assessing and mapping landscape preferences in belgium
TRANSCRIPT
Research line 1Research line 1
Assessing and mapping landscape Assessing and mapping landscape preferences in Belgiumpreferences in Belgium
Vincent Vincent VanderheydenVanderheyden
KarolienKarolien PeetersPeeters
�� RL 1RL 1: : RepresentativeRepresentative surveysurvey (photo(photo--questionnaire) in questionnaire) in orderorder to to
understandunderstand the the wayway people valorise people valorise landscapeslandscapes in relation to the in relation to the
location of location of windwind energyenergy parksparks..
�� ResultResult: :
A modelA model thatthat allowsallows the the assessmentassessment of of landscapelandscape qualityquality basedbased on on
measurablemeasurable indicatorsindicators. .
The The ‘‘consensus consensus preferencepreference’’ for for differentdifferent landscapelandscape types (types (withwith
and and withoutwithout visible visible windwind turbines) turbines) willwill bebe mappedmapped..
General Objective
Research planResearch plan
�� AssessmentAssessment of the of the subjectivesubjective landscape landscape attractivityattractivity�� PhotoquestionnairesPhotoquestionnaires: : originaloriginal photosphotos + + samesame photosphotos withwith simulatedsimulated wind wind turbinesturbines
�� ModellingModelling attractivityattractivity basedbased onon significant landscape parameterssignificant landscape parameters�� attractivityattractivity = f(% green, % = f(% green, % urbanisationurbanisation, traditional landscape , traditional landscape elementselements, , disturbingdisturbing elementselements, , topographytopography, water, , water, ……))
�� Map Map subjectivesubjective landscape landscape capacitycapacity byby model model extrapolationextrapolation in GISin GIS
�� SimulationSimulation of of regionalregional impact of wind turbine impact of wind turbine onon landscape landscape attractivityattractivity
PhotoquestionnairesPhotoquestionnaires
�� WidelyWidely usedused as a as a tooltool forfor assessingassessing landscape landscape
preferencespreferences (e.g. (e.g. suburbanisationsuburbanisation, , roadsroads, ,
greenhousesgreenhouses, traditional landscape , traditional landscape elementselements, , ……))
�� ValidityValidity of of photographsphotographs as as surrogatessurrogates forfor landscape landscape
experienceexperience
�� PossiblePossible to to reachreach a a broadbroad publicpublic
�� TripodTripod at at eyeeye levellevel
�� Horizontal Horizontal observationobservation angleangle 120120°° ((AutostichAutostich))
�� 250 250 photographsphotographs taken in different taken in different regionsregions of of FlandersFlanders and and WalloniaWallonia
�� 54 54 photographsphotographs selectedselected fromfrom orginalorginal database (of 250) to database (of 250) to cover a cover a largelarge varietyvariety of of ruralrural landscape types (landscape types (forestedforested, , suburbanisedsuburbanised, , visiblevisible water surfaces, traditional, open, water surfaces, traditional, open, bocagebocage, , ……))
PhotoquestionnairesPhotoquestionnaires
PhotoquestionnairesPhotoquestionnaires
LocationLocation of the 54 of the 54 selectedselected photographsphotographs
PhotoquestionnairesPhotoquestionnaires
�� SimulationSimulation of wind turbines in the landscape of wind turbines in the landscape
((PhotoshopPhotoshop))
PhotoquestionnairesPhotoquestionnaires
number of turbines per picture
0
2
4
6
8
10
12
14
1 turbine 2 turbines 3 turbines 4 turbines 5 turbines 6 turbines
number of turbines
nu
mb
er o
f p
ictu
res
placing of turbines per picture
0
5
10
15
20
25
30
35
solitair line double line cluster arch
placing of turbine
nu
mb
er o
f p
ictu
res
�� VariationVariation in in numbernumber of turbines of turbines visiblevisible and and distancedistance to the to the observerobserver
PhotoquestionnairesPhotoquestionnaires
�� +/+/-- 2000 2000 respondentsrespondents
�� EachEach respondent: 18 respondent: 18 photographsphotographs, 12 without wind turbine, , 12 without wind turbine,
6 6 withwith wind turbinewind turbine
PhotoquestionnairesPhotoquestionnaires
�� EachEach respondent: 18 respondent: 18 photographsphotographs, 12 without wind turbine, , 12 without wind turbine, 6 6 withwith wind turbinewind turbine
�� The 108 (= 54*2) photographs are divided into 18 piles of 6 The 108 (= 54*2) photographs are divided into 18 piles of 6 photographs photographs
�� 9 piles of photographs with wind turbines9 piles of photographs with wind turbines
�� 9 piles of the same photographs without wind turbines 9 piles of the same photographs without wind turbines
�� The compilation of the piles: different landscape characteristicThe compilation of the piles: different landscape characteristics in s in each pileeach pile
�� Combination of the piles in 9 sets of 18 photographsCombination of the piles in 9 sets of 18 photographs
�� The order of the photographs in each set has been determined The order of the photographs in each set has been determined randomly.randomly.
