Landscape Quality Assessment - PowerPoint Presentation

1. Landscape Quality AssessmentDr Andrew LothianScenic SolutionsFlinders University Research Colloquium, 13 August, 2014

2. ScopeWhy measure landscape quality?How to measure landscape qualityAcquiring the dataRespondentsOverall findingsMappingLessons & Applications The presentation focuses on the study of the Lake District in England but also draws on other studies conducted in South AustraliaDr Andrew Lothian, Scenic Solutions2

3. Who is Andrew Lothian?3Dr Andrew Lothian, Scenic SolutionsI worked in environmental policy in SA Government for many years in Australia. Lectured at Flinders in policy.Long interest in how to quantify landscape aesthetics.During 1990s, undertook PhD in landscape quality assessment at the University of Adelaide.Since then I have conducted 10 consultancy studies on landscape quality & visual impact assessment of developments including wind farms. www.scenicsolutions.com.auFlinders RangesS.A. CoastRiver MurrayBarossa & Eden Valleys

4. Why measure landscape quality?Unlike biophysical assets, landscape aesthetics is a qualitative asset, as perceived by people.The European Landscape Convention defines landscape as “an area, as perceived by people, whose character is the result of the action and interaction of natural and/or human factors.” Landscape quality is the human subjective aesthetic response to the physical landscape.Beautiful landscapes attract millions of tourists throughout the world to areas such as the Swiss Alps, the Canadian Rockies, the Italian lakes and Amalfi coast. The Lake District in England attracts 20 million visitors annually. Australia’s Great Barrier Reef, Kakadu and the Kimberlies, Uluru and Kangaroo Island attract many overseas visitors. They come to see the wild and natural landscapes, not the cities. Many World Heritage areas are outstanding landscapes.Exposure to natural landscapes provides significant health and restorative benefits.Views of attractive landscapes adds significant value to properties.Dr Andrew Lothian, Scenic Solutions4

5. How not to measure landscape qualityThere have been many attempts to measure landscape quality by recording all the physical features – land forms, land cover, land use, water, geology, etc, in the expectation that by analysing all of this data, the landscape quality would emerge.It never did!The reason is that this process is a cognitive activity involving analysis and thinking. But landscape quality involves making judgements about what we like – i.e. preferences. This is an affective process.Example: We know whether or not we like chocolate by tasting it, not by analysing its content, origin, colour etc. These can inform us but do not define its taste. Similarly we judge music by whether we like it, not by analysis of the instruments, score, etc. Landscape character units defined and mappedScenic quality indicators mappedWeightings applied Scores of attributes appliedSubjective judgements madeScenic quality comparisons madeScenic quality described and/or mapped5Dr Andrew Lothian, Scenic Solutions

6. Psychophysics – basis for measuring landscape qualityPreferences are our likes and dislikes and are based on affect, not cognition. The dictionary define aesthetics as “things perceptible by the senses as opposed to things thinkable or immaterial.”This clearly differentiates thinking from the senses.Researchers fell into the trap of assuming cognition was the same as affect.They are completely different.In the 19th century, Gustav Fechner, a German physicist, developed psychophysics – the science of measuring the brain’s interpretation of information from the senses (sight, sound, smell, taste, touch).Over recent decades, psychologists have applied its methods to measuring human landscape preferences.Gustav Fechner 1801 - 18876Dr Andrew Lothian, Scenic Solutions

7. Only by applying the affective paradigm can the attractiveness of a landscape be determined.Attractiveness is determined by measuring preferences.As it relies on preferences it is a subjective quality but preferences can be analysed objectively.Common elements in research methodologies are: Selection of scenes for rating.Rating scale – e.g. 1 to 10.Rating instrument – i.e. a means for showing scenes with a rating scale.Participants who rate the scenes – a sufficient number of raters for statistical analysis. They should be disinterested in the subject – i.e. have no stake in the outcome.Applying the affective paradigm7Dr Andrew Lothian, Scenic Solutions

