarily on ecological measures of the landscape. The
uniqueness of a given landscape is defined by multiple physical, biological,
and human-use dimensions that reflect the implicit assumption that aesthetic
value is primarily a function of ecological criteria (Daniel and
Vining, 1983).
Cooper and Murray (1992) used local patterns of land
class distribution and land class clusters to divide a region into
geographically distinct landscape units. High-elevation and upland areas were
differentiated from lowlands and unit boundaries were then drawn in relation to
selected physiographic and landform features such as watershed boundaries and
specified juxtapositions of land classes.
In the BLM's (1980) scoring scheme for scenic quality,
landscape features were valued using different criterion. The first was in
terms of the four basic design elements, namely: form, line colour and texture
(R. Kaplan, 1985). High valuations are given to the five
natural landscape components (landform, vegetation, water, colour and adjacent
scenery), whilst cultural modification is assumed to have negative effects. It
is the only component that can receive a negative score. The other criterion is
to value landscape in terms of variety, scarcity, vividness and
distinctiveness. Landscapes with the greatest variety in landform, vegetation,
and colour patterns are given the highest scores.
Brabyn (1996) desribes an automated classification
process which uses a GIS to determine uniqueness and variety. The landscape
character classification process used national digital databases to classify
vegetation, naturalness, water and landforms in an objective manner. The
resultant hierarchical classification, which is based on different levels of
generalisation, enables the classification to cope with the different levels of
perception that people experience. Brabyn (1996) also notes
that a landscape character classification does not identify quality and points
out that such a classification needs to evolve as the understanding of the
nature of landscapes becomes more sophisticated.
Public preference models
The recent upsurge in public interest in preserving the beauty of public
lands has resulted in the development of scenic assessment based on public
input (Arthur et al., 1977), indeed, it can be argued
logically that the best source of data upon such a subjective issue as
landscape quality is the general public. Although planners may claim that it is
their duty to guide public taste in these matters, the visual attractiveness of
the landscape is ultimately a product of the aggregated opinions of all the
individuals concerned with that landscape (Briggs and France,
1980).
The visual quality (or value) of a landscape is rated on the basis of an
observer's individual preference of the whole landscape. Those techniques that
are based on subjective assessments of scenery and attempt to encompass the
diverse and changing perceptions of individuals are likely to be most
successful. The essence of the preference approach is the judgement of the
landscape in totality, as opposed to the measurement techniques, which rely on
the definition of factors to explain variation in landscape quality
(Dunn, 1976).
Questionnaires or verbal surveys are the most commonly used
non-quantitative method for sampling scenic preference of various groups. They
are a valuable source of quick information but accuracy can be sacrificed for
speed. They are useful for determining preferences for extremely divergent
categories of landscape (Arthur et al., 1977).
Alternative to questionnaires, one can provide visual stimuli for evaluation,
such as photographs (e.g.Shuttleworth, 1980a; Wade, 1982) or
one can use other stimuli, such as sound (Anderson et
al., 1983). Although perceptions still vary, the variation is less than
with verbal descriptions.
There are various difficulties when carrying out such evaluations. Past
studies show that the personality of the observer, and their location affect
what they observe, as does the duration of observation, the socio-economic
profile of the observers, the type of physical characteristics of the
landscape, the dynamics of its components and its complexity (Amir and Gidalizon, 1990). Two concerns are noted by
Hull and Stewart (1992) - regarding the ecological validity
of photo-based assessments caused by differences between on-site and
photo-based contexts and that the individual rater, rather than the group
average, is the more appropriate unit of analysis for tests of validity of
photo-based assessments. The techniques have other problems - their
psychological basis is at best uncertain; the validity of their quantitative or
semi-quantitative results is invariably questionable; and in order to be
representative of society's views, they require extensive, time-consuming
surveys (Crofts and Cooke, 1974).
