PROCEEDINGS of the
23rd International Congress on Acoustics
9 to 13 September 2019 in Aachen, Germany

Ambient Soundscape Assessment of Wind Parks
Tianhong YU1 2 , Holger BEHM1, Ralf BILL1, Jian KANG3
1 Faculty of Agricultural and Environmental Sciences, University of Rostock, Germany
2 IFB Ingenieure GmbH, Bad Teinach-Zavelstein

3 Institute for Environmental Design and Engineering, The Bartlett, University College London, UK

ABSTRACTThe potential conflicts between wind parks and the public are enormously enhanced after a rapid
increase of wind parks. Assessment and management of environmental noise have played a vital rolein the reaction of people concerning wind parks. This study uses an aural-visual preference survey tosystematically investigate effects of background soundscapes and non-aural factors on annoyancetoward wind parks. Visual and acoustic data were captured from seven German rural wind park sites.
Laboratory experiments were then carried out with 40 participants to investigate the perception of
the wind parks in rural areas. The tests consisted of three parts: 1) visual-only condition, 2) auralonly condition, and 3) combined aural-visual condition. Participants were immersed through google
cardboard in laboratories using virtual reality technology to evaluate properties of sound and visualenvironment. Results suggest that the annoyance of wind parks strongly correlated with sound level
ambient wind parks. However, the visual information did not demonstrate substantial effects on thepeople’s opinions of wind parks. Further results show that the soundscape ambient wind parks
associated with factors including "calmness/relaxation", "naturality/pleasantness" and "diversity."
Additionally, "calmness/relaxation" and "naturality/pleasantness" were found to have a strong
impact on the evaluation of wind park landscapes.
Keywords: Soundscape; audio-visual impact assessment; virtual reality; Wind parks
1.

INTRODUCTION
The concept of the soundscape, which refers to "acoustic environment as perceived orexperienced and/or understood by a person or people, in context" (ISO12913-1, 2014). The
soundscape was suggested by numerous researchers as a critical factor for the understanding
perception of an acoustic environment (Brambilla et al., 2013; Brown et al., 2011; Kang et al.,2016). The soundscape characteristics and sound level were implied as the prominent aspects of theannoyance evaluation (Szychowska et al., 2018). Moreover, the soundscape may dominate thepreference degree to the environment due to its components and places with environmental identity(Carles et al., 1999). The soundscape in a rural area is a complex system. To characterize thesoundscape in a rural area and verify its environmental identity, perceptual measure using
multidimensional indices (semantical differential technique) was suggested (Galbrun and Calarco,2014). Previous research has indicated the need for categorization of the soundscape in different
levels (Kang and Zhang, 2010; Torija et al., 2013; Viollon et al., 2002). Various investigations haveused laboratory protocols to examine the influence of the sound to outdoor settings quality (Jiang
and Kang, 2016), indicating the enhancing effect of nature-related sounds on residential setting
quality (Anderson et al., 1983). Studies on traffic noise annoyance have widely been investigated, as
an example, the influence of the visual aspect of barriers on railway noise annoyance has been
examined (Maffei et al., 2013). However, the impact of ambient sound characteristics on theannoyance of wind turbines which are placed mostly in rural or mildly built-up areas was so far not
clear (Janssen et al., 2011). Many residents near to wind turbines may spend a higher proportion of
their time outdoors, thus considering the influence of the future ambient soundscape on a wind park
annoyance will be a supplement for acoustic research. In the context of wind parks, a holistic
approach to investigate the soundscape around wind parks and their effects should be conducted to
improve environmental quality in rural areas.
The landscape environment is rarely perceived in an isolated but multisensory way. Previous
studies have confirmed the importance of the interaction between aural and visual information. The

