From 3D landscape visualization to environmental simulation: The contribution of sound to the perception of virtual environments

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ContentslistsavailableatScienceDirect

Landscape

and

Urban

Planning

jou rn al h om ep a ge :w w w . e l s e v i e r . c o m / l o c a t e / l a n d u r b p l a n

Research

paper

From

3D

landscape

visualization

to

environmental

simulation:

The

contribution

of

sound

to

the

perception

of

virtual

environments

Mark

Lindquist

a,∗

_,

_Eckart

_Lange

b

_,

_Jian

_Kang

b

a_University_of_Michigan,_United_States b_University_of_Shefﬁeld,_United_Kingdom

h

i

g

h

l

i

g

h

t

s

•Soundsigniﬁcantlyaltersperceptualresponsesto3Dlandscapevisualizations.

•Realismandpreferencearemoderatedbycongruencyofvisualandsoundcontent.

•EyelevelGoogleEarthvisualizationsreceivelowrealismratings.

•Aural-visualsurveydatacollectedviathewebiscomparabletolaboratorydata.

•Soundandvisualsthatarespatiotemporallycongruentarerecommendedforsimulations.

a

r

t

i

c

l

e

i

n

f

o

Articlehistory:

Received28November2014 Receivedinrevisedform 19December2015 Accepted29December2015 Availableonline29January2016

Keywords:

Aural-visualinteraction Environmentalperception Landscape

Visualization Soundscape Virtuallandscapes

a

b

s

t

r

a

c

t

Thisresearchinvestigatedtheperceptualinteractionofcombiningsoundwith3Dlandscape visualiza-tions.ImagessourcedfromGoogleEarthatSt.James’sPark,London,UK,showingterrainonly,terrainwith builtformorterrainwithprimarilyvegetationwerepairedwithfoursoundconditionsusingrecordings fromthepark(i.e.‘nosound’,anthropogenic,mechanicalandnatural).Perceivedrealismandpreference wereevaluatedusingasurveydeliveredviatheInternetandinacontrolledlaboratoryenvironment (N=199total).AnalysisusingrepeatedmeasuresANOVAindicatedtheinteractionofsoundand3D visualizationssigniﬁcantlyaltersenvironmentalperceptionbothpositivelyandnegatively.Soundsand visualsthatarecongruentreceivehigherrealismandpreferenceratingswhilethemoreincongruent thecombinationis,thelowerthecorrespondingratings.Thelowestrealismandpreferenceratingsare giventovisualizationsshowingterrainonlycombinedwithspeech.Thehighestrealismratingsoverall correspondtovisualizationwithbuiltformcombinedwithspeech,andvisualizationsshowing primar-ilyvegetationpairedwithabirdcall.Theabsolutehighestrealismratingwasforthevisualizationwith primarilyvegetationandsomebuiltformpairedwithspeech,whilethehighestpreferenceratings corre-spondtovisualizationsshowingvegetationpairedwithbirdcallornosound.Aural-visualdatacollected viatheweb-basedsurveywascomparabletodatacollectedinthelaboratoryandoverallrealismratings fortheGoogleEarthvisualizationswerelow(e.g.below3ona1–5likerttypescale).Theresultssuggest thereisanopportunitytoincreaseexperientialauthenticityof3Dlandscapevisualizationswithsound. ©2016TheAuthors.PublishedbyElsevierB.V.ThisisanopenaccessarticleundertheCCBY-NC-ND license(http://creativecommons.org/licenses/by-nc-nd/4.0/).

1. Introduction

Three-dimensional digital visualization of landscapes offers manyadvantages over conventional methodsof representation, particularlywhencommunicatingcomplexspatialarrangements

∗_{Corresponding}_author_at:_Mark_Lindquist,₂₅₃₂_Dana_Building,_School_of_Natural ResourcesandEnvironment,UniversityofMichigan,440ChurchStAnnArbor,MI 48109-1041,UnitedStates.

E-mailaddresses:[email protected](M.Lindquist),e.lange@shefﬁeld.ac.uk (E.Lange),j.kang@shefﬁeld.ac.uk(J.Kang).

tonon-designers(Bishop,2005;Kwartler,2005).Todate prepar-ersandpresentersof3Dvisualizationshaveprimarilyfocusedon visualaspectsoflandscapes, inpartbasedonthedominanceof thehumanvisualsystem(Lange&Bishop,2005).However,purely visualapproachestolandscapeexperiencehavebeencriticized. Forexamplethecomplexmulti-sensoryappreciationof individ-ualsforlandscapeshasbeendemonstrated(Scott,Carter,Brown,& White,2009)ashastheimportantimpactofsoundonthe evalua-tionofoutdoorenvironments(e.g.Anderson,Mulligan,Goodman, &Regen,1983;Carles,Barrio,&deLucio,1999).Theresearch pre-sentedhereaimstoforegroundmultisensorylandscapeexperience

http://dx.doi.org/10.1016/j.landurbplan.2015.12.017

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The impact of sound on the perception of environments is increasinglyunderscrutiny.Interestbygovernmentand policy-makersisgrowinginthisarea,particularlyintheregulationand abatementofsoundintheformofenvironmentalnoisefromroad traffic,aircraft,railwayandmachineryandtheirimpactonhealth and safety(Directive2002/49/EC,2002).Theconcept of sound-scapeasfirstsuggestedbySchafer(1977)hasdevelopedintoan areaofresearchconcernedwithstudyingtheimpactofsoundboth positivelyand negativelyonanenvironmentanditsperception. Soundscapesdefined asthe“acoustic environmentasperceived orexperiencedand/orunderstoodbyapersonorpeople,in con-text”(ISO12913-12014,2014).Agrowingbodyofknowledgeis emergingthroughempiricalstudyofsoundscapeintheurban envi-ronment,particularlyurbanplazas(Yang&Kang,2005a)andgreen spaces(Irvineetal.,2009;Nilsson&Berglund,2006).

Landscapearchitectsandplannershaverecentlyturnedtheir attentiontodesigningand planningsoundscapes.Auditory con-cepts for soundscape design and planning have been outlined (Hedfors&Berg,2003)andusedtocreateatoolkitforprofessionals (Hedfors,2003).Intheareaoflandscapeplanningand manage-menttherehavebeenadvocatesforaudiodesign(Brown&Muhar, 2004)aswellasauditoryplanning(Brown,2004).Morerecentlythe soundscapeapproachhasbeenappliedtoearlystageurban plan-ning(DeCoenseletal.,2010)withframeworksforfutureresearch andpracticalneedsoutlined(Kang,2010).

1.2. 3Dlandscapevisualization

Landscapevisualizations are made upof fundamental land-scapeelementsthatarerenderedin3Dtoapproximatethevisual qualitiesof a landscapeand usually includeterrain, vegetation, builtformandwater,andcanbeexpandedtoincorporateanimals (includingpeople)andatmosphere(Ervin,2001).Theseelements contributedifferentlytoperceivedrealismofthelandscapebeing represented,asdoestheirrelativedistancefromanobserversview. Forexample,researchhasshownthatforegroundscenesarerated morerealistic thanmiddle groundorbackgroundscenesatthe samelevel of detail (Lange, 2001).In addition,theinclusion of texturemapsonbothterrainandbuiltformcangreatlyincrease perceivedrealismwhencomparedtosimplegeometry(Appleton& Lovett,2003;Lange,2001;Oh,1994),whilethelandscapeelements thatmostaffectperceivedrealismhavebeenshowntobebuiltform andvegetation(Bishop&Rohrmann,2003).Differentuser charac-teristicshaveshowntoaltertheperceptionof3Dvisualizations: familiaritywithasite canalterpreference ratings(Lange, Hehl-Lange,&Brewer,2008)aswellasaffectingperceivedrealismofa visualizations(Appleton&Lovett,2005;Karjalainen&Tyrväinen, 2002;Lange,2001).Professionalbackgroundcanalsoalterrealism andpreferenceratings,withbuiltenvironmentand environmen-talprofessionalsdifferingfromlaypeopleintheirratingsforboth realismandpreference(Langeetal.,2008;Lange,2001).In addi-tion,familiaritywith3Dgraphicsingeneralandexperiencewith 3Dgraphicsinaplanningcontextcanbothresultinhigherrealism ratingsofvisualizations(Appleton&Lovett,2003).

1.3. Empiricalsoundscapeandlandscaperesearch

Sensesbeyondvisioncanhaveasigniﬁcantimpactonour per-ceptionofandinteractionwithourenvironment.Empiricalstudies havedemonstratedacorrelationbetweentheintensityofsound pressurelevel(SPL)asmeasuredindecibels(dB)andsubjective

turalbackgroundandlong-termenvironmentalexperience(Yang &Kang,2003),ﬁndingthatalignwithresearchonnoise sensitiv-itydemonstratingconsiderableindividualvariationandabilityto adapttonoise(Weinstein,1978).

