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FINDINGS OF INTERNATIONAL LANDSCAPE STUDIES

The findings of surveys were assessed under four broad headings:

THEORY OF LANDSCAPE QUALITY

Fundamental to developing the science of scenery is a hypothesis, a model or, ideally, a theory of landscape preferences, for which data are sought to test and hopefully provide validation. To date, however, a comprehensive theory of scenic quality is lacking.

A more extensive review of landscape theory is available here.

Ever since Porteous’s pithy comment that the landscape field has been “rampantly empirical” (1982), considerable effort has been expended in attempts to develop a comprehensive theory of landscape aesthetics.

The current theories of landscape quality, which seek to explain why we like what we like rather than simply describing what we like, all derive from an evolutionary perspective which argues that landscape preferences are survival enhancing: human preferences have been moulded by what enhances our capacity to survive as a species.

Following are the current theories of landscape preferences:

  • Prospect – refuge theory (Appleton)
  • Affective theory (Urlich)
  • Habitat theory (Orians)
  • Information processing theory (Kaplan and Kaplan)

Current landscape theories

In Jay Appleton’s (1975) prospect-refuge theory, landscapes are preferred which enabled one to see without being seen; they provided places (prospects) where one could spy out game, the enemy or other objects, while also providing places (refuges) in which to hide. Testing of these ideas empirically has provided some support (Woodcock, 1982, Nasar et al, 1983; Herzog, 1984, 1985; Herzog & Smith, 1988) but other contributing factors have also been identified.  While prospects tended to correspond with the appeal of mountains and trees, refuges (e.g. caves) tend to be regarded negatively. Males tended to prefer wide open spaces (prospects) but females prefer safe vantage points (refuges).

In Roger Urlich’s (1981, 1983, 1991, 1993) affective theory, natural settings and landscapes produce emotional states of well-being in their viewers. Measured on a like-dislike dichotomy, these states correlated closely with scales such as beautiful – ugly or scenic quality scales.  A disciple of Zajonc’s (1980) view that preference is pre-cognitive, Urlich provided supporting evidence from his studies.

Using various physiological measures of brain activity and of feelings, Urlich found that urban scenes without trees or natural objects produced negative feelings while scenes of nature provided positive feelings and that these produced physiological benefits. In a study of hospital patients, for example, he found that those patients with a view of trees recovered more quickly and required fewer analgesics than those without this view (Urlich, 1984). Other researchers have extended Urlich’s work to the restorative effects of nature (Hartig, et al, 1991; Parsons, 1991).

Gordon Orians, an evolutionary biologist, proposed habitat theory with the biological imperative for humans to “explore and settle in environments likely to afford the necessities of life …” (Orians & Heerwagen, 1992). Taking the African savanna which contains scattered Acacia trees amongst extensive grassland, believed to be the environment in which humans evolved, Orians argued that there would be a strong preference for this type of environment. Using the characteristic shape of the Acacia trees he found strong preferences for these trees. Similar pastoral environments of trees and grass are found in our public parks comprising extensive lawns and isolated trees, even our own backyards and gardens and are a favourite subject of artists. The ubiquity of this form reinforces Orians’ case.

The overarching theory of environmental perception is information processing theory which has been applied in the field of landscape aesthetics by Stephen and Rachel Kaplan (1989). This involves cognitive processes, in contrast to Urlich’s pre-cognitive. The Kaplans suggested that in extracting information from the environment, humans sought to make sense of the environment and to be involved in it. They identified four predictor variables: coherence and legibility which help one understand the environment, and complexity and mystery which encouraged its exploration (Figure 1).

UNDERSTANDING

Making sense

EXPLORATION

Being involved

IMMEDIATE
The visual array
COHERENCE
Making sense nowOrderly, "hangs together"Repeated elements, regions
COMPLEXITY
Being involved immediatelyRichness, intricateMany different elements
INFERRED
Future, promised, three-dimensional space
LEGIBILITY
Expectation of making sense in futureFinding one's way there and backDistinctiveness
MYSTERY
Expectation of future involvementPromise of new but related information

Source:  Kaplan, 1979, Kaplan, Kaplan and Brown, 1989.
Figure 1 Kaplans’ Predictor Variables

Coherence and complexity involve minimal analysis and are registered immediately while legibility and mystery require more time and thought. Research of these has found that coherence is the strongest predictor and mystery is the most consistent.

Studies of the Kaplans’ information processing model provide support for its elements (Herzog, 1984, 1985, 1987; Herzog & Smith, 1988; Herzog & Bosley, 1992; Stamps, 2004). A considerable degree of interpretation is, however, required in order to apply these four predictor variables in the landscapes studied (e.g. the study of the Upper Yarra Valley and Dandenong Ranges by Brown, Itami and King, 1979).

Although these theories provide glimpses into the basis of human landscape preferences, further development is required. A robust theory which provides an all encompassing framework with which to understand and to predict landscape preferences from a macro to micro level covering all types of landscapes does not yet exist. A range of theoretical models are available which offer explanations of aspects of landscape preferences but which fall well short of a comprehensive and definitive explanation.

Where to now?

While the long term aim should be to assist in the development and testing of theories that will accurately and comprehensive explain and predict human landscape preferences, the aim for most investigators will be more immediate; that of measuring and in some cases, mapping landscape quality for a given area. Providing the methods used are compatible, over time such studies should generate a large body of assessments which will increase current knowledge and understanding of landscape quality. This in turn may assist in the development and testing of theories in the future.

INFLUENCE OF OBSERVER ON LANDSCAPE PREFERENCES

Introduction

Landscape preferences are the product of “what’s out there” with “what’s in here”, the observable, objective fact of the physical landscape as perceived and interpreted by the eyes and mind of the viewer. That which is “behind our eyes” is as important as that which in front of our eyes.

In this section, the influence of observer characteristics upon preferences is examined to identify the important factors and to gauge their relative importance.