8. 1. Photograph region2. Classify region’s landscape units3. Select survey photographs4. Identify & score landscape quality components5. Prepare & implement Internet survey6. Prepare data set and analyse results7. Map region’s landscape qualityThe method I use involves photographing the area, classifying the area into units of similar landscape characteristics, selecting photographs representative of these characteristics, rating of the photographs, analysing the results, and using the understanding gained to map the landscape quality.Community Preferences Method8Dr Andrew Lothian, Scenic Solutions

9. Use of PhotographsAdvantages of photographs:Avoids transporting large groups of people through large region.Enables widely separated locations to be assessed on comparable basis.Can cover seasonal changes.Can assess visual impact of hypothetical developments.Many studies have shown that photographs will provide similar ratings as field assessments providing certain criteria are met.A meta-analysis of studies found a correlation of 0.86 between on-site and photo assessments.Criteria for photographsStandardised horizontal format50 mm focal length (digital equivalent)Colour Non-artistic compositionSunny cloud-free conditions (ideal)Avoid strong side lighting of early morning or eveningGood lateral & foreground context to scenesAvoid distracting and transitory features including peopleThe principle is standardisation so that respondents judge the landscape, not the photograph9Dr Andrew Lothian, Scenic Solutions

10. Landscape UnitsAreas of similar characteristics e.g. land form, land cover, land use, water, texture, colour – as shown in the map.Simple classification of Lake District:Coastal estuaries, marshes and beachesPlainsLow fellsValleys without lakesValleys with lakesHigh fells High mountainsBase the selection of photographs on sampling the landscape units.Lake District Landscape TypologyChris Blandford Associates 10Dr Andrew Lothian, Scenic Solutions

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12. Landscape componentsDr Andrew Lothian, Scenic Solutions12In addition to having photographs rated for landscape quality, a small group scored the scenes for a range of components that might contribute to landscape quality. 1 – 5 scale used to score the visual significance of the component in each scene.For the Lake District, components covered:WaterLand formsLand cover – shrubs and treesNaturalness – absence of human influenceDiversity – total busyness of the sceneCultural elements – artificial featuresStone walls & hedgerowsBy combining these scores with the ratings the strength of their contribution to landscape quality can be determined.Scores: Stone walls & hedgerows 3.31, naturalness 2.54, land cover 3.57 Scores: Land cover 4.22, water 3.10, land form 4.11, diversity 3.90

13. Photography March, June and July, 2013 covering winter, spring & summerOver 4000 photographs145 photos selected and Internet survey prepared in August1500 invitations emailed to potential participantsAcquiring the Data – Lake DistrictRoutes travelled for photographyProgress in survey participation13Dr Andrew Lothian, Scenic Solutions

14. Survey data540 responses314 rated all 145 scenes, 73%34 rated 0 scenes4 displayed strategic bias – mostly 10sNet 430 UK-born respondents & 72 non-UK bornAnalysis covered only UK-bornComparison of ratings by non-UK born included.Number of completed surveysHistogram of scene meansDataNumberMeanSDRespondents4306.141.23Scenes1456.111.2414Dr Andrew Lothian, Scenic Solutions

15. Dr Andrew Lothian, Scenic SolutionsCharacteristics coveredAgeGenderEducationBirthplacePostcodeFamiliarityResidenceRespondent characteristicsThe respondents were generally middle aged, with many more males participating than females, and most were very well educated.15

16. Comparison of respondents with UK population16Dr Andrew Lothian, Scenic SolutionsCompared with the general UK population, the respondents were:Older More males Higher levels of educationThe differences were statistically different.