Landscapeperceptionresearchhasshownthattheinteractions ofaudioandvisualstimulihaveasignificantimpactonvisualand audio–visualresponsestobothrealandphotographedsettings.In onestudyparticipantsratedhowenhancingordetractinga par-ticular soundwastoa landscape both insitu, via photography and description,the resultsof which indicated sounds congru-ent withvisuals were mostenhancing (Anderson et al., 1983). Soundhasalsoshowntoinfluenceoverallenvironmental evalu-ationbothnegativelyandpositively,withcombinationofnatural soundsandimagespreferredovermechanical(Carlesetal.,1999; Carles, Bernáldez,& deLucio, 1992). In addition,the combina-tion of motion and sound have demonstrated to beimportant for reliable judgment of dynamic landscapesvia scenic beauty assessment(Hetherington,Daniel,&Brown,1993).Aircraftnoise in anatural parksetting wasshowntohave anegative impact onresponsestoscenicbeauty,landscapepreference,naturalness andsolitude(Mace,Bell,Loomis,&Hass,2003).Inanotherstudy the presence of anyanthropogenic sound wasshown to nega-tivelyimpactlandscapepreferenceratings,whilenaturalsounds hadnoimpact(Benfield,Bell,Troup,&Soderstrom,2010).Sound hasalsobeenshowntoalterthesubjectiveperceptionoftranquil spacesinneurosciencebasedresearchusingfMRI(Hunteretal., 2010).Through self-reportedand physiological measures these earlierstudiesmadevaluableresearchcontributionsontheeffects ofsoundonperceptionofreallandscapesusingphotographsand videos.However,byfocusingonreallandscapestheydonotdirectly inform processesfor theevaluation offuture landscape change that3Dvisualizationsoffer.Aframeworkhasbeenproposedby theauthorsforcombiningsoundwith3Dlandscapevisualizations (omittedforBLINDreview)andthecurrentstudyaimedto pro-videempiricalevidenceofthecontributiontoperceivedrealism andpreferenceevaluationsofacomputersimulatedenvironment whenpairingrealsoundswith3Dlandscapevisualizations.

1.4. Researchquestionsandhypotheses

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Fig.1.Experimentimagecombination,perview.

professional background) and preference (age, cultural back-ground,noisesensitivityandsitefamiliarity).Finallywe hypoth-esized that online results would not differ signiﬁcantly from laboratoryresults.

2. Methods

2.1. Participants

Atotalof252respondentsparticipatedintheexperimentwith 199completingtheentiresurvey(114/57.3%female)aged18–71 (M=31.31,SD13.19).Previousstudiesexaminingtheperception ofaural–visualstimuliinalabsettinghaveusedasfewas20 par-ticipants(e.g.Hong&Jeon,2014)thoughthenumberofoverall participantsissimilartopreviousstudiesthatevaluatedweb-based landscapepreferencedatacollection(e.g.Wherrett,2000).Inour study71 participated in the laboratory-based experiment;128 online.Laboratory-basedparticipantswererecruitedbythe Uni-versitysubjectpoolemaillistandbypersonalcontacts,andwere eligibletobeenteredinadrawtowina

£

50voucher.Online par-ticipantswererecruitedviaFacebookandtheUniversitysubject poolemaillistandofferedtheopportunitytobeenteredintoa drawtowina

£

25voucher.Meantimetocompletethesurveywas

13.37minwitharangefrom6.83to27.95min.Allresearch con-ductedwasapprovedthroughtheappropriateinstitutionalethics procedures.

2.2. Apparatusandmaterials

2.2.1. Selectionofstudyarea,visualandauralstimuli

Oneoverarchingaimofthecurrentresearchwastoassessthe perceptionofvisualizationssourcedfromtoolsusedbyavariety ofspatialandscientiﬁcresearchersandpractitioners.GoogleEarth wasusedasasourceforthevisualstimulibecauseitisoneofthe mostubiquitous3Dvisualizationtoolsandisbeingusedinmany environmentalevaluationcontexts(e.g.Schrothetal.,2011)butis lackingindepthperceptualevaluation.Asaresultthestudyarea selectionwasinformedbyphysicalaspects(e.g.accessibility, suit-abilityoftheenvironment)aswellastechnologicalaspects(e.g. landscapeelementsavailablein GoogleEarth). St.James’s Park, London,UKwasselectedforthestudysitebecauseithad:(a) pho-torealisticvegetationwithinthepark;(b)photorealisticbuiltform surroundingtheparkforcontext;(c)relativelyhighdetailinthe terrainimagemapping;and(d)rigoroussurveysandcountson visi-tornumbersandusersatisfaction.St.James’sParkisoneoftheeight RoyalParksofLondonlocatedintheCityofWestminster.Thepark

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Fig.3. RecordingandmeasurementlocationsinSt.James’sPark.

covers23hectaresandisboundedbyBuckinghampalace,TheMall andSt.James’sPalace,HorseGuardsandBirdcageWalk.Itincludes asmalllakewithmeanderingpathsandabridge(SJPaerial1kml). St.James’sParkwasthesecondmostvisitedoftheRoyalParksin 2007with6.4millionvisitorstoHydePark’s7.1millionvisitors (Hitchcock,Curson,&Parravicini,2007).

2.2.2. Visualstimuli

Theimageschosenforthestudyweredrawnfromadatabaseof 100imagestakenfrom3Deye-levelviews(i.e.foreground,0–800m (U.S.ForestService,1995))withinGoogleEarthonthestudysite. Viewpointswereselectedaccordingtothefollowingcriteria:(a) showingarepresentativecross-sectionofthesite;and(b)varying ineachimagethevisualamountofbuiltform,terrainand vegeta-tion(e.g.Appleton&Lovett,2003).Threeviewsrepresentativeof thesitewereidentified(view1:primarilyvegetationwithapath; view2:primarilyvegetationwithsomebuiltform;view3: primar-ilyvegetation).Threevisualrepresentationvariableswerechosen forthisresearchthathavebeenidentifiedashavingasignificant impactonperception ofvisualizationsin previousstudies: ter-rain,builtform(e.g.Lange,2001);andforegroundvegetation(e.g. Appleton&Lovett,2003).EachimagewasexportedfromGoogle EarthProata1080pHDTVratio,ata4800×2700pixel.jpgfileto bescalabletofilla1080p(1920×1080pixel)monitor.The combi-nationofelementscontributingtothedifferentvisualconditions usedintheexperimentareillustratedinFig.1andtheninespecific viewsareillustratedinFig.2(view1kml,view2kml,view3kml).

2.2.3. Acousticstimuli

Foursoundconditionswereusedintheexperiment:nosound, anthropogenic sound (human speech), mechanical sound (road

trafﬁc),andnaturalsound(birdcallofaCootFulicaatra)(e.g.Liu, Kang,Behm,&Luo,2014;Liu,Kang,Luo,&Behm,2013).Thesounds weredrawnfrom24recordingsrecordedinSt.James’sParkatfour times(0700,1200,1700and2200)overtwodays(17–18July2012) acrosssixsites(withaseventhsiteontheperipheryoftheparkalso recordedforacomparisonofsoundlevel)(Fig.3).Thesiteswere chosenafteraninitialwalk-throughoftheentireparkandwere evenlydistributedalongacommonroute.

SoundswererecordedwithanEdirolR-444-channelportable recorder in hi-fidelity(48kHz samplingrate, 24-bitresolution) using1channel,amonomicrophone,with“Lowcut”andthelimiter switched onto compensate for wind noise. LAeq was simulta-neouslymeasuredwitha 01dB Solo SoundLevelMeter, which wascalibratedusinga01dBCal01SLthatplayeda94dB1000Hz tone.Thecalibratorwasalsousedtorecorda10ssegmentatthe beginningofeachrecordingenablingcalibrationwiththeHEAD AnalyzerArtemiS11.0.200psychoacousticanalysissoftware(Head Acoustics,2012).Recordingswerebetween140sand150s(120s recording;10scalibration;and5–10sremovingthecalibratorand fittingmicrophonewindguard).Thesoundsusedforthe exper-iment wereselected byidentifyingsoundsexhibiting the most extremedifferencesbyanalysisofLeq,Lmaxandfour psychoa-cousticvariablesofsharpness,fluctuationstrength,loudnessand roughness(Kang,2007)andselectingsounddifferentsound con-tent. The intent in selecting thedivergent sound types was to provide a temporal soundscape variation approximate to what wasuncoveredthroughasoundscapeanalysisofSt.James’sPark conductedbyoneoftheauthorsratherthanspecifically match-ingsoundand3Dvisualizationviewlocations.Thelocation,time andpropertiesofthesoundsusedintheexperimentareshownin Table1.