I have reported elsewhere about the characteristics of the surveys which assessed the participants. The key findings were:

  • Tertiary students dominated, accounting for 41% of participants, sometimes with other participants, but in 28% of surveys, students only were used
  • Members of the general community were 23% of survey participants while visitors to parks or sites being investigated were a further 11%. Other participants included natural resource professionals [8%], design professionals [4.5%], university staff [4.5%] landowners and residents [3%] and children [2%]
  • Only 37% of surveys sought data about the characteristics of their participants, a surprisingly low figure but partly explainable by the high proportion of students.
  • Age, sex, education, employment and socio-economic status were the main details sought [total 75%]. Other details were childhood residence, culture & ethnicity, expert & non-expert, and race.

Respondent Characteristics 

This section examines the influence of respondent characteristics [i.e. age, gender, education, employment and socio-economic status] on their landscape preferences.

Zube et al [1983] examined the changes to landscape preferences over the lifespan, covering children, adults and elderly subjects. Figure 2 correlates scenic value ratings with the six age groups. It shows that young children [6 - 8 years] correlate reasonably well with the older children [9 - 11 years] but much less with teenagers [12 - 18 years]. Better correlations with adults are achieved by older children [9 - 11 years] while those of teenagers are virtually identical with adults. The correlations with the older adults [over 65] also varied significantly from those with other adults.

Age and preferences

Source: Zube, Pitt & Evans, 1983
Figure2  Correlations for Scenic Preference by Age Group

Most of the surveys that covered one or more of respondent characteristics did not use these in their analysis of preferences. Only 12 [5% of total] compared the results with some or all of these characteristics. The main reason for collecting this data was to assess whether the sample was representative of the population.

Of the five basic characteristics, only age and to a lesser extent, gender exhibited an influence on preferences. The evidence is conflicting; eight of the 12 studies found age had no effect while four studies detected some:

  • Respondents aged over 25 were more critical of artificial changes to the landscape and more appreciative of natural elements [Banarjee, 1977]
  • Preferences weakly related to age [Penning-Rowsell, 1982; Cherem & Driver, 1983]

Only Zube et al’s findings could be regarded as definitive - that the preferences of young children, particularly the 6 - 8 year olds group, differ substantially from older children and from adults. This reinforced the finding by Balling & Falk [1982] and Lyons [1983] that the preferences for savanna by children aged 8 - 11 years differed significantly from older children and adults.

Regarding gender, only two studies found it influenced preferences, which is too limited to be definitive:

  • Males were more likely to view the ground, topography & ephemeral objects [Hull & Stewart, 1995]
  • Females were more sensitive to lack of cover & to differences in mystery in savanna [Woodcock, 1982]

Overall, the basic respondent characteristics of age, sex, education, employment and socio-economic status appeared to have a nil or negligible influence on preferences. Some indications exist that the preferences of young children [< 11 years] differ significantly from older children and adults.

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Children

Preferences of young children [6 - 11 years] differ from adults and older adults [> 65 years] differ from other adults [Zube, Pitt & Evans, 1983] Differences in the landscape preferences of children and adults can indicate the influence of acculturation [socialisation] on these preferences and the extent to which preferences are inherent or are learnt.

While Balling and Falk [1982] regarded the high preferences of young children [8 - 11 years old] to be indicative of inherent preferences with an evolutionary origin, Lyons [1983] suggested that this could be explained by familiarity with similar environments in parks and backyards.

Bernaldez et al, [1987] examined the landscape preferences of children on the Canary Islands. Two age groups were used; 11 and 16 years old. Pairs of photographs were used and the children asked to indicate their preference. Factor analysis identified three dimensions:

  • illumination: clear, illuminated scenes rich in detail illuminated vs gloomy, shadowed scenes with less detail
  • diversity: diverse, contrasted, varied scenes vs more monotonous landscapes
  • harshness: rough scenes with edges and aggressive forms vs bland, smooth surfaces

Younger children differed from the older children:

  • they disliked darker scenes with less detail [factor 1] [t = 4.09, p < 0.01]
  • they disliked harshness in scenes [factor 3] [t = 2.92, p < 0.01]

Younger children’s preferences for diverse scenes [factor 2] were similar. Interpreting the results, Bernaldez, et al, considered that factors 1 and 3 were forms of a more general “risk, uncertainty factor” [Ibid, 173] that played an important role in landscape preferences. They linked this with Appleton’s notions of prospect and refuge. While the darkness and deep shadow in factor 1 scenes had links with Kaplan’s mystery factor, there was a point at which risk and uncertainty shifted from exciting and stimulating to fear and frightening. Fear of darkness, the authors noted, was common among children. The shift in the 11 and 16 years olds on this factor indicated the older children were less influenced by this fear and were more inclined to find it stimulating.

Zube et al, [1983] carried out a lifespan analysis, examining how landscape preferences changed over age groups. The ages ranged from 6 years to over 70 years. The study found that children rated landscapes differently from adults.

Figure 3 summarises the correlations of each age group’s scenic ratings with selected landscape dimensions. The 6 - 8 age group and, to a slightly lesser extent the 9 to 11 age group, had markedly different preferences to adults. This indicated that naturalism and strong physical relief were relatively unimportant to children but water was particularly important.

 age & ls dimensions

Source: Zube, Pitt & Evans, 1983
Figure 3 Correlations with Age Group Scenic Ratings

The few studies that have included children indicated that their landscape preferences differed significantly from adults. However there are insufficient studies at present to be definitive.

Personality

Spanish researchers have examined the influence of personality on preferences. The research design involved use of paired photographs of scenes together with a personality test to identify personality types. Factor analysis was used to identify the differences. Maciá [1979] separated the results for male and female. For men, he found:

  • Men with mature mature personalities who dealt with reality preferred humanised landscapes [r = 0.427, p < 0.01]
  • Men who scored high in emotional control preferred pleasant landscapes [r = 0.543, p < 0.01], extroverted men preferred landscapes with diffuse forms and rounded trees [p = 0.236, p < 0.05]

For women, Maciá found:

  • Women with a sensitive, insecure personality preferred natural, unaltered landscapes [r = 0.228, p < 0.01]
  • Women with astute, worldly personalities preferred dry, cold landscapes [r = 0.233, p < 0.01]
  • Extroverted women preferred landscapes with diffuse forms and rounded trees [p = 0.183, p < 0.05]

Maciá concluded that personality structure conditioned landscape choice, and gender could influence preference, either directly or be influenced by personality factors. Abello & Bernaldez [1986] found that the common group had no relationship with personality types, however individuals having low emotional stability preferred landscapes exhibiting “recurrent patterns” and “structural rhythms” [Table 2].