852

vision and audition are commonly accepted as the significant modalities to perceive the environment(Hong and Jeon, 2014; Pheasant et al., 2010). Several studies have tested virtual reality (VR)technology for participatory evaluation (Yu et al., 2017), proving the applicability and advantages inscenario control for comparative presentations (Iachini et al., 2012; Jiang et al., 2017; Ruotolo et al.,2013; YU et al., 2018). The public’s adverse reaction to new wind park projects, likely due to theirnoise, may be increased by the insufficient information of the projects. It was also suggested that thesocial acceptance would be enhanced through the accessible information and participatory of the
public from the initial phase of the planning process (Simão et al., 2009; Yeh and Huang, 2014).
This study, therefore, uses an aural-visual survey to investigate how soundscapes ambient windparks affect the perception of wind parks and verify some non-aural factors might be considered asstatistically significant among them. With the aim of characterizing the soundscapes ambient windparks, various noise level indices and multidimensional scaling based on the semantic differential
technique, which were previously used in the landscape studies, were adopted. As a result of thissurvey three questions will be answered:(1) Effects of sound level on wind parks;(2) Effects of visual information related to wind parks;(3) Perception of wind parks in terms of multidimensional indices.
2.

METHODOLOGY

2.1. Site Selection
Rural landscapes are complex and frequently characterized by various anthropic artificial
processing, thus generating a broad diversity of soundscapes with profoundly different
characteristics. With the aim of assessing the ambient soundscape of wind parks, a preliminary study
with individual sound walks was performed around wind parks in Rostock, which is located in thenorth-east of Germany and a popular area for wind parks. According to the typologies ofsoundscapes around wind turbines in the previous studies (Pedersen et al., 2009; Torija et al., 2013),
seven locations were selected:site 01: located within the main avenue with high road traffic flow with a large number ofvehicles;site 02: located in a natural environment isolated from sounds of human activity, this site isdominated by bird sounds;site 03: situated next to a motorway;
site 04: located in a residential area, including the sounds of people talking;site 05: located near a residential area, including sounds of outdoor activities;
site 06 located in a residential area with a medium road traffic flow;site 07 situated in a natural environment with water sounds.
As listed in Table I, these locations possess main features of a rural landscape, including central
features of (high traffic flow, birds sound, motorway, human sounds, leisure activities, medium
traffic flow, and water sound). For a better understanding of these sites, further related physical data
will be described in the coming section.
TABLE I Physical characteristics at each site. L Aeq: A-weighted sound pressure level; N:
loudness; S: sharpness; Fls.: fluctuating strength; R: roughness.
Site

Sound feature

Category

LAeq[dB]N[soneGF]

S[acum]Fls.[vacil]