17. Similarity of ratingsThe respondents differed significantly from the UK population. Does this matter?It would matter if preferences varied widely across age, gender & education. But they don’t vary significantly.The top graph compares the average preferences on a 1 – 10 scale, indicating their similarity. The bottom graph exaggerates the scale to show the differences. The range is only 0.32 or +/- 0.16.So regardless of their characteristics, people rated the scenes similarly.17Dr Andrew Lothian, Scenic Solutions

18. Respondent origins & familiarityMany of the respondents came from the north-west, 64% lived in Lancashire and Cumbria.57% lived in the Lake DistrictFamiliarity increased ratings by as much as 14%Familiarity might breed contempt, but in respect of landscapes it has the opposite effect. This is due to “place attachment”.CategoryRating% increaseExtremely familiar6.2614.21Very familiar6.039.98Somewhat familiar5.999.25Visited but not familiar6.1011.25Never visited5.48100.0018Dr Andrew Lothian, Scenic Solutions

19. Overall ratings by landscape type19Dr Andrew Lothian, Scenic SolutionsLandscapeScenesMeanMountains227.05Valleys with lakes257.02Rockfaces106.81Streams46.47Valleys without lakes96.27High fells225.87Low fells 115.66Coast35.56Dense trees55.24Quarries34.95Pines84.39Plains104.15

20. Mountains#122 8.36#44 7.55#141 6.51#26 7.2022 scenesMean rating 7.05Range 5.43 to 8.36, a wide range of 2.93 Strong skew to higher ratings – histogramDiversity & naturalness have quite strong influence on ratingsy = 0.78x + 4.20, R² = 0.37y = 0.86x + 4.43, R² = 0.4820Dr Andrew Lothian, Scenic SolutionsHistogram

21. Rockfaces21#81 6.38#99 6.91#17 7.02#111 6.0210 scenesMean rating 6.81Range 5.73 to 7.73, a moderate range of 2.00Strong skew to higher ratings – histogramSurprisingly, neither height or steepness influenced ratingsy = -0.49x + 8.85, R² = 0.26y = 0.19x + 5.92, R² = 0.09Dr Andrew Lothian, Scenic Solutions

22. High Fells22#28 7.14#30 5.04#77 4.39#59 4.3922 scenesMean rating 5.87Range 3.85 to 7.39, a wide range of 3.54Low to high ratings – histogramDiversity & naturalness have strong influence on ratingsy = 1.47x + 2.51, R² = 0.46y = 0.61x + 3.94, R² = 0.16Dr Andrew Lothian, Scenic Solutions

23. Low fells23#5 5.50#55 5.41#100 5.85#109 6.0411 scenesMean rating 5.66Range 4.36 to 6.64, a wide range of 2.28Middle rating – histogramFor those low fells with stone walls, their presence actually decreased ratingsHighest influence of tree spacing on ratings was for scattered trees y = -0.26x+ 6.79, R² = 0.142 = isolated, 3 = scattered, 4 = scat-dense, 5 = denseDr Andrew Lothian, Scenic Solutions

24. 24#11 5.88#120 6.93#57 6.19#63 6.189 scenesMean rating 6.27Range 5.55 to 6.93, a narrow range of 1.38Middle to higher ratings – histogramLand cover & naturalness have moderate influence on ratingsValleys without lakesy = 0.54x + 4.45, R² = 0.44y = 0.80x + 4.00, R² = 0.36Dr Andrew Lothian, Scenic Solutions

25. Valleys with lakes25#16 8.12#38 7.34#89 7.59#136 7.4725 scenesMean rating 7.02Range 5.51 to 8.66, a wide range of 3.15Mainly higher ratings – histogramEven a glimpse of water increased ratingsNaturalness has a strong influence on ratingsy = 1.20x + 2.98, R² = 0.40Dr Andrew Lothian, Scenic Solutions

26. Influence of water on ratingsDr Andrew Lothian, Scenic Solutions26The scores of water in the scenes was compared with the area of water as measured on each photo. There was a reasonable correlation (0.52) but other factors were clearly involved in determining the visual significance of water in a sceneThe area of water as a % of the non-sky portion of each scene was measured and related to the ratings. Surprisingly this found virtually no relationship between the percentage of the scene that was water and the ratings, which suggests that any amount of water, small or large, increases ratings.