Table 2 Influence of Personality on Landscape Preferences [correlations]

  Factors
Personality factor  1 2 3
Common traits 0.02 0.08  
Emotional stability - 0.02 - 0.18** - 0.08
Responsibility - 0.09 - 0.08 - 0.17**

Notes: Factor 1 - fertility, vigour, exuberance
Factor 2 - recurrent patterns & rhythms
Factor 3 - defoliation (structural legibility assoc. with hostility). Significance: ** p = 0.05

The authors commented:

“Apparently, such individuals try to compensate their lack of stability with extreme preference for environmental regularity and prevision.” [Ibid, 24]

The strongest relationship of the “sense of responsibility” dimension of personality was with factor 3 and was negative. This indicates that these respondents “reject hostile, cold, wintry scenes with defoliated vegetation, although the same scenes are more legible and generally appreciated” [op cit].

The Spanish studies provide tantalising indications of the influence of personality upon landscape preferences. It is to be hoped that their work will be replicated in other cultures.

Culture

Surprisingly studies have found culture to have a negligible effect on landscape attitudes. This section examines these studies.

Buhyoff et al, [1983] examined the preferences of participants from the US, the Netherlands, Sweden and Denmark for slides of the Rockies and Appalachians. Correlations were highest between the Danish and Dutch and between the American and Swedish [Table 4].

Table 4   Correlation [Pearson] matrix

 

Netherlands

Sweden

United States

Denmark
0.84*
0.755*
0.727**
Netherlands
0.586***
0.550***
Sweden
0.890*

* p > 0.01; ** p > 0.05; *** p > 0.10

In a finding which may reflect familiarity, Buhyoff et al noted the:

“Danes and Dutch prefer flat and open landscapes, whereas Americans and Swedes show a higher appreciation of forested and mountainous scenes.”

Hull and Revell [1989] found that the level of agreement regarding the scenic beauty of Bali among the Western tourists was significantly higher [0.86] than among the Balinese [0.79] which was surprising given that the tourists came from many countries.. Hull and Revell considered that the Balinese who had been exposed to Western culture for decades might have adopted western values. Nevertheless they considered that the only moderate level of agreement on scenic beauty [F = 1671, df = 2, 777, p < 0.001] suggested that substantial differences existed between cultures; the Balinese preferred scenes with traditional architecture [t = 2.89, df = 48, p < 0.01] while the tourists preferred scenes with people and scenes of wide, lush green tropical rice-field landscapes [t = 2.06, df = 48, p < 0.045].

Certain mountains, trees, agricultural scenes or views towards or away from ‘evil’ or ‘good’ would influence the Balinese ratings, yet these meanings would be unavailable to tourists. The authors suggested: “meaning influences aesthetic evaluations of environments. Hence, to some extent, scenic beauty is learned.”

Overall however, Hull & Revell concluded that despite the “enormous differences which exist between the Balinese and western culture” [Ibid, 189] “the results suggest that there was perhaps more similarity than difference between the two groups in their scenic evaluations” of the Balinese landscape.

Based on the study by Purcell et al [1994], Figure 4 compares the responses by Italian and Australian students to photographs of landscapes from both countries. Preferences for natural vistas were generally higher amongst the Italian participants than amongst the Australian participants but the differences were only slight.

Purcell

Source: Purcell et al, 1994
Figure 4 Comparison of Italian and Australian Landscape Preferences

Sonnenfeld [1967, 1969] studied environmental perception of Eskimos and Americans in Alaska and compared their responses with a control population in Delaware. He was interested in the levels of adaptation to the harsh Arctic environment by differing groups. He found that current and past environmental experience had a major influence on environmental attitudes and perceptions. Preferences for landscapes reflected not only what is attractive but also what was deficient in the home environment [e.g. a lack of fuel in the home environment increased the preference of Eskimos for trees].

Commenting on Sonnenfeld’s studies, Zube & Pitt [1981] considered that the differences found between Australian, Scottish and American cultures [Zube & Mills, 1976, Shafer & Tooby, 1973] were not as great as between the Alaskan native and non-native populations that Sonnenfeld had studied.

Figure 5 indicates the preference values of Asian respondents obtained by Tips & Savasdisara [1986a], using the LCJ method. It indicates, with some exceptions, a reasonable degree of similarity across different nationalities. Note for example, # 9 [which gained first preference rating of 100 for all but one group - Bangladeshi] and # 4 [which was ranked among the lowest scores in most cases]. The standard deviations, a measure of consensus, ranged from 2 [# 9] to nearly 23 [# 7] and averaged 12.4. The correlations of nationalities with Western tourists indicated that, apart from the Bangladeshies and to a lesser extent the Nepalese, the responses were comparable with those of Western tourists.

Tips

Source: Tips & Savasdisara, 1986a
Figure 5 LCJ Preference Values for 11 Landscapes

A study that examined a Third World culture’s view of landscapes was conducted by Chokor and Mene [1992] in Nigeria. The study was unique in being the only landscape study in Africa and one of the few in a Third World country. The study used 15 colour photographs of urban, rural and natural scenes in and around the city of Warri, which is the hub of the country’s oil industry with petroleum, refinery, steel and other industries. Warri is located in flat, marshy terrain surrounded by traditional farming and fishing communities. The photographs were judged by four groups; the poor and uneducated and the rich and educated in both rural and urban areas. Figure 6 shows the ratings for each landscape. The highest ranks were for natural landscapes followed by rural landscapes - a result not dissimilar to Western studies.

Nigerians

Source: Choker & Mene, 1992
Figure 6 Preference Ratings of Nigerians

The rankings of urban landscapes varied widely with both the best and worst scenes as judged by the Nigerians.  Average scores overall [lower the better] were: urban 8.3, rural 8.8, natural 7.5. Comparing the responses of the four sample groups, Choker & Mene found the rural people preferred urban landscapes while urbanites “overwhelmingly favoured nature scenes over rural and urban scenes.". Perhaps, like Westerners, Nigerian urbanites enjoy a contrast to their home environment.