R[asper]Number of
WT

01

High traffic
flowTechnological
sound

65.3

46.06

3.21

0.017

3.24

4

02

Birds

Natural sound

39.0

1.06

1.93

0.006

0.03

4

03

Motorway

Technological
sound

52.5

10.67

1.79

0.005

1.44

10

04

Human
soundsHuman speeches

50.2

2.85

1.46

0.005

0.24

10

05

Leisureactivities

Human speech

53.6

11.39

1.87

0.011

1.57

10

06

Mediumtraffic flow

Technological
sound

41.2

9.7

1.8

0.010

1.2

5

07

Water

Natural sound

43.7

9.7

1.8

0.010

1.2

10

853

2.2. Aural Stimuli
Binaural recordings were made with clear weather from 11:00 am to 3.00 pm using a dummy
head with a height of 1.6 m and a recorder (DAT 208Ax, Sony) in the selected locations. Wind
turbines should be placed at a distance of 800 to 1000 meter away from the residential houseaccording to the local regulations (Plehn, 2012). Jallouli et al. also indicated that wind parks
dominate noise perception if wind turbines were located within 1 km distance (Jallouli and Moreau,2009). In our study, positions for recordings were placed more than 1000 m to the wind park, thenoise of wind turbines was thus irrelevant here. The wind speed during recordings was 7.2 ms-1. Our
recorder was mounted with a windshield to block wind noise. A-weighted sound pressure level(LAeq) were recorded in 3 min. For laboratory experiments, the recordings were edited in Audacity
and then a 32-s aural recording sample of sounds was excerpted from the aural recording. The
analysis of four psychoacoustic metrics including loudness (N), sharpness (S), fluctuation strength(Fls.), and roughness (R) was performed through Artemis (Head Acoustics) Software to identify
sounds at each site. The characteristics of each site are presented in Table I.
2.3. Visual Stimuli
Visual stimuli of wind parks based on the selected sites were created using Unity 3D, which is across-platform game engine and can build virtual scenarios for mobile devices. The model of thearea and the wind turbines (height: 103m, the diameter of rotor: 105m) were modeled and textured
using the 3ds Max modeling software. Both the auditory and visual components of the scenarios
were uploaded to make the virtual environment as realistic as possible. The duration and loudness ofsounds were normalized before being imported into Unity 3D. This simulation considers
visualization of the built environment and the ground of the area and allows head tracking with theaid of a smartphone and a Google Cardboard headset. Sounds and scene view move in an immersive360-degree as the head moves. This VR technology ensures participants experience a high realistic
simulated environment (Rafiee et al., 2018).
2.4. Experimental design
The primary purpose of our laboratory experiments is to investigate the ambient soundscapes on
the perception of the wind park environment. The experiments consist of three parts: 1) visual-only
condition, 2) aural-only condition, and 3) combined aural-visual condition. In total 21 stimuli (3conditions* 7 sites) were created.
In the laboratory experiments, a total of 40 university students (Mean age: 26.8 years, standard
deviation: 3.4 years) participated in the study of the perception of aural-visual stimuli in laboratory
experiments. All participants had normal hearing and regular or corrected to normal vision, had no
prior experience with wind parks and all were naive as to the purpose of the experiment.
Participants were asked to rate their annoyance scores and acceptance of the wind park on eachstimulus using a 7-point Likert scale from “not at all” to “extremely” (1 = “not at all”, 2 = “low”, 3= “slightly”, 4 = “neutral”, 5 = “moderately”, 6 = “very”, and 7 = “extremely”). The preference test,
semantic differential (SD) technique, was suggested by previous studies used as a method forconnecting public’s feelings at linguistic and psychophysical levels towards sounds andcharacterizing the soundscape (Cain et al., 2013; Kang and Zhang, 2010). In order to evaluate SD
scales of a soundscape in considering the components found in existing studies, 10 pairs of bipolar
adjectives (pleasant/unpleasant, various/monotonous, quiet/loud, smooth/rough, calming/agitating,comfortable/uncomfortable, open/closed, natural/artificial, ordered/disordered, and distinct/
ordinary) rated on a 7-point scale were selected (Hong and Jeon, 2013; Nilsson et al., 2012; Torija etal., 2013). Finally, socio-demographic questions were recorded, which includes attributes(“Gender”, “Age”). See also in Table II.
Participants evaluated each stimulus under aural only, visual only, and aural-visual conditions.
They were allowed to replay stimuli as many times as wanted to answer the questions. Eachstimulus lasted approximately 32 s, and the testing order was randomized under each perceived
condition.
Each participant was tested individually. During the experiments, participants sat in a quiet
room (< 40 dB) wearing a Google Cardboard headset with an embedded mobile device. The center
points of the scenarios were aligned on the mobile device as represented by Unity 3D. Acoustic
stimuli were delivered through the headphones (Sennheiser HD 598) plugged into the mobile device.
The test sound level and the on-site recorded one were closely identified with each other as
determined in Table I before the start of testing. All testing procedures were carried out between
10:00 and 14:00 h in a quiet room, to avoid any effect of circadian rhythm.
3.

Results and discussion
The general aim of this study was to investigate the ambient soundscape on the perception of awind park. An aural-visual preference survey to investigate the effects of background sounds andnon-aural factor on the perception of wind parks and their interaction was used. As described before,854the present study examined subjective responses to aural only, visual only, and combined auralvisual stimuli. In the following, the analysis of the subjective responses is conducted. The semantic
analysis of the descriptions of the sounds, the correlations between the preferences of wind parks,
and sound level characteristics are provided below.
TABLE II Index overview of the evaluated variables, the questions, and their scales
Index

Indicator
Perception Question (P)P1Perceived annoyance in the stimuli (Scale: 1-7, from “not at all” to “extremely”)

P2

Preference score for the aural stimuli (Scale:1-7)

P3

Perceived realism of the stimuli (Scale: 1-7, from “not at all” to “extremely”)

P4

Acceptance with the integration of a wind turbine in the stimuli (Scale: 1-7, from “not at all” to “extremely”)
Semantic Differential Test (SD)

SD1-SD10

10 pairs of bipolar adjectives: pleasant-unpleasant, various-monotonous, quiet/loud, smooth/rough, calming/agitating,comfortable/uncomfortable, open/closed, natural/artificial, ordered/disordered, distinct/ordinary.
(Scale: 1-7, from “not at all” to “extremely”)
Socio-Demographic Questions (D)

