رابطه بین فضاهای شهری سبز و سایر ویژگی های مورفولوژی شهری با توزیع صدای ترافیک
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|65697||2016||12 صفحه PDF||سفارش دهید||محاسبه نشده|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Urban Forestry & Urban Greening, Volume 15, 2016, Pages 174–185
The effect of greenery on traffic noise mitigation has been extensively studied on the level of single plants, green walls, berms and hedges, but not considering whole sample areas within the cities. Therefore, the aim of this paper is to investigate the relationship between features of urban morphology related to green spaces, roads or buildings and traffic noise distribution in urban areas. The analysis was applied in eight UK cities with different historical and architectural background, following two different settlement forms (radial, linear). In each city a 30 km2 grid was defined and three different levels of approach were considered (macro-scale, meso-scale, micro-scale). The first level regarded the eight cities as single entities, while in the second one every single tile of the applied grid was investigated in two different cities. In the third level only the eight city centres were analyzed. Statistical analysis was used combined with GIS tools. In total 18 variables were constructed and tested for possible relationships with noise levels (Lden). It was found that in spite of the fact that each city has its own dynamic and form, features of urban morphology were related to traffic noise levels to a different extent at each scale. At the macro-scale, the green space pattern was related to the structure of the city as well as the traffic noise levels in combination with the rest of the morphological parameters. At the meso-scale, an increase in internal road connectivity contributed to higher traffic noise. Green space variables explained part of the variance in traffic prediction models. Finally, at the micro-scale, it was also proved that different areas can have the same building coverage but different noise levels. Therefore, these indexes could be profiled and used as an “a priori” tool for urban sound planning.