Psychological models
The psychological approach has been used in many studies where dimensional
analyses of people's preferences for different landscapes are performed. These
studies have demonstrated that various psychological constructs such as
complexity, mystery, legibility and coherence are important predictors of human
landscape preferences (Buhyoff et al., 1994). The
psychological model refers to the feelings and perceptions of people who
inhabit, visit, or view the landscape. A high-quality landscape evokes positive
feelings, such as security, relaxation, warmth, cheerfulness or happiness; a
low-quality landscape is associated with stress, fear, insecurity, constraint,
gloom, or other negative feelings (Daniel and Vining, 1983).
Because psychological methods use multiple observers and yield one or more
quantitative scale values for each assessed landscape, their reliability and
sensitivity can be precisely determined. This is an important advantage, since
users of these assessments can know the degree of precision and to prove
confidence in the landscape values produced. The methods base landscape
assessments on the reactions and judgements of the people who experience and/or
use the landscapes. In this regard there is an important element of validity
inherent in the method (Daniel and Vining, 1983).
Without clear relationships to objectively determine environmental
features, the psychological methods leave landscape assessment in a
correlational feedback loop; psychological reactions to the landscape are
explained only in terms of other psychological reactions:-
"From a practical perspective, this leaves the landscape manager with
both feet firmly planted in midair" (Daniel and Vining,
1983).
Phenomenological models
The phenomenological model places even greater emphasis on individual
subjective feelings, expectations, and interpretations. Landscape perception is
conceptualised as an intimate encounter between a person and the environment
(Daniel and Vining, 1983). The principal method of
assessment is the detailed personal interview or verbal questionnaire.
Phenomenological models tend not to be used to rank landscapes in terms of
scenic beauty.
Phenomenological approaches have largely sacrificed reliability in favour
of achieving high levels of sensitivity; by emphasising very particular
personal, experiential and emotional factors, the visual properties of the
landscape become only very tenuously associated with landscape experience. This
model represents the extreme of subjective determination of relevant landscape
features. It fails to establish systematic relationships between psychological
responses and landscape features. However, by emphasising the unique role of
individual experiences, intentions, and expectations, the phenomenological
model serves to point out the importance of the human context in which
landscapes are encountered (Daniel and Vining, 1983).
Consensus
Most landscape techniques proceed on the assumption that there is a broad
consensus within our society upon what is considered to be of high landscape
value. This assumption is linked to another: that "visual quality" is
an intrinsic property of landscape and can be stated objectively (Jacques, 1980). The issue of observer consensus is a major
topic in landscape perception and preference.
Landscape preference studies should not rely exclusively on general
rankings of preference, but should also consider other trends of variation and
eventually compare individual patterns of selection. If only consensus aspects
are examined (e.g. group preference rank), idiosyncratic features remain
ignored. The subjects' variance in the relative evaluation of appraisal
characteristics may have very different origins. It may be related to
sociocultural or psychological factors that affect landscape preference as
described by a number of authors (Abello et al, 1986).
Reasons for the real variation in consensus levels remain elusive. Evidence
suggests little overall correlation between perceived attractiveness and
consensus levels, although the more 'extreme' evaluations rarely attract
majority support. Consensus does not increase with greater familiarity. Indeed
those admitting less knowledge of local landscapes show greater consensus in
their generally cautious and conservative evaluations. Those with the greatest
landscape knowledge are more critical of its various qualities so that their
responses show greater variance. The degree of consensus on evaluation,
therefore, generally declines with increasing landscape familiarity, although
not always sufficiently to be statistically significant given the available
sample sizes (Penning-Rowsell, 1982).
Examples
A series of studies by Kaplan and Kaplan illustrated the psychological
model of landscape assessment. A basic method in these studies is to identify
relevant psychological variables on photographs of landscapes. Preference
ratings and ratings on the landscape dimensions are then obtained from naive
observers (Daniel and Vining, 1983).
The essence of Fines' technique is the classification by field observers of
subjective responses to the attractiveness of views according to a single,
comprehensive and predetermined scale (Crofts and Cooke,
1974). Most literature on phenomenological methods is devoted to studies of
developed landscapes or to perception of environmental hazards. There are only
a few specific studies seeking to assess natural landscapes (Daniel and Vining, 1983).