D1-D4

Gender, Age

3.1. Effects of sound level on wind parks preference
3.1.1.Sound level characteristics
First, a median test was performed to determine the reliability of the differences between theperceived annoyances at each site. The result shows a significant difference for the investigated sites[chi2 (6, N = 40) = 41.74; p < 0.001]. Second, a correlation analysis to determine the backgroundsound characteristics with the perceived aural annoyance was applied under aural-visual condition.
According to the results, a strong correlation between the perceived sound, the sound characteristics
including the measured sound pressure level (p < 0.01), loudness (p < 0.05), fluctuation strength (p< 0.05), and roughness (p < 0.01) were found. Finally, the correlation coefficients with soundcharacteristics were calculated and presented below (Table III).
This shows that loudness explained the most variance (81%), compared to sharpness (52%),
fluctuation strength (60%), roughness (80%), and measured sound pressure level (74%). It wassuggested that the aural annoyance was getting worse as the increase of the sound level of ambient
sound at wind park sites.
TABLE III The percentage of explained variance calculated using the correlation
coefficient between the perceived annoyance and background sound characteristics. N:
loudness; S: sharpness; F: fluctuating strength; R: roughness; LAeq: A-weighted soundpressure level.
Sound characteristics vs. perceived annoyance

Explained variance R2

N

0.81

S

0.52

Fls.

0.60

R

0.80

LAeq

0.74

3.1.2.Dominant sound information
In order to further examine how background sound information influences aural-visual wind park
environment, overall preference score was compared between the visual only and mixed aural-visualconditions. Average general preference scores under these three stimuli conditions were illustrated
as shown in Fig. 1. The ANOVA on annoyance rates were performed for each condition. According855

to our analysis, the differences in the mean annoyance rates between the visual only and aural-visualconditions at site 01, site 02, site 05, and site 06 were statistically significant (Fig. 1). There was asignificant difference in preference score when aural information was added. The sounds at site 01
and site 02 were considered as least preferred and most preferred one. The annoyance scores for theaural-visual stimuli increased at site 01 and decreased at site 02 regards the visual-only stimuli. At
site 01 the dominant mechanical sounds may cause an adverse effect on the preference. On thecontrary, at site 02 the dominant natural sounds may decrease the annoyance. At site 05, the aural
input of human activities increased the annoyance for participants. The reason was that, where
human activities took place nearby, allowance for any wind parks will be decreased. At site 06, thenoise of traffic enhances the general annoyance score.
The results indicate that the sounds influence the annoyance a lot. The addition of natural sounds(birds sounds) may increase the preference of the wind parks environment by a score of 0.75, theaddition of mechanical sounds (traffic sounds) and anthropogenic sounds (human sound) may
decrease the preference of the wind parks environment by a score of 2.73 and 0.65. For preferenceof wind parks under the aural-visual condition with dominant natural sounds would be the most
preferred. For preference of wind parks with dominant mechanical sounds would be the least
preferred.
3.1.3.Human sounds
To evaluate the level of acceptance of wind parks with different background sounds, theacceptance level of wind parks with the aid of the aural and visual stimuli was rated. The acceptancescores were illustrated under visual and aural-visual conditions at each site (Fig. 2). All of theinvestigated sites were considered as a highly accepted area for wind parks except site 04 and site
05 where human sounds and activities happened nearby.

!
Fig. 1. Annoyance scores under visual only and aural-visual conditions at each site, where site
01 was rated as the most annoyed one and site 02 was rated as the least annoyed one under
the aural-visual condition. Error bars depict standard error values (*** = p < 0.001, ** = p < 0.01,= p < 0.05).

!
Fig. 2 Acceptance of wind parks under visual only and aural-visual conditions at eachsite, where site 01 was rated as the most annoyed one and site 02 was rated as the leastannoyed one under the aural-visual condition. Error bars depict standard error values.
Wind park projects should be limited to be planned in the leisure sites for human beings.