Table1

Location,time,acousticandpsychoacousticpropertiesofthe3soundsusedintheexperiment.

Loc Time Leq Lmin Lmax StdDev Sharpness Fluctuation Loudness Roughness Content (acum) (vacil) (sone) (asper)

4 700 60.8 55.3 64.6 2 2.39 0.009 37.1 3.32 mechanical

2 1200 56.1 54.3 58.7 0.9 1.99 0.013 30.5 2.86 anthropogenic

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Table2

Onlineexperimentparticipanthardware(Display;Audiodevice).

Displaysize Freq (%) Audiodevice Freq (%)

Monitor:13_–21” ₉₃ _72.7 _Built-in_laptop_speakers ₃₇ _28.9

Monitor:22”–27” 21 16.4 Earbuds 22 17.2

Unsure 5 3.9 In-earmonitors 20 15.6

Monitor:lessthan13” 4 3.1 Desktopcomputerspeakers 17 13.3

iPad/tablet 3 2.3 On-earheadphones 10 7.8

Monitor:largerthan27” 2 1.6 Built-inmonitorspeakers/soundbar 9 7.0

Total 128 100 Over-earheadphones 9 7.0

Highqualityspeakers 2 1.6

Other 2 1.6

Total 128 100

2.2.4. Questionnairedesign

In the main section of the survey respondents were asked to indicate their ratings for realism and preference on a 5 itemlikert-type scale(“How realisticis your experienceof this environment?”—1:not,2:slightly,3:somewhat,4:quite,5:very; “How much do youlike this environment?”—1: notat all,2: a little,3:moderately,4:quitea bit,5:verymuch).Verballabels wereassignedfollowingguidelinesbyRohrmann(2007)forevenly spacedlinguisticseparation.Sitefamiliaritywasgaugedas recom-mendedbyGale,Golledge,Halperin,&Couclelis(1990)usingatwo valuerating(familiarityandfrequencyofvisits)withrespondents shownbothanaerialandgroundlevelphotographofSt.James’s Parkandaskedtwoquestions:(1)AreyoufamiliarwithSt.James’s Park?;and(2)ApproximatelyhowoftendoyouvisitSt.James’s Park?.Noisesensitivitywasassessedusingavalidated5-item sur-veydevelopedbyBenﬁeldetal.(2012)anddirectquestionsasked toassess3Dgraphicsfamiliarity,experiencewith3Dgraphicsina designorplanningprocess,professionalbackgroundandcultural background.

2.2.5. Apparatus

The laboratory-based part of the experiment used a dual workstation setup. Each workstation was identical except for theaudioplaybackhardware:colour calibratedDellUltrasharp 2209WAmonitorconnectedtoaPCwiththemonitorandviewing

environmentadheringtotheISO36642009speciﬁcationswith ambientlightateachworkstationsetto50lux(+/−0.7)andlight output of each monitor measuredat 155(+/− 1) lumens (ISO 36642009,2009).Theresultingon-screenstimulusimagesizewas 31.04cmwidth×17.46cmheight(880×495pixels).Workstation 1used‘high quality’audiohardware (SennheiserHD598 over-earheadphones);workstation2used‘lowquality’audiohardware (ﬁrstgenerationAppleearbudswithnoremoteormic).SPLofthe roomwas34.1dB(A)andtheSPLfromeachsetofaudiohardware werematchedusingaNeumannKU100DummyHeadtomeasure andsetplaybacklevel.

Theapparatususedfortheonlinestudywasself-reportedby eachparticipantduringthedemographicpartoftheonline sur-veyfordisplaysizeand audiodevice(Table2).Theexperiment was delivered via web browser using an online questionnaire (SurveyGizmo,2012)withanexampleoftheonscreeninterface showninFig.4.

2.3. Experimentalprocedure

Theoverall ﬂow of thesurvey is illustratedin Fig.5. Inthe laboratoryconditionparticipantsread aninformationsheetand signedaconsentform,thenwererandomlyassignedtoeitherthe highorlowqualityheadphoneconditionbyselectingoneoftwo piecesofpaper.Allparticipants: (a)answeredpreliminaryuser

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Fig.5.Flowdiagramofthewebquestionnaire.

characteristicquestions;(b)ratedthethreesoundsforthe per-ceivedlevelofloudnessandtheirpreferenceforthatsound;(c) werepresentedwith4samplesetsofstimuli(twoimage/sound conditions,twoimageonlyconditions)tofamiliarizethemselves with the procedure (Lange et al., 2008; Reips, 2002); and (d) werethenpresentedwiththeaural–visualcombinations.The36 differentaural–visual combinations wererandomlyassigned to participantsaccordingtoa3(visual)×3(view)×4(sound)factorial design.Soundswereplayedfor8sduration,followedby partic-ipants indicating their perceivedrealism and preference.Online participantsfollowedtheaboveprocedurewiththeexceptionof: (1)Theconsentformwasdisplayedandagreedtoonscreen;(2) Beinginstructedtomaximizetheirbrowserwindow;(3) Indicat-ingtheirmonitorsizeandaudiohardware;(5)Beinginstructedto useasampleaudiocliptoadjustingtheirvolumetoacomfortable level.Apilotstudyrevealedpotentialconfusionfromparticipants relatingtoterminologyofheadphonetypesaswellaswhenasked tosettheirvolumethereforevisualcueswereaddedtothose ques-tionsforassistance.Theonlinesurveycanbeaccessedathttps:// www.surveygizmo.com/s3/2314737/VSS-p1-p56-ONLINE-LAUP.

Toreducedropoutandthenegativeimpactofdropoutonthe surveydatasixmeasureswereusedthatwereadaptedfromRoth (2006)whicharepresentedinTable3.Inclusioncriteriawerethat participantshadtoexhibitattentivenessbynothavingan exces-sivelylongdurationonthemainsurveyquestions(i.e.lessthan30s forthe36sound/imagecombinations).

2.4. Statisticalanalysis

Theanalysiswascompletedinthreeparts.Partoneemployeda mixedrepeatedmeasuresANOVAtoevaluatetheeffectof exper-imentalconditionandaudiovisualhardwareonresponseswith betweensubjectfactorsbeing“experimentcondition”(2levels), “audio device”(2levels), and“display size” (2levels).Part two employedarepeatedmeasuresANOVAtoevaluatetheeffectofthe withinsubjectindependentvariables onrealismandpreference ratings,aswellastheirinteractions(withinsubjectsfactorswere “view”(3levels), “visualcondition”(3levels)and “soundtype” (4levels)).PartthreeusedamixedrepeatedmeasuresANOVAto informhypothesisgenerationforfutureresearchareas.Post-hoc testswereusedtodetermineifanysigniﬁcantdifferencesexisted betweengroupsinthemixedANOVAwithaBonferronicorrection usedtocontroltheerrorrate.Thereissomecontroversy surround-ingeffectsizeforANOVAsasthereisevidencethatetasquaredhas beenmisreportedinthepastincommunicationsresearch(Levine &Hullett,2002)whichislikelytobethecaseforlandscape pref-erencestudies.Alternativeseffectsizeshavebeendeveloped(e.g. Bakeman,2005;Olejnik&Algina,2003)howevernotforthecurrent studiesdesign.Asaresult,effectsizeisreportedhereinpartialeta squared(p2)asthisisconsistentwithpreviouslandscape pref-erenceresearchandrecommendedwhenothermethodsarenot feasible(Lakens,2013),whichallowsforcomparisonwithstudies thatuseasimilardesign.AnalysiswasconductedinSPSS21 (ver-sion21.0.0.2).Thedatawasassessedfornormalitybyinspectionof

absolutevaluesforskew(<2.0)andkurtosis(<4.0)(West,Finch,& Curran,1995).Nosubstantialdeparturefromnormalitywas indi-catedforthedata.Violationsofsphericityarecontrolledusingthe Greenhouse-Geissercorrectionvalue,whichisincludedinall fol-lowingtableswhenthesphericitytestissigniﬁcant.Additionally themixedANOVAwereanalysedforhomogeneityofvarianceusing Levene’stest(Levene,1960),ﬁndingthattherewashomogeneity ofvarianceforthemajorityofresponsesforquestionresearch2 (479/576,83.2%)andresearchquestion3(204/216,94.4%).This wasdeemedacceptableasANOVAisrobustagainstreasonable vio-lationsofvariance,especiallywhengroupsizesarerelativelyequal (Howell,2012).

