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    The effect of road traffic noise on the prices of residential property – A case study of the polish city of Olsztyn2015

    SENETRA A., SZCZEPANSKA A., WASILEWICZ-PSZCZOLKOWSKA M.Journaux et Revues (scientifiques)

    préférences révélées, prix hédoniques

    Transportation Research Part D: Transport and Environment
    Volume 36, May 2015, Pages 167–177


    Highlights

    • Traffic noise is a factor driving apartment prices.
    • An acoustic map as a source of information for property market analysis.
    • The values of the Noise Depreciation Sensitivity Index (NDSI) were calculated.
    • The spatial distribution of apartment prices in an urban agglomeration was presented.
    • The spatial distribution of traffic noise levels in an urban agglomeration was analyzed.

    Abstract

    The key factors that determine the prices of real estate are location, technical standard of property as well as the local environment. In urban agglomerations, road traffic noise has a considerable impact on the purchasing decisions made by apartment buyers. This is a widespread problem in Central-Eastern Europe. The main objective of this study was to verify the working hypothesis that apartment prices are correlated with traffic noise levels in Olsztyn, the capital city of the Region of Warmia and Mazury in north-eastern Poland.

    The study was carried out in four principal stages. Firstly, traffic noise intensity was determined for apartments (objects of real estate transactions concluded in 2013), based on an acoustic map for the city of Olsztyn. The map was developed in line with the provisions of Directive 2002/49/EC of the European Parliament and of the Council of 25 June 2002 relating to the assessment and management of environmental noise. Secondly, the values of the Noise Depreciation Sensitivity Index (NDSI) were calculated. NDSI determines the percentage change in property prices per dB increase in noise levels. The distribution of unit prices of apartments was mapped relative to noise levels, and the relationships between the analyzed variables were assessed. Thirdly, linear correlations between the unit prices of apartments and noise levels were analyzed. The strength and direction of relationships between the analyzed parameters were determined based on Pearson’s correlation coefficient. In the last stage, the distribution of the unit prices of apartments was mapped by ordinary kriging, a geostatistical estimation method. The research hypothesis was confirmed by comparing the spatial distribution of traffic noise levels measured in stage 1 with the spatial distribution of apartment prices.

    http://www.sciencedirect.com/science/article/pii/S1361920915000206

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