856

Although, wind energy was a renewable energy, which can bring the clean energy for human beings.
Regards to its intrusion to the landscape and communities, this study suggests that planning of windparks must be restricted near areas of human activities.
3.2. Effects of visual information on wind parks preference
In order to study the relation between vision and the subjective measures, analysis of aural
annoyance between aural-only and aural-visual conditions was performed. The aural annoyancescores at each site averaged across all subjects were illustrated in Fig. 3. The result showed that themost perceived sound was site 02 with birds sound, whereas site 01 with high traffic sound was theleast preferred (Fig. 3). Under the aural-visual condition, participants mostly dislike site 01
including the high way sound, with a mean annoyance score of 5.5 (SD of 1.48). Compared to that,the mean annoyance score for site 02 with birds sound was 1.7 (SD of 0.9). The related annoyancescores for site 03, 04, 05, 06, and 07, are 3.4, 3.42, 3.38, 3.33, and 3.48, respectively. Overall, theirannoyance scores remained similarly. Finally, it was suggested that there are no significant
differences between aural-only and aural-visual conditions at each site (P > 0.05).

!
Fig. 3. Average ratings of the aural annoyance at each site under aural only and combinedaural-visual conditions, where site 01 was rated as the most annoyed one and site 02 was
rated as the least annoyed one. Error bars depict standard error values.
The annoyance of wind parks was mostly on the sound levels of the simulation. The negative
impacts of wind parks may depend on either the ambient natural or mechanical elements.
Furthermore, according to the ANOVA analysis, no significant effect was observed for theannoyance scores and the number of wind turbines. The number of wind turbines may not affect thepreference of wind parks at a distance of more than 1 km.
3.3. Analysis of soundscape on multidimensional scales
For the purpose of evaluating the key factors which characterize the soundscape around windparks on multidimensional scales, the SD technique was used. Ten semantic descriptors wereselected. Factor analysis of overall results under the condition of aural-visual was carried out toclassify the ten semantic descriptors. The method of varimax rotation was selected to extract theorthogonal factors. The criterion factor of eigenvalue was set greater than 1. In total, three factors
were determined, as shown in (Table IV). Factor 1 (42.4%) is mainly associated with “calmness/relaxation” which was suggested by previous researchers (Sudarsono et al., 2016), including“smooth/rough,” “distinct/ordinary,” “quiet/loud,” “ordered/disordered,” “comfortable/
uncomfortable,” and “calming/agitating.” Factor 2 (15.6%) can be associated with “naturality/
pleasantness, ” including “open/closed,” “natural/artificial,” and “pleasant/unpleasant.” Factor 3(11.4%) is associated with “various/monotonous, ” composing “various/monotonous.” These threefactors cover the main facets of designing the acoustics of a landscape region. The soundscapequality around wind parks correlates well with the attributes.
After multiple regression analysis, the results demonstrated the dominant factors which best
explain the influence of the perception of wind parks in the landscape with different ambient sounds.
Furthermore, through Pearson’s correlation coefficients, the relationships between these factors andsound level characteristics were identified (Table V). Regarding factors obtained under the auralvisual condition, it was indicated that “calmness/relaxation” was related to the acoustic
characteristics of the loudness and fluctuation strength, as well as annoyance. Additionally, the“naturality/pleasantness” was related to the loudness, roughness, and annoyance. Both “calmness/relaxation” and “naturality/pleasantness” showed a significant correlation with annoyance, which
implies the importance of the “calmness/relaxation” and “naturality/pleasantness” in the perception857

of wind parks. Finally, there was no correlation between “diversity”, acoustical metrics andannoyance.
TABLE IV Factor analysis of semantic descriptors under the condition of aural-visual. KaiserMeyer-Olkin measure of sampling adequacy: 0.725; cumulative 69.487%. Rotation method:
varimax with Kaiser Normalization; N= 40.
Component

Factor 1 (42.4%)

Smooth0.874

Distinct

0.858

Quiet

0.841

Order

0.692

Comfortable

0.679

Calming

0.659

Factor 2 (15.6%)

0.468
0.451

Open

0.836

Natural0.695

Pleasant

Factor 3 (11.4%)

0.458

0.601

Various

0.919

TABLE V Pearson’s correlation coefficients between the selected sound metrics (** = p < 0.01, *= p < 0.05).
FactorLoudness
Sharpness
Fluctuation
strength
Roughness
L Aeq
Annoyance
Calmness/relaxation
Naturality/
pleasantness

Psychoacoustic metrics

Semantical factors

Shar
pness

Fluct
uationstrength

Rough
ness

L Aeq

Ann
oyanceCalmness/relaxation

Naturality/
pleasantness

Various/monotonous

0.948**

0.889**

0.946**

0.842*

0.898**

0.841*

0.790*

0.561

0.859*

0.842*

0.693

0.718

0.633

0.577

0.454

0.881**

0.587

0.777*

0.756*

0.672

0.294

0.812*

0.896**

0.916

0.843*

0.571

0.859*

0.782*

0.794*

0.431

0.964**

0.971**

0.593

0.983**

0.644

0.622

4.