3. Results

3.1. Onlinevs.laboratoryparticipation

In order to determine the suitability of the Internet for aural–visualexperiments3factorswereanalysed:experimental condition,audiohardwareanddisplaysize.Theanalysisfocusedon themaineffectofeachbetween-subjectsfactor,andtheinteraction ofthebetween-subjectsfactorwitheachindependentvariableof view,visualconditionandsound.Forexperimentalconditionthe combineddatawereanalysedfordifferencesoccurringbetween laboratory(N=71)andonlineparticipants(N=128)revealingno signiﬁcantmaineffectsorinteractions(p>.05forall).Inthe labo-ratoryconditionparticipantswererandomlyassignedtoeitherthe highquality(N=37)orlowquality(N=34)audiohardware appa-ratus,theanalysisofwhich revealednosigniﬁcantmaineffects orinteractions(p>0.05forall).Thecombineddata(N=199)was analysedtodetermineanyeffectofdifferingvideodisplay hard-waresizeonresults.Alllaboratory-basedparticipantsuseda22” monitor,whileonlineparticipantsindicatedthedisplaysizeaspart ofthesurvey(Table2).Thefrequencyofdisplaysizesusedinthe experimentisillustratedinFig.6.

Themajorityofparticipantsusedamonitorbetween13”and 21”(93/199or46.7%)followedcloselybyamonitorbetween22” and27”(92/199or46.2%).Asaresulttheanalysiswaslimitedto

93 92 5

4 3 2

0 20 40 60 80 100

Monitor: 13"-21" Monitor: 22"-27" Unsure Monitor: less than 13" iPad/tablet Monitor: larger than 27"

frequency

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Table3

Measurestakentoreducedropoutandtoreducethenegativeimpactofdropout(adaptedfromRoth,2006).

Measure Description

High-hurdletechnique Thedemographicdata(personalization)werecollectedbeforetheevaluationofthestimuli

Warm-uptechnique Thecollectionofpersonaldataandpracticingstimulusratingbeforetherealexperimentstartensuresthatthedata collectedintheexperimentalphasecomesfromthemostlyhighlycommittedparticipants

Incentive Participantsweregiventheopportunitytobeenteredinadrawforagiftcertiﬁcate(£25online,£50laboratory participation)

Noplug-ins Noplug-insareneededfortheuser’sPC,thesurveyworkswithallmodernwebbrowsers.

Two-item-one-screendesign Eachratingtakesplaceonaseparatewebpage.Theresultsaretransferredandsavedtodatabaseimmediatelyafter clickingthesubmitbutton.Iftheparticipantdropsout,theformerresultsandthepointoftimeofdropoutcanbe examined

Recordofresponsetimeperpage Theresponsetimeisrecordedforeachwebpage/eachrating.Ifdataqualitysuffersfrominterruptionsofthe experiment,thiscanbeidentiﬁed

thosetwovariablesastherewerenotenoughresponsesintheother categoriestomeettheassumptionofthemixedANOVA.Themain effectandinteractionsofdisplaysizeonrealismandpreference ratingswasnotsigniﬁcant(p>0.05forall)apartfromthe interac-tionofdisplaysizebyviewforpreference:F(2,362)=4.71,p=0.010, p2=0.025.Visualinspectionindicatedthatparticipantswith dis-playsbetween13”and21”ratedallviewssimilarly,whilethose withdisplaysbetween22”and27”ratedpreferencesigniﬁcantly higherforviews1and2thanthosewithmonitorsbetween13”and 21”.Thismanifestedinameandifferencesof0.09onthe5-point ratingscaleandaverysmalleffect.Becausetheeffectwassmallit wasconcludedthattheindependentvariablesinthisinstancedid notdramaticallyaffectresults,andfurtheranalysiswasconducted onthecombinedsample.

3.2. Meanrealismandpreferencescoresbyallparticipants

Participants ratedthe three soundswithout visuals for per-ceivedloudnessand preference atthebeginning of thesurvey. Duringincrementalprototypingparticipantswereaskedtoratethe soundsforrealismandpreference,however,manyindicatedsome confusionbeingaskedtoratethesoundforrealismsothiswas omittedfromthemainsurvey.TheresponsesareshowninTable4 andwereinlinewithpreviousstudiesindicatinghigherpreference for natural soundsover anthropogenic sound,with mechanical soundsleast preferred. Interestinglythe sound content had an effectonperceivedloudnessasallsoundsusedintheexperiment werematchedforloudness.

Table5presentsallmeansandstandard deviations for real-ismandpreferenceratingsforall36combinationsofview,visual conditionandsound,aswellasthecorrelationbetweenrealism andpreferenceratings.Theoverallresultscanbesummarizedas follows:

Thelowestrealismandpreferenceratingsbothcorrespondto visualcondition1(terrainonly)+speechwithmeanscoresfor real-ismrangingfrom1.33to1.42andforpreferencefrom1.51to1.54. The highest realism ratings consistently correspond to two combination:visualcondition2(builtform)+speech;andvisual condition 3 (primarily vegetation)+natural sound,with mean scoresrangingfrom2.62to2.82.Onenotableexceptionisview 2+visualcondition3+speech,whichhappenstohavethehighest meanscoreforrealismat2.85whilethesamecombinationforview

Table4

Meanloudnessandpreferenceratingsofsoundsusedintheexperiment.

Source Loudness Preference

Mean SD N Mean SD N

Trafﬁc 2.68 0.95 199 2.02 1.02 199

Speech 2.42 0.98 199 2.24 0.93 199

Nature 2.09 0.87 199 2.97 1.04 199

3scores2.26.Thiscanpossiblybeexplainedbythesmallamountof builtformvisiblebehindthevegetationthatwhenviewedwiththe speechsoundindicatesthepresenceofhumanssomewhereoutof thescene.

Thehighestpreferenceratingsconsistentlycorrespondtotwo combinations:visualcondition3(primarilyvegetation)+nosound; andvisualcondition3+naturalsound,withmeanscoresranging from2.95to3.13forbothcombinations.Finally,realismand pref-erencescoreswerepositivelycorrelated forall36combinations withrrangingfrom0.399to0.832,allsigniﬁcantatp<0.01.

3.3. Analysisofvarianceofmeanrealismandpreferencescores

Themeanswereanalysedviaathreefactorwithinrespondents ANOVAwiththefactorsdefinedas“view”(3levels);visual condi-tion(3levels)andsound(4levels).Theoverallresultsforrealism andpreferenceareshowninTable6.Allmaineffectsand interac-tionsweresignificant(p<0.05forall)withvisualconditionhaving thelargesteffectforrealismandpreferenceaswellasthe interac-tionhavingarelativelystrongeffect.Thedatawasanalysedfurther byisolatingeachvisualconditionbythelevelofthevariables“view” and“sound”,separatelyforeachdependentvariable“realism”and “preference”,withposthoccontrastsusedtoidentifysignificant effects.Fig.7illustratesthemeanrealismandpreferenceratings byview,visualconditionandsound type,withthefullANOVA andcontrasttablesforrealismshowninTable7andpreference inTable8.

3.3.1. ANOVAandcontrastsforrealismscores

ANOVAandcontrasts for realismareshown inTable7 ana-lysedseparatelyforeachvisualcondition.Forvisualcondition1 themaineffectof‘sound’wassignificant(p<0.001)thoughnot themaineffectof‘view’(p<0.307)ortheinteraction(p<0.301) thereforethedatawascollapsedacrossviewwithmeanrealism ratingscomputedforeachleveloftheindependentvariablesound. Contrastsrevealedsignificantdifferencesbetween4ofthe6sound conditions(p<0.001,Table7),theexceptionbeing‘nosoundvs. traffic’(p<0.179)and‘trafficvs.nature’(p<0.82).Therelationship isillustratedinFig.7,showingthat‘speech’receivesthelowest overallrealismrating(M=1.40,SD=0.62)whichwassignificantly lower than allthe othersound conditions (no sound: M=1.80, SD=0.95, p<0.001;traffic: M=1.93, SD=0.91, p=0.001;nature: M=2.01,SD=0.90,p<0.001),withthelargestdifferencebetween ‘speech’and‘nature’(p2=0.378).