Quantitative holistic methods
Quantitative holistic methodologies combine two approaches: quantitative
public preference surveys and landscape features inventories. Measures of
landscape quality should be systematically related to physical / biological and
social features of the environment so that accurate predictions of the
implications of environmental change can be made (Arthur et
al., 1977).
Models, such as that of Shafer et al. (1969)
represent a compromise between techniques which assess the effects of landscape
elements on overall preference by summing evaluations of individual dimensions
(descriptive methods) and techniques which emphasise the interactions of
landscape elements by evaluating the scenic quality of the entire image
(preference models); this compromise creates the quantitative holistic models
such as the psychophysical and surrogate component models (Buhyoff and Riesenman, 1979; Arthur et al., 1977).
A prominent feature of this method is the use of a statistical technique
known as multiple regression analysis to establish a mathematical relationship,
between components of the landscape and the scenic preferences of observers.
Weights for landscape components are estimated from preference ratings
collected from the public. The weights, multiplied with a set of measurements
of landscape components, produce an overall scenic quality score for the other
similar landscapes.
These predictive models have tended to be more a tool for research than for
impact assessment. Their orientation is to predict scenic quality based on the
presence of quantifiable landscape attributes (Palmer,
1983). Psychophysical modelling uses measurements of physical landscape
features to predict people's preferences for the overall visual quality of the
landscapes (Daniel and Vining, 1983).
Implicit in the psychophysical approach is the principle that a model of an
observer's perceptive processes need not be complete in all possible respects
in order to obtain meaningful results. Although this assumption is at variance
with the Gestalt school of thought (regarding the sum of parts to make the
whole), it has nevertheless been largely upheld by modern empirical
psychophysical work (McAulay, 1988).
Traditional psychophysical models, while not "classifying"
landscapes, are developed to make predictions of scenic preference or visual
quality from variables which are often selected for their predictive, rather
than "genuine" explanatory ability (Buhyoff et al., 1994).
Surrogate component techniques are based on the identification of physical
landscape components which can be compared with preference ratings. Visual
management systems aim to be able to both predict and explain scenic
preference; their essential purpose is the prediction and assessment of impacts
resulting from potential management alternatives (Bishop and
Hulse, 1994).
Psychophysical models
Psychophysical methods of landscape assessment seek to determine
mathematical relationships between the physical characteristics of the
landscape and the perceptual judgements of human observers (Daniel and Vining, 1983). The relationships of interest are
those between physical features of the environment (e.g. topography,
vegetation, water, etc.) and psychological responses (typically judgements of
preference, aesthetic value or scenic beauty). Landscape features such as land
cover, land use, forest stand structure, and arrangement are measured and then
statistically related to scenic quality judgements. Models such as paired
comparisons, Likert scales, and sorting and ranking scales are a means to
evaluate scenes quantitatively (Arthur et al., 1977);
multiple linear regression has recently been the most commonly used techniques
to determine these relationships (Buhyoff et al.,
1994).
Of all landscape assessments, these methods have been subjected to the most
rigorous and extensive evaluation. They have been shown to be very sensitive to
subtle landscape variations and psychophysical functions have proven very
robust to changes in landscapes and in observers (Daniel and
Vining, 1983). Relying on ordinal or interval scales of measurement,
psychophysical methods have consistently been able to provide different
landscape-quality assessments for landscapes that vary only subtly. However,
they require the full range of scenes to be selected to represent all of the
physical characteristics used as predictors of scenic beauty (Hull and Revell, 1989). They also provide good assessments of
public perceptions of the relative scenic quality differences between
landscapes (Buhyoff et al., 1994) based on the
assumption that the aesthetic judgements of public panels provide an
appropriate measure of landscape quality (Daniel and Vining,
1983).
However, the models can be expensive and time consuming to develop and are
restricted to a particular landscape type and to a specified viewer population
and perspective; in the short term they are not highly efficient (Daniel and Vining, 1983). The very structure of these models
is often a limiting factor in their explanatory value and wide generalisation
(Buhyoff et al., 1994).
