TY - JOUR
T1 - Multi-sensory landscape assessment
T2 - The contribution of acoustic perception to landscape evaluation
AU - Gan, Yonghong
AU - Luo, Tao
AU - Breitung, Werner
AU - Kang, Jian
AU - Zhang, Tianhai
N1 - Publisher Copyright:
© 2014 Acoustical Society of America.
PY - 2014/12/1
Y1 - 2014/12/1
N2 - In this paper, the contribution of visual and acoustic preference to multi-sensory landscape evaluation was quantitatively compared. The real landscapes were treated as dual-sensory ambiance and separated into visual landscape and soundscape. Both were evaluated by 63 respondents in laboratory conditions. The analysis of the relationship between respondent's visual and acoustic preference as well as their respective contribution to landscape preference showed that (1) some common attributes are universally identified in assessing visual, aural and audio-visual preference, such as naturalness or degree of human disturbance; (2) with acoustic and visual preferences as variables, a multi-variate linear regression model can satisfactorily predict landscape preference (R2= 0.740), while the coefficients of determination for a unitary linear regression model were 0.345 and 0.720 for visual and acoustic preference as predicting factors, respectively; (3) acoustic preference played a much more important role in landscape evaluation than visual preference in this study (the former is about 4.5 times of the latter), which strongly suggests a rethinking of the role of soundscape in environment perception research and landscape planning practice.
AB - In this paper, the contribution of visual and acoustic preference to multi-sensory landscape evaluation was quantitatively compared. The real landscapes were treated as dual-sensory ambiance and separated into visual landscape and soundscape. Both were evaluated by 63 respondents in laboratory conditions. The analysis of the relationship between respondent's visual and acoustic preference as well as their respective contribution to landscape preference showed that (1) some common attributes are universally identified in assessing visual, aural and audio-visual preference, such as naturalness or degree of human disturbance; (2) with acoustic and visual preferences as variables, a multi-variate linear regression model can satisfactorily predict landscape preference (R2= 0.740), while the coefficients of determination for a unitary linear regression model were 0.345 and 0.720 for visual and acoustic preference as predicting factors, respectively; (3) acoustic preference played a much more important role in landscape evaluation than visual preference in this study (the former is about 4.5 times of the latter), which strongly suggests a rethinking of the role of soundscape in environment perception research and landscape planning practice.
UR - http://www.scopus.com/inward/record.url?scp=84915788454&partnerID=8YFLogxK
U2 - 10.1121/1.4898424
DO - 10.1121/1.4898424
M3 - Article
C2 - 25480067
AN - SCOPUS:84915788454
SN - 0001-4966
VL - 136
SP - 3200
EP - 3210
JO - Journal of the Acoustical Society of America
JF - Journal of the Acoustical Society of America
IS - 6
ER -