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Mean SD Mean SD

1 1 Nosound 1.73 0.99 1.87 1.08 0.787**

Trafﬁc 1.94 1.06 1.72 0.91 0.669**

Speech 1.41 0.73 1.54 0.77 0.444**

Nature 1.98 0.97 2.15 1.05 0.731**

2 Nosound 2.37 0.99 2.62 1.02 0.649**

Trafﬁc 2.51 1.04 2.25 1.01 0.480**

Speech 2.82 1.11 2.56 1.00 0.509**

Nature 2.41 1.06 2.63 1.03 0.673**

3 Nosound 2.57 1.12 3.01 1.10 0.670**

Trafﬁc 2.43 1.07 2.39 0.97 0.472**

Speech 2.39 1.07 2.36 0.92 0.550**

Nature 2.76 1.15 3.07 1.07 0.635**

2 1 Nosound 1.84 1.03 2.06 1.11 0.789**

Trafﬁc 1.94 1.03 1.89 0.99 0.620**

Speech 1.42 0.76 1.56 0.78 0.518**

Nature 2.02 1.03 2.29 1.12 0.719**

2 Nosound 2.29 1.04 2.44 1.00 0.651**

Trafﬁc 2.51 0.99 2.11 0.93 0.399**

Speech 2.76 1.17 2.49 0.95 0.542**

Nature 2.26 1.03 2.45 1.02 0.680**

3 Nosound 2.63 1.04 2.95 1.03 0.600**

Trafﬁc 2.59 1.09 2.44 0.97 0.423**

Speech 2.85 1.07 2.72 1.01 0.563**

Nature 2.75 1.07 3.00 1.04 0.619**

3 1 Nosound 1.8 1.04 1.97 1.08 0.832**

Trafﬁc 1.89 1.08 1.83 1.03 0.677**

Speech 1.33 0.68 1.51 0.75 0.459**

Nature 2.02 1.02 2.23 1.14 0.779**

2 Nosound 2.22 0.97 2.22 0.90 0.613**

Trafﬁc 2.41 0.97 2.01 0.85 0.438**

Speech 2.62 1.08 2.29 0.84 0.510**

Nature 2.19 0.97 2.28 0.99 0.612**

3 Nosound 2.63 1.12 3.13 1.07 0.615**

Trafﬁc 2.24 1.10 2.24 1.01 0.557**

Speech 2.26 1.10 2.35 0.97 0.529**

Nature 2.81 1.10 3.06 1.06 0.693**

Table6

ANOVAresultsforrealismandpreference,allparticipants.

Source SS df MS F Sig. p2 εa

Realism Maineffects

view 17.45 2,394 8.72 17.14 <0.001 0.080

visualcondition 874.35 1.56,307.72 559.75 126.93 <0.001 0.392 0.781

sound 22.50 2.53,498.43 8.89 6.35 0.001 0.031 0.843

Two-wayinteractions

view×viscond. 15.43 4,788 3.86 7.49 <0.001 0.037

view×sound 14.33 6,1182 2.39 6.79 <0.001 0.033

viscond×sound 231.27 5.23,1029.38 44.26 46.54 <0.001 0.191 0.871

Three-wayinteraction

view×viscond×sound 19.03 10.31,2030.98 1.85 4.56 <0.001 0.023 0.859 Preference

Maineffects

view 15.29 2,392 7.65 13.57 <0.001 0.065

visualcondition 840.16 1.53,299.81 549.26 145.71 <0.001 0.426 0.765

sound 291.36 2.74,536.23 106.50 55.84 <0.001 0.222 0.912

Two-wayinteractions

view×viscond 33.84 3.74,732.01 9.06 16.32 <0.001 0.077 0.934

view×sound 5.75 5.63,1103.20 1.02 2.87 0.011 0.014 0.938

viscond×sound 131.18 5.57,1091.61 23.55 37.14 <0.001 0.159 0.928

Three-wayinteraction

view×viscond×sound 20.90 10.85,2125.76 1.93 5.30 <0.001 0.026 0.904

SS=TypeIIISumofSquaresdf=degreesoffreedom;MS=MeanSquareF=Fratio;Sig.=signiﬁcance;p2=partialetasquared(effectsize).

a_A_value_in_this_column_indicates_{Mauchly’ssphericity}_test_was_{signiﬁcant,}_and_the_indicated_{Greenhouse-Geisser}_correction_applied_to_the_results._{Signiﬁcance}_(at_0.05)

isinbold.

1and2acrossallstimulicombinationsforvisualcondition2,with meanscoresrangingfrom0.10to0.18lower,whiletheeffectof eachsoundconditionwasconsistentacrossviews(e.g.Fig.7). Con-trastsrevealedsimilarsigniﬁcantdifferencesbetween5ofthe6

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Table7

ANOVAandcontrastsforrealismbyvisualcondition.

Source SS df MS F Sig. p2 ␧a

Visualcondition1 Maineffects

sound 132.24 3,594 44.08 45.5 <0.001 0.187

Interactions

view×sound 1.93 5.58,1104.85 0.35 1.21 0.301 0.006 0.93

Contrastsb

nosoundvstrafﬁc 3.49 1,198 3.49 4.79 0.179 0.024

nosoundvsspeech 31.89 1,198 31.89 43.59 <0.001 0.18

nosoundvsnature 8.86 1,198 8.86 15.58 0.001 0.073

trafﬁcvsspeech 56.46 1,198 56.46 83.44 <0.001 0.296

trafﬁcvsnature 1.23 1,198 1.23 2.23 0.82 0.011

speechvsnature 74.39 1,198 74.39 120.56 <0.001 0.378

view 11.54 2,396 5.77 10.81 <0.001 0.052

sound 78.5 2.85,563.29 27.59 30.33 <0.001 0.133 0.948

Interactions

view×sound 1.47 5.61,1110.07 0.26 0.64 0.684 0.003 0.934

Contrastsb

Views

view1vsview2 1.02 1,198 1.02 4.11 0.132 0.02

view1vsview3 5.72 1,198 5.72 20.67 <0.001 0.095

view2vsview3 1.91 1,198 1.91 6.95 0.027 0.034

View1&2collapsed

sound 27.67 3,594 9.22 25.56 <0.001 0.114

nosoundvstrafﬁc 6.33 1,198 6.33 9.58 0.014 0.046

nosoundvsnature 0.01 1,198 0.01 0.02 1 0

trafﬁcvsspeech 15.76 1,198 15.76 24.52 <0.001 0.11

trafﬁcvsnature 5.81 1,198 5.81 7.14 0.049 0.04

speechvsnature 40.7 1,198 40.7 47.61 <0.001 0.19

sound 23.6 2.855 8.27 16.29 <0.001 0.076

nosoundvstrafﬁc 7.29 1,197 7.29 7.46 0.034 0.036

nosoundvsnature 0.18 1,197 0.18 0.22 1 0.001

trafﬁcvsspeech 8.49 1,197 8.49 9.58 0.013 0.046

trafﬁcvsnature 9.78 1,197 9.78 10.81 0.007 0.052

speechvsnature 36.49 1,197 36.49 30.39 <0.001 0.134

view 20.54 1.93,380.62 10.63 15.94 <0.001 0.075 0.966

sound 41.77 2.76,543.91 15.13 13.91 <0.001 0.066 0.92

Interactions

view×sound 30.05 5.58,1098.34 5.39 12.55 <0.001 0.06 0.959

Contrastsb

Views

view1vsview2 5.58 1,197 5.58 18.19 <0.001 0.085

view1vsview3 0.48 1,197 0.48 1.72 0.191 0.009

view2vsview3 9.33 1,197 9.34 24.56 <0.001 0.111

sound 16.5 2.88,567.08 5.73 9.58 <0.001 0.046 0.96

nosoundvsspeech 6.55 1,197 6.55 5.25 0.138 0.026

nosoundvsnature 6.91 1,197 6.91 5.58 0.115 0.028

trafﬁcvsspeech 0.32 1,197 0.32 0.37 1 0.002

trafﬁcvsnature 21.34 1,197 21.34 18.3 <0.001 0.085

speechvsnature 26.91 1,197 26.91 25.98 <0.001 0.117

sound 8.52 2.84,562.08 3 5.13 0.002 0.025 0.946

nosoundvstrafﬁc 0.25 1,197 0.25 0.19 1 0.001

nosoundvsspeech 9.78 1,197 9.78 8.15 0.029 0.04

trafﬁcvsspeech 13.14 1,197 13.14 14.08 0.001 0.067

trafﬁcvsnature 5.17 1,197 5.17 4.34 0.199 0.022

speechvsnature 1.82 1,197 1.83 1.65 1 0.008

sound 46.76 2.85,564.95 16.39 23.37 <0.001 0.106 0.951

nosoundvstrafﬁc 29.94 1,197 29.94 21.29 <0.001 0.098

nosoundvsspeech 26.91 1,197 26.91 15.87 0.001 0.075

trafﬁcvsspeech 0.08 1,197 0.08 0.07 1 0

trafﬁcvsnature 64.49 1,197 64.49 55.6 <0.001 0.22

speechvsnature 60.01 1,197 60.01 43.62 <0.001 0.181

df=degreesoffreedom;F=Fratio;Sig.=signiﬁcance;p2=partialetasquared(effectsize).

isinbold.