27. River Murray StudyDr Andrew Lothian, Scenic Solutions27A similar finding was made in the study of the River Murray. Scenes without water rated 4.43 but the presence of even a small glimpse of water (score 1) raised this to 5.78.The difference in ratings between a glimpse and extensive water was only 1 unit. Water scoreRating15.7826.0336.2846.5356.78Water score 1.05, Rating 6.08

28. Plains28#18 3.74#64 4.05#107 4.74#75 3.8910 scenesMean rating 4.15Range 3.11 to 5.77, a wide range of 2.66Low to middle ratings – histogramAbundance of land cover has slight influence Plains are low in diversity but it has a strong influence. y = 0.44x + 2.77, R² = 0.53y = 1.45x + 1.40, R² = 0.60Dr Andrew Lothian, Scenic Solutions

29. Components vs components 29Revised culturaly = 0.75x + 0.64, R² = 0.37y = 0.79x + 1.09, R² = 0.40y = 0.48x + 1.59, R² = 0.33Landscape components were scored on a 1 – 5 scale.Comparing the scores of one component with another brings out some interesting relationships.Dr Andrew Lothian, Scenic Solutions

30. Components vs ratings30y = 1.29x + 1.93, R² = 0.78y = 1.14x + 2.52, R² = 0.43ScoreRating13.6125.0536.5047.9559.40y = 1.45x + 2.16, R²= 0.63y = 0.19x + 5.78, R = 0.01Cultural elements include farming, sheep and cattle, stone walls and hedgerows, fields, narrow winding roads, and farmhouses.It indicates that cultural elements had little influence on ratings. Dr Andrew Lothian, Scenic SolutionsComparing ratings with scores shows their influence

31. Dr Andrew Lothian, Scenic Solutions31Barossa StudyThe Barossa study made an interesting discovery through comparing factor scores with scenic ratings. It might be thought that the vines enhance scenic quality but this is not so, they actually reduce it.It is the presence of trees around the vineyards that enhance scenic quality.

32. Comparison scenes – with & without features32With polesWithout polesDiff.% 3.134.311.1837.703.024.061.0434.444.025.881.8646.272.924.731.8161.993.274.751.4745.002.924.73PowerlinesColourWith colourWithout colourDiff.%6.655.670.9814.746.3946.3850.0090.145.794.840.9516.416.285.630.6410.254.053.745.794.84With sheepWithout sheepDiff.% 6.475.880.599.125.54.870.6311.454.053.740.317.655.344.830.519.55SheepDr Andrew Lothian, Scenic Solutions

33. 33Stone walls & hedgerows5.504.83With wallsWithout wallsDiff.%5.504.830.6712.186.976.720.253.595.404.890.519.444.314.050.266.035.555.120.437.758.318.00SnowSummerDiff.%7.306.291.0113.848.318.000.313.736.856.830.020.907.497.040.455.95Seasonal changeWaterWith waterWithout waterDiff.% 6.516.240.274.157.346.061.2817.447.486.930.557.307.116.410.709.857.346.06Dr Andrew Lothian, Scenic Solutions

34. 345.024.807.147.17With treesWithout treesDifference% difference4.85.020.224.586.767.140.385.627.177.14-0.03-0.425.045.120.081.595.946.110.162.84Trees were inserted into 4 scenes to assess the effect of revegetating the fells on the landscape. 3 were rated higher without the trees & one was higher with the trees.Respondents may have rejected trees on familiar fells. Or they rejected the dense trees as scattered trees received a positive rating.Or they prefer the fells to be bare rather than vegetated.Trees5.125.04Dr Andrew Lothian, Scenic Solutions