CONCLUSIONS
Investigating how new infrastructure projects, such as wind parks impact the quality of people
living, is an essential factor in the landscape planning. Various factors need to be defined andindecently investigated regards the case of wind parks. In this study, the aural-visual simulation wasused to evaluate soundscapes ambient wind parks without taking into account the noise of windturbines. The background sounds and non-aural factor on the perception of wind parks andinteraction between the aural and visual information were investigated.
According to the results, the background sound characteristics including sound pressure level,
loudness and roughness were strongly correlated with the perceived annoyance of wind parks. The
aural information played a significant role in the preference of wind parks. The addition of bird
sounds had a positive effect on the preference of wind parks. However, the addition of humansounds, traffic sounds, or water sounds ambient wind parks might decrease preference of the858

landscape. Additionally, the ratings of acceptance of wind parks demonstrated a high level ofagreement for wind park projects and suggested a limitation of wind parks in the sites where humanactivities took place nearby. Furthermore, no significant correlation was achieved between visual
information and annoyance scores. The visual information may not affect the preference of windparks at a distance of more than 1 km.
At last, the analysis of the soundscape on multidimensional scales indicated the importance of
the “calmness/relaxation”, “naturality/pleasantness”, and “diversity” on the preference of theenvironment around wind parks. Among them, factors of “calmness/relaxation” and “naturality/
pleasantness” were strongly correlated with background sound metrics including loudness,fluctuation strength, roughness, sound pressure level, and perceived annoyance. The soundscape hasa significant role in the evaluation of wind park landscapes. For a more reasonable acoustic
environment within the context of landscape planning, the soundscape should be further consideredand studied in future research.
REFERENCES
Anderson, L. M., Mulligan, B. E., Goodman, L. S., Regen, H. Z., 1983, Effects of Sounds on Preferences for Outdoor Settings, Environment
and Behavior 15(5):539-566.
Brambilla, G., Gallo, V., Asdrubali, F., apos, Alessandro, F., 2013, The perceived quality of soundscape in three urban parks in Rome, The
Journal of the Acoustical Society of America 134(1):832-839.
Brown, A. L., Kang, J. A., Gjestland, T., 2011, Towards standardization in soundscape preference assessment, Applied Acoustics 72(6):387-392.
Cain, R., Jennings, P., Poxon, J., 2013, The development and application of the emotional dimensions of a soundscape, Applied Acoustics
74(2):232-239.
Carles, J. L., Barrio, I. L., de Lucio, J. V., 1999, Sound influence on landscape values, Landscape and Urban Planning 43(4):191-200.
Galbrun, L., Calarco, F. M. A., 2014, Audio-visual interaction and perceptual assessment of water features used over road traffic noise, The
Journal of the Acoustical Society of America 136(5):2609-2620.
Hong, J. Y., Jeon, J. Y., 2013, Designing sound and visual components for enhancement of urban soundscapes, The Journal of the AcousticalSociety of America 134(3):2026-2036.
Hong, J. Y., Jeon, J. Y., 2014, The effects of audio–visual factors on perceptions of environmental noise barrier performance, Landscape and
Urban Planning 125:28-37.
Iachini, T., Maffei, L., Ruotolo, F., Senese, V. P., Ruggiero, G., Masullo, M., Alekseeva, N., 2012, Multisensory Assessment of Acoustic
Comfort Aboard Metros: a Virtual Reality Study, Applied Cognitive Psychology 26(5):757-767.
ISO12913-1, 2014, Acoustics—soundscape—part 1: Definition and conceptual framework (I. O. f. Standardization, ed.), Geneva: ISO.