Overall, these studies indicate that the influence of culture is not as great as might be expected. Acculturation with Western values may be a partial explanation, but is not adequate. For example, Zube and Pitt found to their surprise a very low correlation by a small subgroup of black city-centre residents in Hartford, Connecticut, a group that one would expect to be well acculturated.

I am uneasy about the use of photographs from the United States in testing the preferences of other cultures [e.g. Shafer & Tooby, 1967; Tips & Savasdisara, 1986a]. Kaplan & Herbert, 1987, found that American students viewed the scenes of Western Australian forests as “foreign” and the opposite may apply to viewing of American scenes by other cultures. The use of scenes from another country introduces problems of unfamiliarity, of possibly associating the scene with tourist travel literature, even of linking with aspirations among Third World cultures to live in the United States. To their credit, Purcell et al, 1994, used photographs from both countries in testing the preferences of Italians and Australians. Another option would be to use scenes from a third country, unrelated to either.

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Familiarity

All the wide world is beautiful, and it matters little where we are...
The spot where we chance to be always seems the best. John Muir, 1890

Writing about the ongoing change to the British landscape, I.G. Simmons wrote perceptively in 1965 that there was no “right landscape, only a familiar one." In their seminal paper on English Landscape Tastes, Lowenthal and Prince [1965] identified rejection of the present as one of the characteristics of English preferences - a delight in the history of the landscape and a preference for the familiar.

The British have a particular fascination with the immutability of their landscape, esteeming its beauty and expressing grave concerns about changes brought about by modern agricultural practices, such as the removal of hedgerows which add considerable diversity to the scene. Articles have abounded with titles such as: “Changes in the English landscape” [Jackson, 1964], “The British landscape is losing its character” [Lovejoy, 1968], “The future of the British countryside” [Green, 1975], “The farming landscapes of England and Wales: a changing scene” [Leonard & Cobham, 1977] and “Shroud for the Scottish landscape” [McCluskey, 1986].

The strength of attachment that the English have to their landscape illustrates the important role of familiarity in influencing landscape preferences. While “familiarity breeds contempt” in many situations, landscapes appear to be an exception. Familiarity transforms a mediocre landscape into a scene that is loved and cherished by those who have grown to experience it.

Dearden [1984] examined the influence of several factors including familiarity on landscape preferences [Figure 7]. He found that respondents who lived in more natural, low-density housing for most of their adult lives feel more positively about rural and natural scenes than residents from high-density housing.

Familiarity

Source: Dearden, 1984
Figure 7 Correlations of Familiarity with Socio-Economic Variables

Only three of the correlations were significant:

  • Housing density occupied as adults correlates with rural and wilderness preferences
  • Housing density occupied over last 5 years correlates with rural preferences
  • The lower the density of housing environment, the higher the relative scores for less developed landscapes

Dearden suggested that housing density occupied as adults is a good predictor of familiarity. No significant relationships were apparent between city size and landscape preference.

Factors perceived by respondents to be important in influencing landscape preferences included past landscape experience, travel, present residential environment and recreational activities. These were the first four ranks out of 11 options and support the influence of familiarity on preferences.

Dearden considered familiarity with landscape types to be a persuasive influence [Ibid, 304]. He contrasted this with the finding of Wellman & Buhyoff [1980] of no regional familiarity effect and suggested the viability of generic landscape preference models.

Hammitt [1979] asked some visitors to a bog environment [i.e. wetlands] in a Virginian National Forest to rate photographs of the site prior to their visit and again following the visit. Other visitors were only asked following the visit. Preference was rated on a 5-point scale and familiarity was rated on the visitor’s recall of having seen the scene using a 3-point scale [familiar, not familiar, not sure]. Information on prior visits to the site was also obtained [Figure 8].

Hammitt

Source: Hammitt, 1979; units are notional.
Figure 8  Preferences vs. familiarity - Bog environment

Hammitt found that the ratings of scenes were virtually identical [rho = 0.97] and prior visits appeared also to have virtually no effect with only one photograph showing significant difference [chi test]. Hammitt considered that “a single on-site experience is sufficient for developing a sense of familiarity.".

Comparison of preference and familiarity indicated a positive relationship [rho = 0.53] with the majority of scenes being strongly correlated. Hammitt considered that scenes high in ‘distinctiveness’ and ‘involvement’ were more familiar than featureless scenes offering little appeal for visual involvement. He also found that high familiarity with low preference could also occur and that therefore “familiarity, per se, is [an] insufficient basis for appreciation.”

Although Hammitt did not derive a regression line for his data, the equation for the data in Figure 8 is y = 0.53x + 21.2, r2 = 0.28. Scenes of low familiarity have a wider scatter of preferences than familiar scenes. (Deletion of the four outlier data points in or near the high preference/low familiarity quadrant and the high familiarity/low preference quadrant yields an equation of y = 0.87+7.84, with a much improved r2 of 0.82. This suggests a much closer relationship between familiarity and preference than indicated by Hammitt. However the deletion of these data points cannot be justified as if they were incorrect.)

Lyons [1983] asked respondents to indicate their preferences for six biomes and examined their changes with age. Figure 9 summarises the findings. Adults top preferences were for coniferous and deciduous forests. Lyons considered the findings “support the hypothesis that a person’s landscape preference is strongly influenced by his or her residential experience in different biomes.” While Balling and Falk (1982) attributed the savanna preferences of children to habitat theory, Lyons considered it was more likely to be due to the familiarity of children to savanna-like parks and backyards.

Lyons

Figure 9 Preferences for Biomes by Age

Nieman [1980] examined the landscape preferences of residents near the Long Island coast and the Great Lakes shore and found that the residents strongly preferred the environment with which they were most familiar [Figure 10]. Similar results were found when respondents were asked which coastal area they would most prefer to live - in both cases, 82% preferred to live where they were rather than in the other location.

Nieman

Source: Nieman, 1980; n=981, c = 59.278, df = 2, p<.01
Figure 10   Preferences vs. familiarity: Great Lakes and Long Island       

Strumse [1996] assessed the landscape preferences of students for Western Norwegian agrarian landscapes. Contrary to her expectations, she found that the two familiarity variables, geographical region during childhood and population density during childhood, had an insignificant influence on preferences. For example, she found that the preference of students who lived in Western Norway during childhood was 3.62 compared with 3.64 for those who grew up elsewhere [5 point scale]. Similarly, the preference of those who grew up in urban areas was 3.66 compared with 3.60 from rural backgrounds.