IAAA BA CA DA EA FA GA HA
54 without turbine 54 with turbine
HB IBCB DB EB FB GBBBAB
Set 1ABBACA
Set 2BBAACA
Set 3CBDAFA
Set 4DBGAFA
Set 5EBDAIA
Set 6FBGAHA
Set 7GBAAIA
Set 8HBBAEA
Set 9IBEAHA
PhotoquestionnairesPhotoquestionnaires
�� +/+/-- 2000 2000 respondentsrespondents
�� EachEach respondent: respondent:
�� 2 2 testphotographstestphotographs
�� 1 set of 18 1 set of 18 photographsphotographs (12 without wind turbine, 6 (12 without wind turbine, 6 withwith wind wind
turbine)turbine)
�� Attitude Attitude scalescale: 7: 7--point point LikertLikert--scalescale
PhotoquestionnairesPhotoquestionnaires
�� 2 2 testphotographstestphotographs
PhotoquestionnairesPhotoquestionnaires
�� Additional questionsAdditional questions
�� SES: socioSES: socio--economic indicatorseconomic indicators
�� Questions which help to establish a link with the second Questions which help to establish a link with the second
research line (in depth interview):research line (in depth interview):�� Landscape in environment of respondentsLandscape in environment of respondents
�� Knowledge about nearby projectsKnowledge about nearby projects
Set 3 = reeks Set 3 = reeks CBCB, DA, FA, DA, FA
ramilliesramillies44AAFF
wasseigeswasseiges66AADD
Laakdal_Laakdal_nikenike22AAFF
botrangebotrange11AAFF
brulybruly_4WT_4WT33BBCC
Bertem2mtBertem2mt44BBCC
dinantdinant22AADD
BlankenbergeBlankenberge_Natuurreservaat_Natuurreservaat11AADD
Heuvelland_Blekerijstraat1mtbisHeuvelland_Blekerijstraat1mtbis55BBCC
LommelLommel_Balendijk1mt_Balendijk1mt66BBCC
GooikGooik_Assesteenweg1_Assesteenweg133AADD
StokkemStokkem__SchiervellaanSchiervellaan55AAFF
Geel_Breeven4mtGeel_Breeven4mt11BBCC
LinterLinter__RodestraatRodestraat33AAFF
boisbois--odetodet_1WT_1WT22BBCC
StokkemStokkem_Molenveld4_Molenveld455AADD
VillersVillers--enen--FagneFagne66AAFF
javinguejavingue44AADD
PhotoquestionnairesPhotoquestionnaires
�� Door Door byby door questionnaires (+/door questionnaires (+/--2000)2000)
�� StratifiedStratified sample of 80 sample of 80 formerformer municipalitiesmunicipalities ((FlandersFlanders, Brussels, , Brussels, WalloniaWallonia))
�� 25 25 respondentsrespondents per per municipalitymunicipality (To (To muchmuch?)?)
�� Representative sample for BelgiumRepresentative sample for Belgium
�� n = (1.96n = (1.96²² x N) / (1.96x N) / (1.96²² + margin of error+ margin of error²² x (Nx (N--1))1))
�� For Belgium: N= 10,000,000 For Belgium: N= 10,000,000 –– margin of error 5% = 2.5% above margin of error 5% = 2.5% above
and 2.5% below and 2.5% below –– confidence interval 95% (1.96 standard error)confidence interval 95% (1.96 standard error)
�� 1500 respondents = near to a standard representative sample1500 respondents = near to a standard representative sample
3846001067153624004267Number of respondents
10%8%6%5%4%3%Margin of error
PhotoquestionnairesPhotoquestionnaires
�� StratifiedStratified sample of 80 sample of 80 formerformer municipalitiesmunicipalities ((FlandersFlanders, Brussels, , Brussels, WalloniaWallonia))
First results
�� HeverleeHeverlee en en GelrodeGelrode, 50 interviews, 2 sets (set 1 en set 2), 50 interviews, 2 sets (set 1 en set 2)
GenderGender
Man code 1Woman code 2
Mean Heverlee: 1,4Mean Gelrode: 1,6Mean set 1: 1,5
Mean Heverlee: 1,6Mean Gelrode: 1,7Mean set 1: 1,6
Set 1 - Verdeling geslacht
manvrouw
Set 2 - Verdeling geslacht
manvrouw
AgeAge
Mean Heverlee: 46Mean Gelrode: 43Mean set 1: 44Minimum: 16Maximum: 81
Mean Heverlee: 41Mean Gelrode: 41Mean set 1: 41Minimum: 13Maximum: 64
Set 1 - Verdeling leeftijd
<20
20-29
30-39
40-49
50-59
60-69
>69
Set 2 - Verdeling leeftijd
<20
20-29
30-39
40-49
50-59
60-69
>69
Level of Level of educationeducation
88universityuniversity
11higherhigher educationeducation (long type)(long type)
1010higherhigher educationeducation (short type)(short type)