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view 7.327 1.90,375.21 3.87 10.773 <0.001 0.052

sound 148.017 3,594 49.34 50.853 <0.001 0.204

Interactions

view×sound 2.116 5.60,1108.15 0.378 1.26 0.275 0.006 0.93

Contrasts Views

view1vsview2 3.663 1,198 3.66 18.92 <0.001 0.087

view1vsview3 0.95 1,198 0.95 5.10 0.075 0.025

view2vsview3 0.882 1,198 0.88 6.77 0.03 0.033

View1&3collapsed

sound 46.081 3,594 15.36 43.90 <0.001 0.181

nosoundvstraﬁc 3.94 1,198 3.94 5.38 0.129 0.026

nosoundvsnature 13.851 1,198 13.85 22.59 <0.001 0.102

trafﬁcvsspeech 13.588 1,198 13.59 22.34 <0.001 0.101

trafﬁcvsnature 32.564 1,198 32.56 44.41 <0.001 0.183

speechvsnature 88.222 1,198 88.22 122.56 <0.001 0.382 0.93

sound 56.637 3,594 18.88 34.23 <0.001 0.147

nosoundvstraﬁc 4.829 1,198 4.83 4.02 0.279 0.02

trafﬁcvsspeech 23.925 1,198 23.93 23.80 <0.001 0.107

trafﬁcvsnature 29.794 1,198 29.79 27.16 <0.001 0.121

speechvsnature 107.116 1,198 107.12 91.07 <0.001 0.315

view 39.42 1.90,371.65 20.79 31.67 <0.001 0.139 0.948

sound 44.59 2.86,561.38 15.57 18.9 <0.001 0.088 0.955

Interactions

view×sound 2.2 6,1176 0.37 1.11 0.354 0.006

Contrastsb

Views

view1vsview2 4.2 1,196 4.2 13.46 <0.001 0.064

view1vsview3 19.67 1,196 19.67 52.62 <0.001 0.212

view2vsview3 5.7 1,196 5.7 22 <0.001 0.105

sound 18.63 3,594 6.21 12.4 <0.001 0.059

nosoundvsspeech 1.29 1,198 1.29 1.35 1 0.007

nosoundvsnature 0 1,198 0 0 1 0

trafﬁcvsspeech 16.91 1,198 16.91 17.89 <0.001 0.083

trafﬁcvsnature 27.52 1,198 27.52 25.89 <0.001 0.116

speechvsnature 1.29 1,198 1.29 1.39 1 0.007

sound 17.87 3,588 5.96 11.31 <0.001 0.055

nosoundvsnature 0.02 1,196 0.02 0.02 1 0

trafﬁcvsspeech 27.8 1,196 27.8 30.57 <0.001 0.135

trafﬁcvsnature 22.11 1,196 22.11 19.71 <0.001 0.091

speechvsnature 0.33 1,196 0.33 0.29 1 0.001

sound 10.82 2.88,569.40 3.76 8.52 <0.001 0.041 0.959

trafﬁcvsspeech 16.91 1,198 16.91 24.06 <0.001 0.108

trafﬁcvsnature 15.2 1,198 15.2 16.2 <0.001 0.076

speechvsnature 0.05 1,198 0.05 0.05 1 0

view 3.22 1.90,376.88 1.69 2.51 0.085 0.013 0.952

sound 231.01 2.80,553.97 82.57 65.51 <0.001 0.249 0.933

Interactions

view*sound 23.14 5.6,1108.84 4.13 9.99 <0.001 0.048 0.933

sound 91.46 2.88,569.16 31.82 44.68 <0.001 0.184 0.958

trafﬁcvsspeech 0.5 1,198 0.5 0.4 1 0.002

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Table8(Continued)

Source SS df MS F Sig. p2 ␧a

speechvsnature 105.65 1,198 105.65 78.25 <0.001 0.283

sound 38.94 3,594 12.98 22.41 <0.001 0.102

nosoundvsspeech 10.18 1,198 10.18 8.3 0.026 0.04

trafﬁcvsspeech 16.33 1,198 16.33 12.9 0.002 0.061

trafﬁcvsnature 61.92 1,198 61.92 52.15 <0.001 0.208

speechvsnature 14.65 1,198 14.65 11.92 0.004 0.057

sound 123.75 2.85,564.07 43.44 60.09 <0.001 0.233 0.95

trafﬁcvsspeech 1.63 1,198 1.63 1.25 1 0.006

trafﬁcvsnature 123.86 1,198 123.86 92.5 <0.001 0.318

speechvsnature 97.09 1,198 97.09 82.89 <0.001 0.295

df=degreesoffreedom;F=Fratio;Sig.=signiﬁcance;p2=partialetasquared(effectsize).

isinbold.

b _Contrasts_adjusted_for_multiple_comparisons_with_Bonferroni_adjustment.

higherthan‘trafﬁc’(e.g.M=2.52,SD=0.91,p<0.001,views1&2) andmuchhigherthan‘nosound’(e.g.M=2.34,SD=0.91,p<0.001 views1&2)or‘nature’(M=2.34,SD=0.94, p<0.001views1&2), whichalsohadoneofthelargereffects(p2=0.23).The combi-nationswith‘nosound’and‘nature’resultedinalmostidentical ratings(e.g.M=2.34,p=1,views1&2).

For visual condition 3 the ANOVA revealed that the main effectsandinteractionswereallsignificant(p<0.001forall). Con-trasts(Table7)revealedthatrealismratingsdifferedsignificantly betweenviews1and2(p<0.001)andviews2and3(p<0.001)but notviews1and3(p<0.101).Furthercontrastswereconductedfor eachviewbysoundtype,whichrevealedvariedsignificant differ-encesbetweenrealismratingsdependingontheview(Table7). All views were rated similarly with ‘no sound’ (M=2.57–2.63) and‘nature’(M=2.75–2.81),whichwerenotsignificantlydifferent fromeachotherforanyview(p>0.05forall).‘Traffic’and‘speech’ hadnearlyidenticalratingsforview1(trafficM=2.43,SD=1.06; speechM=2.39,SD 1.06)andview3(trafficM=2.24, SD=1.10; speechM=2.26,SD=1.09),howeverforview2ratingswerehigher fortraffic(M=2.59,SD=1.09)andsignificantlyhigherforspeech (M=2.85,SD=1.07)(e.g.Fig.7).Asview2wastheonlyimagein visualcondition3that containedbuiltformthis seemsto indi-catethatthepresenceofanybuiltformcanhaveanimportant moderatingeffectonperceivedrealismwithdifferentsoundtypes.

3.3.2. ANOVAandcontrastsforpreferencescores

ANOVAandcontrastsforpreferenceareshowninTable8 ana-lysedseparatelyforeachvisualcondition.Forvisualcondition1 themaineffectof‘view’and ‘sound’weresignificant(p<0.001) thoughnottheinteraction(p<0.275).Contrasts(Table8)revealed thatpreferenceratingsdifferedsignificantlybetweenviews1and 2(p<0.001),andviews2and3(p=0.030),whileviews1and3 didnotdiffersignificantly(p=0.075);thereforeview2was consid-eredinisolationandviews1and3merged.Fig.7illustratesthe relationship:view2wasmorepreferredthanviews1and3 rela-tivelyconsistentlyforallsounds,scoringfrom0.03to0.14higher. Contrastsshowtheeffectofthedifferentsoundswasconsistent forthe4conditions,withsignificantdifferencesbetween prefer-encemeansfor5ofthe6soundcombinations(p<0.05,Table8), theexceptionbeingthe‘nosoundvs.traffic’condition,whichwas notsignificantforviews1and3(p=0.129)orview2(p=0.279).As withrealism‘speech’resultedinthelowestpreferenceratingsfor visualcondition1(view1&3:M=1.53,SD=0.65;view2:M=1.56, SD=0.78).

For visual condition2 the main effect of ‘view’and ‘sound’ weresignificant(p<0.001)thoughnottheinteraction(p=0.354). Contrasts revealedthat preference ratingsdiffered significantly between all views (p<0.001 for all, Table 8); therefore each viewwasconsideredindependently.Contrastsrevealedsignificant differencesbetweenpreferenceratingsfor3ofthe6sound com-binationsthatinvolvedtraffic(p<0.001forallexceptview3,‘no sound’vs.‘traffic’p=0.011),whiletheremainingthreewerenot significant(p=1.000forall).Therewasacleardownwardtrend inpreferenceratingsbetweenviews;view1wasmostpreferred (meansrangingfrom2.25to2.62),followedbyview2(2.11–2.49) andview3leastpreferred(2.01–2.30) whichalldiffered signif-icantly(p<0.001forall),whichcouldbeattributedtotheFerris wheelvisibleinthebackgroundofview1andmoredetailofthe buildinginview2comparedtoview3.Inaddition,‘traffic’with visualcondition2resultedinsignificantlylowerpreferencescores forallviews(p<0.05forall)comparedtotheothersoundsresulting inmeanscoresbetween0.29and0.38lower.