Those living in Western Norway had moderate preferences [mean 3.56], for western Norwegian agrarian landscapes, while those from other regions had higher preferences [mean 3.83] for the area. However, those living in rural areas had a higher preference for farming landscapes [mean 3.87] than urban residents [mean 3.52]. Overall, Strumse concluded that, while childhood residence and population density did not affect preferences, the respondent’s present location did have an influence.

Wellman and Buhyoff [1980] sought to examine the extent to which regional familiarity affected landscape preferences. Students in Virginia and Utah were shown slides of the Rocky Mountains and Appalachian Mountains. Information about their residency was obtained. The experimental group was told they would be evaluating a mixture of Eastern and Western [i.e. in the US] slides while the other group were given no information about the origin of the scenes [control group].

The study produced three findings [Table 5]:

  • prior information about the scenes made no difference to their ranking of photographs
  • there was no inherent preference for either region
  • subject’s evaluated landscapes similarly regardless of the familiarity with the region

Table 5 Comparison of Preferences between Groups

Question

Spearman’s Rho

Pearson’s  r

1. Utah control vs Utah experimental
0.69
0.78
2. Virginia control vs Virginia experimental
0.85
0.93
3. All Utah vs all Virginia
0.92
0.90
Note: p < 0.05
   

Based on these findings, the authors concluded that inherent familiarity did not appear to be present. They found that “subjects from widely different geographic regions evaluated the landscapes, in terms of preference, in essentially the same manner.”

Despite this, the studies reviewed indicate that, on the whole, familiarity had a significant influence on landscape preferences and this was usually a positive influence. Among the findings were:

  • Housing density occupied as adults appeared to be a good predictor of familiarity [Dearden, 1984]
  • A general familiarity with landscape types tended to be a persuasive influence [Dearden, 1984]
  • A single on-site experience was sufficient for developing a sense of familiarity [Hammitt, 1979]
  • Scenes high in ‘distinctiveness’ and ‘involvement’ were more familiar than featureless scenes offering little appeal for visual involvement [Hammitt, 1979]
  • High familiarity with low preference occurred - familiarity of itself was an insufficient basis for appreciation. [Hammitt, 1979]
  • Scenes of low familiarity produced a wider range of preferences than when the scene was very familiar [based on Hammitt, 1979]
  • Landscape preference was strongly influenced by his or her residential experience in different biomes [Lyons, 1983]
  • Strong preference for the environment with which the respondents were most familiar [Nieman, 1980]
  • While childhood residence and population density did not affect preferences, the respondent’s present location did have an influence [Strumse, 1996]

Some studies found familiarity had little or negligible effect on landscape preferences (e.g. Cook & Cable [1995] and Wellman & Buhyoff [1980]). Penning-Rowsell [1982] asserted that familiarity appeared to result in greater criticism of the landscape qualities and that consensus in fact appeared to decline with familiarity. An instance where familiarity had a negative effect was reported by Kaplan & Herbert  [1987], who found that pines tended to be regarded negatively among Australian students, whereas the opposite occurred in North America [Lyons, 1983].

Summarising, it appears that, if the respondents do not normally regard the scene positively, familiarity will not alter this basic perception but, however where the scene elicits a positive response, this will be reinforced and even increased by its familiarity.

Expert vs. Lay

In an early seminal study, Fines [1968] initially used respondents with no design training, but then rejected their ratings in preference to a smaller group with considerable training and experience. His justification of this was twofold: firstly, “such people [i.e. those with training] are most likely to seek and to obtain the greatest enjoyment from landscape” and secondly, the majority may some day aspire to similar values - a justification which appears quaint and elitist by today’s standards. However, the assumption underlying Fine’s approach was that the landscape ratings of the majority would differ from that of the trained minority. Does the evidence support his assumption?

Anderson [1978] examined the preferences of samples of the community, students and natural resource managers in regard to the Michigan landscape. Figure 11 summarises the preferences of each group and indicates considerable variation. The study divided residents and students by race [black and white] and analysed the differences further.

 Anderson

Source: Anderson, E., 1978
Figure 11 Landscape Preferences by Groups

Anderson concluded that the preference ratings of professionals were distinctly different from those of students and residents:

“They tended to prefer scenes of heavy manipulation such as clearcuts, recently cutover areas and poorly stocked areas, dense forest stands, either managed or unmanaged, and open unused lands. Professionals showed less variation in their ratings. The other two groups expressed much greater sensitivity to the range of scenes.”

Buhyoff undertook a series of experiments involving foresters and non-foresters assessing the impact of beetle damage on forests. However, because the focus of these studies was on the perception of damage rather than landscape aesthetics, they are not included here. Some studies that examined the difference between expert and non-expert participants focused on issues other than landscape quality [e.g. Kaplan & Herbert’s study of Western Australian natural settings included an expert group from the wildflower society].

Buhyoff et al [1978] assessed the ability of trained landscape architects to reproduce the preferences of their client group. They found that, given general information on what the clients like and don’t like about the scenes, they could “come close” [Ibid, 259] to their client’s rank orderings. Their own personal preferences were found to be quite “unrelated to other person’s preferences.".

Vodak et al, [1985] found that scenic beauty ratings by students who were uninformed about forest harvesting techniques were similar to those of forest landowners: r = 0.93. The correlation was even higher with students who were informed about harvesting methods: r =  0.949. The authors concluded that the result “lends further validation to the use of student panels in landscape aesthetics research.”

Zube [1973] used widely differing groups to evaluate photographs of landscapes - the groups included environmental designers, resource managers, environmental technicians, students, housewives and teachers, and secretaries. The first four groups were essentially all male, the latter three mainly [>90%] female. He found close correlations amongst the six groups - r2 averaged 0.74 [p < 0.01]. Zube commented that the data indicated that:

“agreement tends to be strongest on the evaluation of the highest and lowest qualities - the most scenic and the least scenic - within a group of landscapes. Polar positions are apparently more easily identified on a continuum of scenic landscape values even when the comparison is limited to everyday rural landscape. The innumerable shades of gray that lie between the two poles are much less sharply defined. It is also probable that the wider the range of alternatives being evaluated, the larger the gray area is likely to be.”