55higherhigher secondarysecondary educationeducation
11lowerlower secondarysecondary educationeducation
11without diploma/without diploma/elementaryelementary
educationeducation
33universityuniversity
33higherhigher educationeducation (long type)(long type)
66higherhigher educationeducation (short type)(short type)
77higherhigher secondarysecondary educationeducation
11lowerlower secondarysecondary educationeducation
44without diploma/without diploma/elementaryelementary
educationeducation
Set 1 - Verdeling onderwijsniveau
zonder diploma/lageronderwijslager middelbaar
hoger middelbaar
hoger onderwijskorte typehoger onderwijslage typehoger universitaironderwijs
Set 2 - Verdeling onderwijsniveau
zonder diploma/lageronderwijs
lager middelbaar
hoger middelbaar
hoger onderwijskorte type
hoger onderwijs lagetype
hoger universitaironderwijs
CategoryCategory of of respondentsrespondents
1717workerworker
44retiredretired
22housewifehousewife-- oror husbandhusband
11jobjob--seekerseeker
22studentstudent
1212workerworker
44retiredretired
22housewifehousewife-- oror husbandhusband
22jobjob--seekerseeker
44studentstudent
Set 1 - Verdeling personencategorie
leerling of studentwerkzoekendehuisvrouw- of manpensioenwerkende
Set 2 - Verdeling personencategorie
leerling of studentwerkzoekendehuisvrouw- of manpensioenwerkende
AppreciationAppreciation withwith and without wind and without wind
turbineturbine
Gemiddelde waardering
0
1
2
3
4
5
6
7
0 2 4 6 8 10 12 14
landschap
waa
rder
ing
zonder turbine
met turbine
InitiallyInitially lessless appreciatedappreciated landscape: landscape: increaseincrease in in appreciationappreciation
InitiallyInitially betterbetter appreciatedappreciated landscape: landscape: decreasedecrease in in appreciationappreciation
H 8,86C 6,49
E 8,08
J 1,58I 3,9
D 3,45
G 4,8
A 6,84
F 6,08
B 6,36
y = 0,2052x - 0,8123
R2 = 0,5276
-0,8
-0,6
-0,4
-0,2
0
0,2
0,4
0,6
0,8
1
1,2
0 2 4 6 8 10
aantrekkelijkheid oorspronkelijke foto
del
ta a
antr
ekke
lijkh
eid
Test case Test case --> Hypothese> Hypothese
AppreciationAppreciation withwith and without wind and without wind
turbine (turbine (pilepile A and B)A and B)y = 0.5199x - 2.6387
R2 = 0.3571
-1
-0.5
0
0.5
1
1.5
0 1 2 3 4 5 6 7
waardering landschap zonder turbine
del
ta w
aard
erin
g
Series1
Linear (Series1)
Decrease in
appreciation
Increase in
appreciation
DecreaseDecrease in in appreciationappreciation
DecreaseDecrease in in appreciationappreciation
IncreaseIncrease in in appreciationappreciation
IncreaseIncrease in in appreciationappreciation
Landscape attractivity maps
�� AttractivityAttractivity = f (landscape variables, wind turbine)= f (landscape variables, wind turbine)
Stedula
Landscape attractivity maps
�� AttractivityAttractivity = f (landscape variables, wind turbine)= f (landscape variables, wind turbine)
Landscape attractivity maps
�� Mapping the Mapping the attractivityattractivity of landscapes according to the inhabitants of of landscapes according to the inhabitants of Belgium Belgium
�� ThisThis meansmeans: : linkinglinking visibilityvisibility of indicators of indicators basedbased onon terrerstrialterrerstrialphotographyphotography withwith viewshedviewshed indicators indicators basedbased onon GISGIS--layerslayers ((DEMDEM, , HRHR--landland cover cover mapsmaps) ) �� MScMSc thesis thesis MelisandeMelisande CelisCelis
Agenda
Writing of the report
Link between line 1 and 2
Simulation of regional impact of wind turbine on landscape attractivity
Map subjective landscape capacity bymodel extrapolation in GIS
linking terrestrial photography withviewshed indicators based on GIS-layers(MSc thesis)
modelling attractivity
digitalisation of photographs
questionnaires
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