Relationship between green space-related morphology and noise pollution
Relationship between green space-related morphology and noise pollution
Green spaces have been proved to have a positive effect on traffic noise pollution in the local scale; however their effects have not been explored on the urban level. This paper investigates the effects of green space-related parameters from a land cover viewpoint on traffic noise pollution in order to understand to what extent greener cities can also be quieter. A triple level analysis was conducted in the agglomeration, urban and kernel level including various case study cities across Europe. The green space parameters were calculated based on land cover data available in a European scale, while traffic noise data were extracted from online noise maps and configured in noise indices. In the first level 25 agglomerations were investigated, six of which were further analyzed in the urban and kernel levels. It was found that the effect of green spaces on traffic noise pollution varies according to the scale of analysis. In the agglomeration level, there was no significant difference in the cluster of the higher green space index and the percentage of people exposed in the lowest (55–59 dB(A)) or the highest noise band of more than 70 dB(A). In the urban level it was found that lower noise levels can possibly be achieved in cities with a higher extent of porosity and green space coverage. Finally, in the kernel level a Geographically Weighted Regression (GWR) analysis was conducted for the identification of correlations between noise and green. Strong correlations were identified between 60% and 79%, while a further cluster analysis combined with land cover data revealed that lower noise levels were detected in the cluster with higher green space coverage. At last, all cities were ranked according to the calculated noise index.
921-933
Margaritis, Efstathios
bccaaf39-3821-485e-b282-a54b71033fe4
Kang, Jian
6afbc9a6-9338-449c-9cb9-24994c1c1c87
Margaritis, Efstathios
bccaaf39-3821-485e-b282-a54b71033fe4
Kang, Jian
6afbc9a6-9338-449c-9cb9-24994c1c1c87
Margaritis, Efstathios and Kang, Jian
(2016)
Relationship between green space-related morphology and noise pollution.
Ecological Indicators, 72, .
(doi:10.1016/j.ecolind.2016.09.032).
Abstract
Green spaces have been proved to have a positive effect on traffic noise pollution in the local scale; however their effects have not been explored on the urban level. This paper investigates the effects of green space-related parameters from a land cover viewpoint on traffic noise pollution in order to understand to what extent greener cities can also be quieter. A triple level analysis was conducted in the agglomeration, urban and kernel level including various case study cities across Europe. The green space parameters were calculated based on land cover data available in a European scale, while traffic noise data were extracted from online noise maps and configured in noise indices. In the first level 25 agglomerations were investigated, six of which were further analyzed in the urban and kernel levels. It was found that the effect of green spaces on traffic noise pollution varies according to the scale of analysis. In the agglomeration level, there was no significant difference in the cluster of the higher green space index and the percentage of people exposed in the lowest (55–59 dB(A)) or the highest noise band of more than 70 dB(A). In the urban level it was found that lower noise levels can possibly be achieved in cities with a higher extent of porosity and green space coverage. Finally, in the kernel level a Geographically Weighted Regression (GWR) analysis was conducted for the identification of correlations between noise and green. Strong correlations were identified between 60% and 79%, while a further cluster analysis combined with land cover data revealed that lower noise levels were detected in the cluster with higher green space coverage. At last, all cities were ranked according to the calculated noise index.
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Accepted/In Press date: 19 September 2016
e-pub ahead of print date: 6 October 2016
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Local EPrints ID: 483069
URI: http://eprints.soton.ac.uk/id/eprint/483069
ISSN: 1470-160X
PURE UUID: ea861727-f04c-459a-aa5a-32e33628e74c
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Date deposited: 20 Oct 2023 17:39
Last modified: 18 Mar 2024 04:12
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Author:
Efstathios Margaritis
Author:
Jian Kang
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