Psychophysical assessments are useful in many management contexts -
features such as quantitative precision, objectivity, and a basis in public
perception and judgement are important. The assessments are not based on one
expert's opinion, but reflect a measured consensus among observers
representative of the public that views landscapes and is affected by
management actions (Daniel and Vining, 1983).
Surrogate component models
The basis of component techniques is the identification and measurement of
those physical components of the landscape which are regarded as surrogates of
scenic quality. The individual components are isolated, their identification
and measurement discussed and their combined utility within existing techniques
evaluated. Because component ratings are compared to overall preference ratings
in these models, the contribution of particular components to scenic beauty can
be measured in terms of explained variance (Arthur et
al., 1977).
These components can be assigned to three groups in relation to their
assumed importance in determining scenic quality. The major components comprise
the landscape skeleton as expressed by macro relief (measured by terrain
types), relative relief and water presence (measured by drainage density). To
these can be added the minor but permanent components which are the variations
of the macro forms at smaller scales. They are the overall variations such as
surface texture and ruggedness, particular features such as the irregularity of
two-dimensional outlines and three-dimensional forms, and the singularities
such as isolated features. Finally, there are the transitory components with
regard to the characteristics of water bodies and surface textures
(Crofts, 1975).
Visual Management Systems
Another approach to the evaluation/assessment of visual resources is the
design-based classification/assessment. Visual management systems (VMS) are
straightforward systems that use intuitive constructs and easily observable
physical landscape attributes to arrive at landscape classification decisions.
Because expert, or knowledge-based, computer systems are capable of carrying
out reasoning and analysis functions in narrowly defined subject areas at
proficiency levels approaching that of humane experts, they have
characteristics that can be used to develop not just a method of predicting
visual landscape quality but also a system that explains why certain levels of
quality exist. In fact, the specification of knowledge may well be the most
important contribution of a scenic quality assessment or prediction system
(Buhyoff et al., 1994).
Examples
The prolific work of Shafer and colleagues (Arthur et
al., 1977) is an example of quantitative holistic methodologies. They
have measured areas, perimeters, and tones of the differentiated landscape
zones of photographs and related them to preference rankings using factor
analysis and multiple regression techniques (e.g. Shafer et
al., 1969; Shafer and Tooby, 1973; Brush and Shafer, 1975). Shafer's
studies illustrate a sound and systematic approach to relating components to
preferences (Arthur et al., 1977).
The Scenic Beauty Estimation (SBE) method requires that landscapes be
observed and judges by panels of persons representative of targeted
populations. To develop models using this system, a number of different
landscapes must be assessed and their physical characteristics evaluated
(Daniel and Vining, 1983). This can be done using colour
photographs or slides (Arthur, 1977) or on-site at the
landscapes (Schroeder and Daniel, 1981).
Psychophysical models have been developed for landscape vistas by relating
measured characteristics of the vistas to scaled landscape preference
(Daniel and Vining, 1983). These have often used colour
slides of forest or panoramic views and gained preference ratings using
paired-comparison formats (Buhyoff and Wellman, 1980; Buhyoff
and Riesenmann, 1979).
In Eleftheriadis and Tsalikidis's (1990) model, coastal
landscape quality was expressed in terms of scenic beauty preferences of the
resource users, and these preferences were related to quantitative measures of
land use designations, and of forest stand and site characteristics.
Carls (1974) used the landscape zones of Shafer et al. (1969) together with a people zone, and
low and high development zones to look at the effects of people and man-induced
conditions of preferences for outdoor recreation landscapes.
Task Four illustrates the application of
descriptive inventory techniques to areas around three existing windfarms in
Wales and a proposed site in Scotland.