Jallouli, J., Moreau, G., 2009, An immersive path-based study of wind turbines' landscape: A French case in Plouguin, Renewable Energy34(3):597-607.
Janssen, S. A., Vos, H., Eisses, A. R., Pedersen, E., 2011, A comparison between exposure-response relationships for wind turbine annoyanceand annoyance due to other noise sources, The Journal of the Acoustical Society of America 130(6):3746-3753.
Jiang, L., Kang, J., 2016, Combined acoustical and visual performance of noise barriers in mitigating the environmental impact ofmotorways, Science of The Total Environment 543(Part A):52-60.
Jiang, L., Masullo, M., Maffei, L., Meng, F., Vorländer, M., 2017, A demonstrator tool of web-based virtual reality for participatory
evaluation of urban sound environment, Landscape and Urban Planning.
Kang, J., Aletta, F., Gjestland, T. T., Brown, L. A., Botteldooren, D., Schulte-Fortkamp, B., Lercher, P., van Kamp, I., Genuit, K., Fiebig, A.,
Bento Coelho, J. L., Maffei, L., Lavia, L., 2016, Ten questions on the soundscapes of the built environment, Building andEnvironment 108:284-294.
Kang, J., Zhang, M., 2010, Semantic differential analysis of the soundscape in urban open public spaces, Building and Environment 45(1):150-157.
Maffei, L., Masullo, M., Aletta, F., Di Gabriele, M., 2013, The influence of visual characteristics of barriers on railway noise perception,
Science of the Total Environment 445:41-47.
Nilsson, M. E., Jeon, J. Y., Rådsten-Ekman, M., Axelsson, Ö., Hong, J. Y., Jang, H. S., 2012, A soundwalk study on the relationship between
soundscape and overall quality of urban outdoor places, The Journal of the Acoustical Society of America 131(4):3474-3474.
Pedersen, E., van den Berg, F., Bakker, R., Bouma, J., 2009, Response to noise from modern wind farms in The Netherlands, The Journal of
the Acoustical Society of America 126(2):634-643.
Pheasant, R. J., Fisher, M. N., Watts, G. R., Whitaker, D. J., Horoshenkov, K. V., 2010, The importance of auditory-visual interaction in theconstruction of ‘tranquil space’, Journal of environmental psychology 30(4):501-509.
Plehn, M., 2012, Wind energy in the baltic sea region 2.
Rafiee, A., Van der Male, P., Dias, E., Scholten, H., 2018, Interactive 3D geodesign tool for multidisciplinary wind turbine planning, Journalof Environmental Management 205(Supplement C):107-124.
Ruotolo, F., Maffei, L., Di Gabriele, M., Iachini, T., Masullo, M., Ruggiero, G., Senese, V. P., 2013, Immersive virtual reality andenvironmental noise assessment: An innovative audio-visual approach, Environmental Impact Assessment Review 41:10-20.
Simão, A., Densham, P. J., Haklay, M., 2009, Web-based GIS for collaborative planning and public participation: An application to thestrategic planning of wind farm sites, Journal of Environmental Management 90(6):2027-2040.
Sudarsono, A. S., Lam, Y. W., Davies, W. J., 2016, The effect of sound level on perception of reproduced soundscapes, Applied Acoustics
110:53-60.
Szychowska, M., Hafke-Dys, H., Preis, A., Kociński, J., Kleka, P., 2018, The influence of audio-visual interactions on the annoyance ratings
for wind turbines, Applied Acoustics 129(Supplement C):190-203.
Torija, A. J., Ruiz, D. P., Ramos-Ridao, A. F., 2013, Application of a methodology for categorizing and differentiating urban soundscapesusing acoustical descriptors and semantic-differential attributes, The Journal of the Acoustical Society of America 134(1):791-802.
Viollon, S., Lavandier, C., Drake, C., 2002, Influence of visual setting on sound ratings in an urban environment, Applied Acoustics 63(5):493-511.
Yu, T., Behm, H., Bill, R., Kang, J., 2017, Audio-visual perception of new wind parks, Landscape and Urban Planning 165:1-10.
Yu, T., Behm, H., Bill, R., Kang, J., 2018, Validity of VR Technology on the Smartphone for the Study of Wind Park Soundscapes, ISPRSInternational Journal of Geo-Information 7(4):152.

859