Forvisualcondition3themaineffectofviewwasnot signifi-cant(p=0.085),whilethemaineffectofsoundandtheinteraction ofviewandsoundwassignificant(p<0.0005forboth).Contrasts revealedsimilareffectsofsoundacrossviews,with‘traffic’and ‘speech’bothresultinginthelowestpreferenceratings(ranging from2.26to2.35)and‘nosound’and‘natureresultinginthe high-estpreferenceratings(rangingfrom2.95to3.13).Theexceptionto thistrendwasforview2combinedwith“speech”whichreceived ameanscoresignificantlyhigherthantheother‘traffic’or‘speech’ combinations(M=2.72,SD=1.02).Aswasthecasewithrealismthe builtformvisibleinthebackgroundofview2suggeststhe impor-tanceofaural-visualcongruenceandtheimpactthiscanhaveon preferenceratings,inthisinstanceupto0.46ona5-pointscale.

3.4. Hypothesisgenerationforperceptualvariationbyuser characteristic

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Fig.7.Meanratingforrealism(left)andpreference(right)byvisualcondition:visualcondition1,collapsedacrossIVofviewforrealismandviews1&3forpreference(top); visualcondition2,comparingview1&2collapsedtoview3forrealismandallviewforpreference(middle);andvisualcondition3,comparingall3viewsforrealismand preference.Errorbarsshow95%conﬁdenceintervals.

between-subjectsvariableandthemaineffectsofview,visual con-ditionandsoundasthewithinsubjectfactors.Forsitefamiliarity theresponsestothetwoquestionswereaveragedtoprovidean aggregatesite familiarity scorehowever this resultedin a very largegroupinginbottomofresponses(e.g.91.5%ofrespondents scoring a 1 or 2 out of 5). To satisfy the ANOVA assumptions sitefamiliaritywasanalysedvia3groups:moderatetoveryhigh familiarity,alittle,andnofamiliarity.Analysisofprofessional back-groundwasgoingtobeconductedacrossthreegroups(Landscape, n=62;BuiltEnvironment,n=16;and“Other”,n=94)howeverthis resultedinveryunbalancedgroups.Asacompromiseresponses werecombined into two categories:Landscapeand Built Envi-ronment(Architecture,CivilEngineering,Geography,Horticulture,

LandscapeArchitectureandPlanningbackgrounds)and‘Other’,(i.e. expertandlayperson).Othercharacteristicswereanalysed unal-tered.

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Table9

UsercharacteristicmixedANOVAgroups.

Characteristic[ratingtype](group,n) Total

Sitefamiliarity[realism&preference](3groups,n=198)

verymuch/quiteabit/moderately 41(20.6%)

alittle 51(25.6%)

notatall 106(53.8%)

3Dcomputergraphicsfamiliarity[realism](5groups,n=199)

Verymuch 27(13.6%)

Quiteabit 36(18.1%)

Moderately 41(20.6%)

Alittle 76(38.2%)

Notatall 19(9.5%)

3Dgraphicsexperienceindesign/planning[realism](2groups,n=199)

No 131(65.8%)

Yes 68(34.2%)

Professionalbackground[realism](2groups,n=170)

Expert 78(46.8%)

Laypeople 92(53.2%)

Agegroups[preference](3groups,n=193)

15–24years 80(40.2%)

25–44years 84(42.2%)

45–64years 29(14.6%)

Culturalbackground[preference](2groups,n=197)

UK 94(47.7%)

“Other” 103(52.3%)

Noisesensitivity[preference](3groups,n=199)

Low 66(33.2%)

Medium 109(54.8%)

High 24(12.1%)

from0.05to0.09withmeansdifferingbyupto0.26onthe1–5 scale).Thestandoutwastheinteractioninvolvingaparticipant’s countryofbackgroundandpreferenceratingswhichindicatedthat participantswhohadspentthemajorityoftheirlifeintheUK pre-ferredthecombinationofvisualcondition1withthenaturalsound morethannon-UKparticipants(F(1,195)=114.82,p<0.001, par-tial2₌_0.37)_which_manifested_in_a _difference_of_0.30_between thetwogroups. ThisisattributedtoUKparticipantspotentially viewingtheterrainonlyvisualizationasabeachandthebirdcall originatingfromaseagullbasedonanecdotalconversations fol-lowingtheexperiment,whichis anareaforfurtherresearch.It isworth noting thatalso thevast majorityof significant inter-actioninvolved ‘speech’asa variable,withtheexceptionbeing differencesbyprofessionalbackgroundforrealismandpreference, whichwasthe‘nosound’vs.‘traffic’conditionforboth.Theimpact ofspeechspecificallyfocusingontheinclusionandexclusionof peopleinvisualizationsisanareaforfutureresearch,asistheeffect ofdifferenttypesofspeechonparticipantswithdifferentcultural backgrounds.

4. Discussion

4.1. Contributionofcombiningsoundand3Dlandscape visualizationsontheperceptionofasimulatedenvironment

Theresultsofthis studyare consistentwiththehypotheses thattheinteractionsofauralandvisualstimulihaveanoticeable andstatisticallysigniﬁcanteffectonrealismand preference rat-ingsforasimulatedenvironment,whichisprimarilyinﬂuenced bythecongruenceoftheauralandvisualstimuli.Fig.8illustrates this,showingthepositiveornegativeeffectofeachsoundbyvisual conditionrelativetothe‘nosound’condition.Overallspeechhas thelargestimpact onrealismratings,both positively and neg-atively,whichvaries bythevisualcondition.Combinations that wereperceivedincongruoushavethelargest(negative)impacton

preference,withanthropogenicandmechanical sounds detract-ingmostfromvisualizationswithpredominantlyvegetation.This would suggestthat “whatisexpected” hasless ofa perceptual impact than what is not expected, which aligns with previous researchonsoundscapepreferencethatindicatedthathuman pref-erencescorescorrelatedwiththeabsenceorpresenceofwanted orunwantedsounds(Lam,Brown,Marafa,&Chau,2010).Thisis alsoconsistentwithpreviousresearchindicatingtheimportance ofthecongruenceofauralandvisualstimulionmultimodal per-ception(e.g.Carlesetal.,1999;Zhang&Kang,2007).Whilethe soundswererecordedatthegenerallocationsofthevisualizations themajorityofparticipantswerenotfamiliarwiththesiteandas suchwouldberespondingtothecombinationswithoutconnecting thistoaspecificrealworldlocationandwhattheyexpectto experi-encethere.Theresultsalsosupportpreviousresearchthatindicates thatnaturalsoundhaseitherapositiveorsmalleffecton prefer-enceofphotographs(e.g.Benfieldetal.,2010).Whatisinteresting isthemoderatingeffectofanyvisualanthropogenicindicators(e.g. buildings)onbothrealismandpreferenceratings.Thisisevidentin visualcondition3:trafficandspeechbothreducedperceived real-ismthemostforview3(predominantlyvegetation)andlessfor view1(mostlyvegetationwithabuildingjustvisibleinthe dis-tance),whilespeechactuallyincreasedperceivedrealismforview 2(showingmostlyvegetationwithabuildingclearlyvisiblebehind thetrees).Forpreferencetrafficandspeechagainaremoderated bytheimagerycontainingbuiltform,inasimilarpatterntothat forrealism,

Thecombinationofvisualcondition2(terrainandbuiltform) withthespeechsoundresultedinthehighestoverallincreasein realismratings(+.50comparedtonosound)furthersupporting theimportanceof congruentstimuli.Evenwhen nopeopleare presentinthevisualizationthepresenceofanthropogenicvisual elements(i.e.buildings)seemstohaveprovidedthecontextfor realism.Inthisinstancenaturalsounddidnotsignificantlyalter perceivedrealism,whichsuggestsastrongerinfluenceof anthro-pogenic sound on visualizations of natural environments than naturalsoundonvisualizationsofbuiltenvironments.Interestingly thereisalsosomepreliminaryevidencethatcongruenceisafactor evenwhenpeopleperceivesoundsandvisualsincorrectlyas poten-tiallyisthecasewithUKparticipantspotentiallyhearinga‘seagull’ andseeinga‘beach’.Thishighlightstheimportanceofbothcontext specificityoftaskinaural–visualenvironmentalsimulations.