35. MappingMapping proceeded area by area, 40 in all, to build up the complete map. The generic ratings that were derived from the survey were applied to each area. LandscapeRating Plains 4Pines4Low fells 5Rivers6Valleys without lakes 6Valleys with lakes6/7High rounded fells 5High steep (≥30%) fells 6High fells with rockfaces 6Mountains (≥700 m – 850 m) 7Mountains ≥ 850 m 8Dr Andrew Lothian, Scenic Solutions35The map shows the main rating to be 5 (yellow) with ribbons & areas of 6 (light red - rivers, valleys without lakes, steep fells). Many lakes and mountains from 700 – 850 m were 7 (darker red) and inside those were small areas of 8 (darkest red).

36. Landscape quality ratingsDr Andrew Lothian, Scenic Solutions36

37. Dr Andrew Lothian, Scenic Solutions37Why do we like what we like?What generates the appeal of landscapes? – why do we like what we like? Hierarchy of influences – innate individualMost landscape theory is based on evolutionary perspective – what we like is survival enhancing. We like what aids our survival as a species.This might explain our preference for water but doesn’t explain liking for the sea which we cannot drink. Or survival in mountains . DEMOGRAPHIC Individual Indi FAMILIARITYRegional CULTURESociety INNATEAll people It may however explain preferences for scattered trees – like African savannah - rather than dense trees which can hide predators & be difficult to climb.Dearden’s Pyramid of Influences

38. Dr Andrew Lothian, Scenic Solutions38Restorative benefits of viewing nature2012 Cumbria Visitor Survey found that the top reasons for visiting the area was because of the physical scenery and landscape of the area (69%) followed by the “atmospheric character of the area being peaceful, relaxing, beautiful and so on (54%).”Studies from experiencing natural environments: Reduced anger and violence among residents of Chicago apartments and reduced crime in their neighbourhoodLess fatigue and more rapid recovery from fatigueReduced blood pressureLower heart rates and reduced stress for students swotting for examsEven viewing posters of natural scenes is beneficial.Intuitive understanding of the restorative benefits of viewing nature helps explain the popularity of the Lake District which attracts 20 million visitors a year. The landscape survey found that the naturalness correlated highly with ratings, as did land form and diversity, both part of naturalness.

39. Dr Andrew Lothian, Scenic Solutions39What is the economic value of Lake District landscape?A century ago, the Swiss landscape was judged to be worth $200m/annum2009 – 2012 visitation averaged 22.05 million visitor days .Average expenditure of £980 million/year = £44.44/visitor/day. The area of the Lake District National Park is 2219.68 km2Annual expenditure = £441,505/km2 or £4,415/ hectare. Farmgate income £59m = £31,536/sq km or £315/ha = 7% of its value for visitors. Total: £473,041/sq km or £4,730/ hectare.

40. ApplicationsDr Andrew Lothian, Scenic Solutions40Possible applications include:Incorporating landscape quality provisions in policies and planning to ensure its recognition, protection and enhancement;Defining scenic quality objectives for the management, protection and enhancement of landscape quality in the region;Assisting in the definition and substantiation of nominations of areas for World Heritage and National Park status;Promoting the tourism and recreational opportunities of the region;Assisting in the selection of routes for transmission lines and roads and for minimizing developmental impacts, e.g. wind farms.

41. ConclusionsThe project provides insights and understanding of how the community view the Lake District’s scenic assets. Measuring and mapping the landscape quality of the Lake District is a first for the UK which abandoned landscape quality assessment decades ago. However the project demonstrates that a robust and credible method of measuring community preferences is available. 41Dr Andrew Lothian, Scenic Solutions

42. Dr Andrew LothianDirector, Scenic SolutionsPO Box 3158, Unley, Adelaide South Australia, 5061, AUSTRALIAMobile: 0439 872 226Phone/fax: (618) 8272 2213Email: lothian.andrew@gmail.com Internet:  www.scenicsolutions.com.au Dr Andrew Lothian, Scenic Solutions42