Urban traffic noise and the relation to urban density, form, and traffic elasticity

2017

Ecological Indicators

127

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.

Section: Introductionmentioning

confidence: 99%

Relationship between green space-related morphology and noise pollution

Margaritis

2017

Ecological Indicators

127

“…In previous studies on urban environments (e.g., solar potential, atmospheric environment and traffic noise), urban morphological factors, for example building density, building patterns, street layout and coverage and landscaping, have been represented and studied using a number of quantitative urban morphological parameters (Cheng et al, 2006;Xie et al, 2006;Salomons and Pont, 2012). However, there is a shortage of integrated research on green areas from the perspectives of both birdsong loudness and visibility of green areas in the context of urban morphology to suggest practical landscape and urban design guidelines.…”

Section: Introductionmentioning

confidence: 99%

Integrated effects of urban morphology on birdsong loudness and visibility of green areas

Hao

Landscape and Urban Planning

Krijnders³

2015

Abstract:The aim of this study is to determine how to increase birdsong loudness and the visibility of green areas in low-density residential areas by controlling urban morphological parameters. The spatial sound level distributions of birdsong at 12 sites sampled from a GIS database of Assen, the Netherlands, were simulated by noise mapping techniques and calculated using a MATLAB program on spatial sound level matrices. The visibilities of green areas are analysed and calculated by Visibility Analysis Graph in Space Syntax. Correlation analyses were conducted between the obtained data on spatial sound level indices, the mean visibility and urban morphological parameters. The results show that birdsong loudness has significant positive linear relationships with urban morphological parameters, including Building Plan Area Fraction (R 2 =0.491), Green Area Perimeters (R 2

“…Therefore, the improvement of urban morphology parameters, which is a method for suppressing traffic noise, has attracted an increased level of attention from researchers. Salomons and Pont (2012) analyzed the influence of urban density, urban structure and traffic elasticity on traffic noise. Guedes et al (2011) analyzed the influence of construction density, the existence of open spaces and the location of street construction on environmental noise distribution.…”

Section: Introductionmentioning

confidence: 99%

Analysis of traffic noise distribution and influence factors in Chinese urban residential blocks

Zhou

Environment and Planning B: Urban Analytics and City Science

Zou

et al. 2016

To improve the acoustic environment of residential blocks, noise mapping is employed in this study to analyze traffic noise distribution and the influence factors of four types of residential blocks in China. The study shows that high-rise small blocks have the highest average noise level (L avg ) for ground and building facades, followed by small low-rise blocks while modern residential blocks yield the lowest value. An analysis of the standard deviation (STD) of spatial statistical noise level (L n ) shows that the STD of the ground and building façade of two types of small blocks is higher than that of other blocks. The analysis of influence factors indicates that the lot area of residential block has significant negative correlation with ground and building facade average noise level (L avg ) , and street coverage ratio (SCR) has significant positive correlation with ground and building facade average noise level (L avg ). In low-rise and high-rise small blocks, ground space index (GSI) has significant negative correlation with ground and building facade average noise level (L avg ); street interface density (SID) has significant positive correlation with the STDs of ground and building facade noise. Floor space index (FSI) shows significant positive correlation with the STDs of ground and building facade noise in low-rise small blocks.