4.2. PerceivedrealismofGoogleEarth

Inadditiontotheaural–visualinteractionsthisresearchhasalso identiﬁedan importantvisualresult—therelativelylow realism attributedtoGoogleEartheye-levelvisualizations.Itiscautioned thatbasedonthevisualizationsusedinthisresearchthehighest levelofrealismattributedtoaGoogleEarthvisualizationis2.81 (onascaleof5),whichplaceseventhemostrealistic combina-tionsbetween‘slightly’and‘somewhat’realontheratingsscale. Researchersandprofessionalsneedtobeawareofthisrelatively lowlevelofrealismifusingGoogleEarth.

4.3. UsingtheInternetforaural-visualdatacollectionand landscapeevaluation

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-0.90 -0.80 -0.70 -0.60 -0.50 -0.40 -0.30 -0.20 -0.100.00 0.10 0.20 0.30 0.40 0.50 No s o u n d Tr a ff ic Sp e e ch Na tu re No s o u n d Tr a ff ic Sp e e ch Na tu re No s o u n d Tr a ff ic Sp e e ch Na tu re No s o u n d Tr a ff ic Sp e e ch Na tu re No s o u n d Tr a ff ic Sp e e ch Na tu re No s o u n d Tr a ff ic Sp e e ch Na tu re

All views View 1&2 View 3 View 1 View 2 View 3

vis cond 1 vis cond 2 vis cond 3

me

an

re

al

is

m

ra

tin

g

c

h

a

view x visu

al condition x soun

d

-0.90 -0.80 -0.70 -0.60 -0.50 -0.40 -0.30 -0.20 -0.10 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00 No s oun d Tr a ff ic S pee ch Na tu re No s oun d Tr a ff ic S pee ch Na tu re No s oun d Tr a ff ic S pee ch Na tu re No s oun d Tr a ff ic S pee ch Na tu re No s oun d Tr a ff ic S pee ch Na tu re No s oun d Tr a ff ic S pee ch Na tu re No s oun d Tr a ff ic S pee ch Na tu re No s oun d Tr a ff ic S pee ch Na tu re

View 1&3 View 2 View 1 View 2 View 3 View 1 View 2 View 3

vis cond 1 vis cond 2 vis cond 3

m e an p re fer en ce r a ti n g ch an g e

view x visu

al con

dition x so

und

Fig.8.Meanrealism(top)andpreference(bottom)ratingchangerelativetothe‘nosound’condition.

displaysizeandaudiohardwarefidelitywereshowntonot sig-nificantlyalterrealismandpreference ratingsforthesimulated environment.Thissuggeststhatwhenusingmonitorsupto27” andheadphonesforsounddeliverythereisflexibilityinthechoice ofhardwareused.

4.4. Limitationsofthestudy

Someimportant limitations of thestudy are acknowledged. First,therewerealimited numberofviewsusedinthe experi-ment,andanunevenoperationalizationacrosstheviewsresulting incomplexnon-linearpatternsofresults.Second,becauseofthe within-subjectdesignofthestudyandrequiringparticipantsto raterealismandpreferencetogethertherecouldbeaninﬂuenceon responsesandarelationshipbetweenrealismandpreferenceoccur whereitwouldnotwerethequestionsaskedseparately.Indeed

astherealismand preferenceresponsesarecorrelated foreach questionthereisclearlyarelationshipbetweenthem,indicating eitherthathigherrealismleadstohigherpreference,orthat par-ticipantsdidnotcompletelydistinguishbetweenthetwo.Some evidencefortheformeristhatvisualcondition2realismscores increasedwithtraffic,whiledecreasingsignificantlyforpreference. Thisisanareawherefurtherresearchwouldbebeneficial.

4.5. Codeofethicsforenvironmentalsimulation

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wouldbe highlyunethical, and likely would becalledout as a problembyeitherinformedstakeholdersorprofessionals.More problematicisidentifyingexactlywhatincongruentsoundis—as mentioned,allofthesoundsusedintheexperimentwererecorded atSt.James’sParkand,whilenotdirectlymatchedtovisualization location,couldbearguedtobeavalidinclusionwithaparticular visualizationorviewpoint.Theselectionofview(s),sound(s), sea-sonsandtimeofdayarebutafewofthecriticaldecisionstobe made,andweproposethataccuracyofexperiencebeaguiding prin-cipleforaural–visualsimulations.Inthecontextofethicalconduct preparersandpresentersofaural–visualsimulationsare encour-agedtofollowSheppard’scodeofethics(2001).Inadditionthey shouldgenerallyproducesimulationsthatsimulatetheactualor expectedappearanceandsoundofthelandscapeandsoundscape ascloselyas possibleusingspatiotemporallycongruentstimuli. Thiswouldlenditselftomoreneutraljudgementsandtransparency intheprocess.

4.6. Implicationsforfutureresearch

Thecurrentstudyfocusedspeciﬁcallyonperceptualresponses tothecombinationofauralandvisualstimuliinordertoinform broadrecommendationsfor aural–visualenvironmental simula-tions and to identify future research needed. We suggest the followingresearchisneededtoinformaural–visualenvironmental simulations:

-evaluationofdifferencesbetweenperceptualresponsesto mul-tisensorycomputersimulatedenvironmentsandreal-world,on siteexperience.

-developmentofprocedurestoevaluaterealismandpreference responsestodifferentsounds.

-perceptualeffectsofdifferentsoundsources(e.g.synthesized) withdifferenttypesofvisualizations(e.g.realistic)(seeLindquist, Lange,&Kang,2014foranelaborationofoptions).

-speciﬁctechniquesofauralizationforparticularprojectcontexts (e.g.forwindturbinesseePieren,Heutschi,Müller,Manyoky,& Eggenschwiler,2014).

-assessmentofthecommunicationeffectivenessofaural–visual simulations.

-theeffectofdifferentpresentationmodesofaural–visual stim-uli (e.g. real-time movement vs. static; surround sound vs. mono/stereo).

-theeffectofdifferentusercharacteristicsontheperceptionof aural–visualsimulations(speciﬁcallyontheimpactofsite famil-iarity and professional background on perceived realism and culturalandprofessionalbackgroundonpreference).

4.7. Implicationsforpractice

Forlandscapearchitectsandplannersthissignalsthe impor-tanceofconsideringthetotal environmentalexperiencebeyond howsomething looks, which canadditionallyresult in positive indirecteffects, suchasaidingspatialnavigationfor thevisibly impairedby enhancingsound based spatialcues(e.g. Parkin& Smithies,2012).Preparersandpresentersofvisualizationsneed tobeconsciousthatwhenusingsoundwithvisualizations differ-entpointsofviewmayvarythelandscapeelementsrepresented whichcan alter perceptualresponsesin unexpectedways. This underscorestheimportanceofmultipleviewpointsforevaluation, aswellasthepotentialcontributiontomultisensoryenvironmental simulationofreal-timevisualizationwithaccuratelymodelled spa-tializedsound.Visualizationpreparersalsoneedtobeconsciousof thecross-sensoryeffectofaural–visualinteraction,asasoundthat maybeobviouslyonethingtoaresearchercanbealteredbya

visu-alizationtobeheardassomethingdifferentbyaparticipant—with potentiallyunwantedandunexpectedresults

5. Conclusions

Relyingsolely onvisualrepresentationsof environmentsfor design,planningandevaluationdoesnotsufficientlysimulateour experienceoftheworld.Inthisstudythecontributionofsound totheperceptionof3Dlandscapevisualizationswasassessedina laboratoryandonlineexperiment.Thereisaclearopportunityto increasetheauthenticityoflandscapeexperiencewhenusing3D landscapevisualisationsbyincorporatingsoundasitsignificantly altersperceptionofrealismandpreference.EyelevelGoogleEarth visualizationsreceivelowrealismratingsandaural–visualdata col-lectedviaaweb-basedsurveywascomparabletodatacollected inthelaboratory.Realismandpreferencevaryprimarilyasa func-tionofaural–visualcongruency(e.g.themorecongruentthevisual landscapeelementwaswiththesoundthehighertherealismand preferencewas).Thesefindingssuggestthatcouplingthe appro-priatesoundwithacorrespondingvisualizationcanbeaneffective waytomoreaccuratelysimulateenvironmentalexperiencewhen using3Dlandscapevisualization.

AppendixA. Supplementarydata

Supplementarydataassociatedwiththisarticlecanbefound, intheonline version,athttp://dx.doi.org/10.1016/j.landurbplan. 2015.12.017.

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