Methodological problems and error in models
All these types of models are complicated by methodological problems that
can affect interpretation of results. One such problem is whether numerical
ratings of landscape beauty represent people's preferences for the landscapes,
their judgements of scenic beauty of the landscapes, or both. There is
considerable support for the argument that scenic beauty judgements differ from
scenic preferences (Arthur et al., 1977); according
to Jacques (1980) public preferences tend to give a measure
of 'value', 'quality' is discerned through judgement. When asked to indicate
their preference for various landscapes, observers tend to apply criteria for
use of those areas (recreation, residence etc) rather than for inherent beauty
(Arthur et al., 1977).
There are some persistent errors in the evaluation of landscape, as
identified by Hamill (1985). Examples of the following seven
types of error have been found in the literature: incorrect use of numbers
derived from place in a classification; incorrect use of numbers to stand for
words; use of spurious numbers in simple mathematical operations; use of bad
data in complex mathematical and statistical operations; use of data that does
not satisfy requirements of the model; use of numbers to support, derive, or
demonstrate meaningless, spurious or useless concepts; and use of concepts
without adequate operational definitions.
Economics of landscape evaluation
How do preference values determined from models relate to economic values
of the same landscapes? Results of an exploratory study (Brush
and Shafer, 1975) suggest that a consumer's evaluation of real estate that
overlooks a given natural scene correlates highly with the scene's predicted
preference scores. It should be possible to develop an equation that ties
scenic preference values to economic land values. The results of such research
should be useful in benefit-cost and environmental impact analyses of the
effect of proposed man-made changes in natural environments.
Traditional economic analyses have generally failed to account for
unmarketed (nonpecuniary) resources, such as aesthetics. The effect of
excluding nonpecuniaries from trade-off (economic) decisions is that they have
entered the system as if they were free. Recognition of this problem has, in
part, motivated attempts to evaluate scenic resources. If applied to aesthetic
resources, redefinition would require putting a price on scenic beauty or
charging for its "use". However, putting a price on aesthetic
resources is probably not feasible for several reasons. First, aesthetic
experiences are difficult to define, second, there is the problem of placing
charges on aesthetic experiences (Arthur et
al.,1977).
Methods of scenic resource financial valuation
Several methods have been used to obtain values for scenic resources.
"Willingness-to-pay" values (how much will a commuter pay to preserve
the trees), revealed demand (does he take a different highway?) and opinion
tallies (does he complain to his MP?) are only a few of the methods used
(Arthur et al., 1977). Opinion tallies, often result
in undervaluation. Revealed demand is complicated by the necessity of
identifying all of the variables acting on the situation.
The hedonic price method (HPM) is a less subjective way of scoring
landscape components; components of landscape are valued against people's
willingness to pay to live in particular types of landscape, defined as
comprising of different bundles of components (Willis and Garod,
1993). HPM is a process of constrained maximisation in which systems of
equations involving both prices and quantities for the composite commodity and
its attributes are constructed and then solved (Price,
1994).
The travel cost method (TCM) uses a sample of visitors to a site which
embodies desired environmental attributes and asks them factual questions about
the origin of their journey to the site, their mode of transport and perhaps
about other costs incurred and their own socio-demographic characteristics
(Bergin and Price, 1994).
Contingent Valuation Technique and Willingness-to-Pay
Contingent valuation techniques (CVT) in landscape evaluation are seen as a
natural evolution from landscape evaluation methods based on the scoring of
landscape components and other public preference techniques such as landscape
ranking. By valuing landscape as an entity, CVT avoids many of the problems,
such as those of separability and collinearity, often associated with travel
cost and hedonic price methods of landscape valuation (Willis
and Garrod, 1993).
Willingness-to-pay (WTP) studies can assist in valuing today's landscape,
they also attempt to value the benefits which residents and visitors might
derive from alternative landscapes which could arise at some time in the future
(Willis and Garrod, 1993).
WTP's linearity means that it is a linear or other predetermined function
of the quantity of the feature in the landscape. However, evidence suggests
that the impact of a landscape feature does not increase in proportion to its
size (Willis and Garrod, 1993). Unfortunately, WTP values
are often too high (Arthur et al., 1977) and WTP to
gain a commodity is generally less than willingness to accept compensation for
losing it (Price, 1994).
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