Based on his findings, Zube suggested that qualitative scenic judgements be limited to three levels - high-medium-low, as more than this may imply a “degree of visual discrimination” that is probably rare.

Resulting from these studies, the similarities between lay and expert observers appeared to outweigh the differences. Similar ratings or preferences were found across a wide range of groups, including foresters & city dwellers [Kellomaki & Savolainen, 1984], students, natural resource managers, river users, and university staff [Mosely, 1989], planners, farmers, residents [Sullivan, 1994], landowners & students [Vodak, et al, 1985] and environment professionals, wives & teachers, and secretaries [Zube, 1973].

Paradoxically the one professional group whose preferences appear to differ from that of the community was landscape architects. More surveys found that their preferences differed [Anderson & Schroeder, 1983; Brown, 1985; Buhyoff et al, 1978; Miller, 1984] than studies that found similarities [Craik, 1972, and Schomaker, 1978]. Thus, while the preferences of natural resource managers generally corresponded reasonably well with those of the community, the views of landscape architects appeared to be at significant variance to the community.

Reliability over time

The reliability of observer responses has been assessed by examining the extent to which they change over time. Coughlin and Goldstein [1970] examined the consistency of ratings one month after the initial rating. They found a reasonably good correlation of 0.73 between the two ratings.  Hull & Buhyoff [1984] reassessed preferences after the elapse of more than twelve months. Individual observer reliability averaged nearly 80% while group consensus values were very reliable [r = 0.956, p < 0.05]. The authors recommended that group data be used in preference to individual responses.

Influence on Preferences of   Observer Characteristics - Conclusions

This section has examined whether preferences are related to observer characteristics. Summarising its findings:

  • The basic respondent characteristics of age, gender, education, employment and socio-economic status generally have a nil or negligible influence on landscape preferences.
  • The sole exception to the above is that there are indications that the preferences of young children [<11 years] differ significantly from older children and adults, however the number of studies are insufficient to be definitive.
  • There is some evidence that personality structure type can influence the choice of landscapes and preferences but again the evidence is confined to a few studies.
  • The studies on the influence of culture on preferences have found that culture has a relatively slight influence and the commonalities across cultures appear to be greater than the differences.
  • Familiarity with landscape is one of the stronger factors and usually has a positive influence, but some studies have found the opposite. Interpreting this it appears that, if the scene is not normally positively regarded, familiarity will not alter this, whilst where a scene elicits a positive response, this will be reinforced and even increased by familiarity.
  • Like the influence of culture, the similarities between lay and expert observers appear to outweigh the differences, and similar ratings of preferences were found across a wide range of groups.

Overall, landscape preferences appeared to be surprisingly consistent across respondent characteristics of age, gender, education, socio-economic status, culture, and whether expert or a lay observer. Two possible exceptions to this are young children [< 11 years], whose preferences differ from older children and adults, and the influence of familiarity with a given landscape. Generally, familiarity contributes to positive preferences, if the scene is normally regarded positively.

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MODE OF PRESENTATION

Photographs

Nearly 90% of studies used photographs to represent the landscape in the surveys of preferences. Most of these [79%] were colour photographs. How adequately do photographs represent landscapes?

Differences between an actual field observation and a photographic representation are immediately apparent. A field observation allows one to absorb a range of scenes of a given area whereas a photograph generally represents a single scene, separated from its context.

Photographs allow viewers to immediately compare scenes from widely separated areas, which is impossible in the field. While the range of landscapes viewed in the field is generally narrow, being constrained by the range of scenes present, the range for a set of photographs of scenes can be far wider. Viewing photographs quickly establishes the relative values of widely dispersed landscapes, an extremely difficult achievement for field surveys; in the field the scenes set their own values unrelated to any common base, and it is difficult, if not impossible, to relate this to a common standard in the field.

Not only does photography save the time and expense that might be required for participants to travel between locations, but it also allows compression of seasonal variations into a few moments – a feat that field observations cannot hope to achieve.

Field observations take time whereas an observer may view a photograph for only a few seconds. Field observations have their own advantages: they generally occur while in motion, observing the same scene from a range of viewpoints, even allowing one to enter into the scene and gain an appreciation of its depth and height and width experientially. In contrast, a photograph represents in two dimensions a scene that one views over time as a spectator, not as participant in the three dimensions of the true scene. Thus, a photograph reduces the experiencing of a scene in the field, not from three dimensions to two, but from four dimensions to two.

This process of simplification focuses attention on the visual quality of the scene rather than on aspects that are irrelevant to this purpose. 

The field of vision of the eye is much larger than that contained within the typical photograph: the human eye views a cone of vision of 130° [with peripheral vision extending to 208°] compared with only half of this, 65°, for a wide angled 35 mm camera lens [Shuttleworth, 1980, 63]. Add to this the greater field of view provided by motion, and it is evident that photographs provide a very restricted view. Field observations are frameless, the landscape exists in its totality without being bound by some artificial contrivance to contain it whereas a photograph is a sample of the scene. Viewing a scene in the field allows one to choose what to view, whereas photographs reflect the choices made by the photographer, thus limiting their individuality.

Viewing the scene in the field is frameless, a lateral 360° view plus upwards and downwards. By contrast, a photograph is limited, the frame denying the view beyond.

Photographs present a static scene which one observes from a distance, as though in a mirror, without opportunity to enter or become involved - the observer “of the natural environment is in [the] environment in a way in which the spectator of a photograph is not in the photograph” [Carlson, 1977].

In transforming a three dimensional landscape into a two dimensional image, a photograph subtly changes the scene’s appearance. A photograph of a scene, particularly a black and white rendition, highlights the formalist qualities of line, form, colour, texture, proportion and balance. Indeed when viewing a photograph the elements can be seen as forms, lines, textures whereas in the field they are trees, grass, water, clouds and so on.

In the field one can be aware of the effect of time, season and ephemeral phenomena such as lighting on the appearance of the landscape - the scene on a dark night, lit by moonlight, snow covered or drenched with rain, the scene amidst a storm, lit by a setting sun, or the boughs of trees bent by a strong wind. Photographs used in surveys are generally taken during the 10 am to 4 pm period to gain maximum light penetration, reduce shadows, and avoid the ephemeral effects provided by sunrise and sunset. Photographs in tourist brochures generally show the scene under ideal conditions; similarly, photographs used in surveys can convey an ideal state that fails to reflect the full diversity of conditions in the field.

