HighlightsAssessing noise and visual impacts of motorways in an integrated approach.Traffic condition, distance and landscape type are influential on perceived impact.Noise exposure can be a potential indicator for the integrated impact.

    AbstractMotorways are often seen as intrusive to both landscape and soundscape, and recent studies on multisensory perception suggest that an integrated assessment of the environmental impacts is necessary. This paper investigates the effects of traffic condition, distance to road and background landscape on the perceived integrated impact of noise and visual intrusion of motorways, and explores if noise exposure can be a powerful indicator for the perceived integrated impact. Six traffic conditions, consisting of three levels of noise emission×two levels of heavy good vehicle percentage in traffic composition, two types of background landscape and three distances to road, were designed as experimental scenarios, and created using computer visualisation and edited audio recordings. A laboratory experiment was carried out to obtain ratings of perceived environmental quality of each experimental scenario. The results show that traffic volume as expressed by noise emission level strongly influenced the perceived integrated impact, whereas traffic composition did not make noticeable differences. Distance to road was the second most influential factor, followed by background landscape. A regression model using noise level at receiver position and type of background landscape as independent variables was developed and can explain about a quarter of the variation in the perceived integrated impact.


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    Titel :

    Perceived integrated impact of visual intrusion and noise of motorways: Influential factors and impact indicators


    Beteiligte:
    Jiang, Like (Autor:in) / Kang, Jian (Autor:in)


    Erscheinungsdatum :

    2017-01-01


    Format / Umfang :

    7 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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