Effects of open green spaces and urban form on traffic noise distribution
Effects of open green spaces and urban form on traffic noise distribution
The aim of this study is to examine the effect of urban form and green spaces in relationship with traffic noise distribution. For the analysis, a Matlab code was implemented to calculate the basic Ln indexes. At the same time, spatial analysis through GIS was applied for the rest of the indicators. In total twelve variables were tested using Sheffield and Brighton as test sites. The outcomes are organised in a three level approach. In the first one, the correlation between Lnindexes and green space is presented. In the second level, possible quiet zones are identified usinga cluster analysis indicator. At last, the most correlated variables for both cities are identified through Pearson correlation analysis. Results prove that different indicators are prevalent to each city. Consequently more cites have to be tested in order to have a robust noise prediction formula.
Margaritis, Efstathios
bccaaf39-3821-485e-b282-a54b71033fe4
Kang, Jian
14529396-9429-4b49-8a99-9847edce4961
2014
Margaritis, Efstathios
bccaaf39-3821-485e-b282-a54b71033fe4
Kang, Jian
14529396-9429-4b49-8a99-9847edce4961
Margaritis, Efstathios and Kang, Jian
(2014)
Effects of open green spaces and urban form on traffic noise distribution.
Forum Acusticum, Poland, Republic of, Krakow, Poland.
07 - 12 Sep 2014.
6 pp
.
Record type:
Conference or Workshop Item
(Paper)
Abstract
The aim of this study is to examine the effect of urban form and green spaces in relationship with traffic noise distribution. For the analysis, a Matlab code was implemented to calculate the basic Ln indexes. At the same time, spatial analysis through GIS was applied for the rest of the indicators. In total twelve variables were tested using Sheffield and Brighton as test sites. The outcomes are organised in a three level approach. In the first one, the correlation between Lnindexes and green space is presented. In the second level, possible quiet zones are identified usinga cluster analysis indicator. At last, the most correlated variables for both cities are identified through Pearson correlation analysis. Results prove that different indicators are prevalent to each city. Consequently more cites have to be tested in order to have a robust noise prediction formula.
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Published date: 2014
Venue - Dates:
Forum Acusticum, Poland, Republic of, Krakow, Poland, 2014-09-07 - 2014-09-12
Identifiers
Local EPrints ID: 483066
URI: http://eprints.soton.ac.uk/id/eprint/483066
PURE UUID: bc1dfdc3-1d06-4382-ac00-ca31d91feba3
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Date deposited: 20 Oct 2023 17:37
Last modified: 27 Feb 2024 03:17
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Contributors
Author:
Efstathios Margaritis
Author:
Jian Kang
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