Field observations allow the observer to be aware of other stimuli on the senses - the sounds of birds, leaves, wind, water; the smell of the woods and of the air; touching the bark of the trees, the feel of the track under the feet, the coolness of the wind or the water in the stream; and the taste of water or berries off bushes.

While photographs have none of these peripheral stimuli directly, viewing photographs of scenes can bring recollections of the actual experiences in similar locations. This will obviously apply more readily where the observer is familiar with the kind of area represented by the photographs.

Generally speaking an observer in the field has chosen to visit the location and, therefore presumably has a preference for the scenes to be experienced. By contrast, a participant in a landscape preference study has not necessarily any real desire to visit or experience the scenes portrayed. Thus, one would expect the preferences gained from field observers who have voluntarily visited the area to exceed those of a random sample of the community chosen to view the photographs of the same scenes. However, the popularity of a locality may be due to factors other than its landscape (e.g. Dunn, [1976] found that a particular site was more popular than others due to its convenience for local, short-stay recreation trips).

The influence of the photograph goes beyond the emphasis of the formalist, the composition of the landscape elements in a photograph has played a role in shaping community landscape preferences [Stilgoe, 1984]. Since the end of the 19th century the combination of cars and cameras has resulted in the photography of countless scenes, particularly along popular scenic routes.

According to Stilgoe, rules of composition were promulgated by popular magazines - rules such as not allowing the horizon to bisect the scene, having a broad foreground with a tree, fence or road, an unimportant middle ground and having mountains, clouds or other features of interest in the background. Care was taken to avoid anything indicative of industry - telegraph poles along early roads were a bane and an early professional photographer removed these from his negatives.

These rules are clear parallels with the Gilpin’s 18th century notions of the picturesque - “that kind of beauty which would look well in a picture” and of the rules he established, particularly of the foreground, middle ground and background.

A range of studies has been conducted into the suitability and effectiveness of photographs as alternatives to field observation. These are summarised below.

The effect on preferences of the location of vegetation in a scene was examined by Patsfall et al [1984]. Their first study found that foreground vegetation on the right hand side of a scene gave positive preferences, but this was negative if the vegetation was on the left side. However a second study reversed the slides so that the content that had been on the right was now on the left. The result was that the left foreground was positively valued while the right foreground was negatively valued. The findings suggest that placement of content in the foreground affects preferences rather than its location on one or other side of the scene.

Relevant to composition was Nassauer’s [1983] comparison of responses to 50 mm slides and 35 mm wide angle slides. She combined three 50 mm photographs to provide a panoramic scene and compared these with the wide angle view. Responses for 17 pairs of matched sets indicated that the rating of the panoramas were higher than the wide angled scenes [p < 0.05].

While clearly there are significant differences between photographs and field observations the cost and logistical difficulty of taking large numbers of observers into the field militate against field based assessments. Dearden’s study [1980] near Victoria, BC was one of the few preference studies based on field assessments - 12 observers were transported by mini-bus through the area over two days. Robinson et al [1976] also used field methods in surveying the Coventry-Solihull-Warwickshire region of England and Briggs & France [1980] transported observers through the study area in South Yorkshire.

Some studies have overcome the difficulties of field-based surveys by interviewing those on site. Brush and Shafer [1975] interviewed campers in the area being assessed. This results in only those with an interest in the area being interviewed. Differential accessibility of sites may affect the selection of the population being studied [Shuttleworth, 1980].

Photographs can be modified to include or delete certain features enabling assessment of this on preferences. Hull & McCarthy [1988] used photographs of the Australian bush with and without wildlife to assess whether wildlife enhances preferences [it does!]. Similarly photographs can be used to depict changes to the landscape which could not be simulated in the field [e.g. Trent et al, 1987; Zube et al, 1987].

Some techniques to assess landscape preferences would be difficult if not impossible to use in a field situation. In the LCJ, Q-sort and rating methods participants compare a range of photographs at a sitting. The Q-sort method requires participants to place photographs of scenes in up to say seven piles and allows the participant to change their choices. Similarly the LCJ method requires the participant to compare paired photographs; a comparison of 15 scenes requires 105 paired photographs.

Shafer’s method of analysing photographs of landscapes would be difficult to replicate in a field situation - he cautiously stated in his paper that the “model does not predict landscape appeal directly. Rather it predicts the appeal for a photograph of a landscape” [Shafer et al, 1969]. Photographs thus enable the use of techniques that would be virtually impossible to employ in the field. The SBE method, however, can be used equally in the field and with photographs.

Zube et al [1987] traced the development of simulation techniques, from the development of early drawings and models through to photography, videos and animation. They also reviewed the literature on photographic representations.

For a review of research that has compared field assessments of landscapes with photographs click here.

Labels

Several studies have examined the influence that labelled photographs have on preferences.

Anderson [1981] used the SBE method to assess the effects of labels. A set of 90 slides of ponderosa pine forest in Arizona was divided randomly into six sets of 15 slides each. The experimenter introduced each set as showing a national park, national forest, a commercial timber stand, an outdoor recreation area, a wilderness area or a leased grazing range. A label accompanied the showing of the slides.

The study found that the SBE scores were affected by the land use designations [Figure 12]. Wilderness and national park labels elevated scores while economic uses depressed them. ANOVA tests indicated that the labels accounted for a substantial amount of the variance: 12% [F = 25.87, df 5, 495; p < 0.001]. The findings reinforce the importance of naturalism in positively influencing preferences.

label

Source: Anderson, 1981
Figure 12 Effect of Labels on Scenic Quality Rating of Forests

Hodgson & Thayer [1980] used a similar method with labels appearing on identical colour photographs: lake - reservoir, forest growth - tree farm, pond - irrigation and stream bank - road cut [Table 6].

Table 6 Effect of Labels on Photographs

Group Natural Label Human influence
1
20.7
25.0
2
25.2
29.8
3
26.8
38.4
Average
24.3
31.1

Note: Low scores mean better scenic quality, high score - low scenic quality
Differences significant at p < 0.05 Source: Hodgson & Thayer, 1980

In all cases, labels implying human influence resulted in the scenes being judged as of lower scenic quality, with the differences in Group 3 being particularly pronounced. The figures indicated that the scores given for human influence were 78% that of the natural labels, considerably less than the Anderson study.

The authors suggested that the labels may stimulate viewers to “supply their own images of what is outside the frame.”, imagining scenes supplied by the memory of landscapes not actually in the photograph. Alternatively, the labels may cue mental constructs in the viewer’s mind with an inherent rank ordering of scenic quality - akin to the adage “don’t confuse me with the facts, I’ve made up my mind”.

In a similar study, Vodak et al, 1985 obtained different results from Anderson. Student participants were divided randomly into two groups, one group was informed about the harvesting practices, including use of the term “clearcut”, but the other group was not given this information. The scenic beauty estimate for the informed students was very similar to that of the uninformed students - correlations with landowner SBEs of 0.95 and 0.93 respectively [p < 0.0001]. There were no differences in the scenic beauty evaluations of the two groups leading the authors to conclude “that there was no semantic bias present."

Two studies described the differences in scenes verbally rather than integrating them with the photograph. Simpson et al [1976] showed scenes firstly as a baseline and then the subjects were given a written explanation about forest practices as seen in the slides. In modelling condition, a forestry ‘expert’ would then indicate how they would evaluate some sample slides. In the no-social anchor condition, no indication was given. The subjects assessed further slides. Where a message had been given, the differences in responses for the clearcut, thinned and natural scenes were marked but were non-existent for the no-message situation. The social anchoring and message increased the subjects’ acceptance of the managed areas.

Yeiser & Shilling [1978] used galvanic skin response to measure the intensity of emotion among viewers of natural scenes. The GSR is a physiological measure, as used in lie detection, over which the subject has no control. Using a conservation group and forestry students as subjects plus a control group of non-forestry students, scenes of forest management practices were shown with selected stimulus terms displayed [Table 7].

Table 7  Galvanic Responses to Scenes and Descriptions 

Term
Conservation Group
Forestry Group
Control Group
Cull tree
0.50
- 0.44
0.65
Site prep. area
- 0.38
0.01
- 0.59
Charred slash pile
- 0.62
- 0.23
- 0.51

ANOVA showed that the groups differed [p < 0.05] in their response to the cull tree term as well as to scenes of site preparation and charred slash piles. Surprisingly, the control group, had stronger antipathy to two of the terms than the conservation group suggesting that the greater knowledge of forestry practices by the latter group actually modified their responses.

The authors drew three conclusions:

  • People with no knowledge of the professional terminology [e.g. cull tree] responded to the connotation of the term
  • The greater the number of reasons given for motivating a response, the less intense the response
  • The longer the time perspective under consideration, the less intense the response.

Overall, these studies indicated that, for whatever reason, appellations given to scenes do affect the responses significantly. They indicated the importance of not colouring responses by suggesting or including anything that will constrain or direct the respondent towards a particular response.

Viewing Time

In 1980, R.B. Zanonc argued against the prevailing doctrine in cognitive psychology that affect is post-cognitive. He provided experimental evidence that discriminations [like-dislike] could be made in the complete absence of recognition memory.  Urlich also cited evidence in support of affect being precognitive [Urlich, 1986, 30-31, Urlich et al, 1991, 206-7]. Urlich proposed that:

“immediate, unconsciously triggered and initiated emotional responses - not ‘controlled’ cognitive responses - play a central role in the initial level of responding to nature, and have major influences on attention, subsequent conscious processing, physiological responding and behavior” [Urlich et al, 1991].

He also suggested that an:

“evolutionary perspective implies that adaptive response to unthreatening natural settings should include quick-onset positive affects and sustained intake and perceptual sensitivity.”

These views are antithetical to the information processing approach which holds that, although preferences are generated extremely rapidly, they are nevertheless the result of cognitive processing. Lazarus [1982] suggested that Zajonc made the mistake of equating cognition with reality [Ibid, 1022]. Lazarus argued that this process occurred outside of conscious awareness and was virtually automatic. He:

“regards emotion as a result of an anticipated, experienced, or imagined outcome of an adaptionally relevant transaction between organism and environment [and therefore] cognitive processes are always crucial in the elicitation of an emotion.”

Lazarus considered that this approach “in no way threatens the basic premises of the evolutionary-adaptional perspective."

Herzog has examined this issue in several studies. Herzog [1984, 1985] included scenes which respondents viewed for 20 milliseconds [i.e. 1/50 sec] or 200 milliseconds [i.e. 1/5 second] and compared the responses with 15 seconds. Tests on the four waterscapes showed that their means differed from each other [p < 0.05]. In a mountain waterscapes scene, the 20 ms time differed from the others [p < 0.05] while for a swamp scene, the two fast speeds differed from the 15 second time. There were no significant differences in viewing times for the other scenes [Figure 13].

Herzog

Source: Herzog, 1984 and 1985
Figure 13 Effect of Viewing Times on Preferences

The results for the three lower scenes indicated no significant difference between the two high-speed viewings, but these were significantly lower than the mean for the 15 second viewing [t = 2.37, df = 113, p < 0.025].

While short duration viewing times affected preference ratings, the difference was very small. Nor was the difference in one direction - some were lower and some were higher. The findings were probably insufficient to provide definitive support for Zanonc, but it is difficult to comprehend complex cognitive processes being undertaken in as short a space as 20 ms.

Wade [1892] examined whether preferences were affected by respondents being given as much time as they desired to view scenes. He found no relationship between preferences and viewing time.

Mode of Presentation - Conclusions

 The mode of presentation of scenes can influence landscape preferences and care needs to be taken:

  • Providing the photographs are in colour and that they give a sufficient view to provide context for a scene, they can be a reasonable surrogate for the physical landscape and also they tend to yield a more objective response than a field assessment
  • Labels given to scenes can affect responses significantly, particularly if they indicate a human influence in an otherwise natural scene; it is thus essential that responses be not coloured by providing additional suggestions other than what the scene contains
  • Short viewing times appear to slightly affect preference ratings but the findings are not consistent

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