The Modeling of the Acoustic Condition of Urban Environment Using Noise Annoyance Assessment

Abstract

In the following article, a method of modeling urban environment exposed to road noise pollution for the purpose of noise nuisance assessment has been proposed. In order to accomplish it, GIS technology has been applied to divide the area under study into hexagonal fields. The presented case shows an area of urban environment exposed to noise pollution by means of object feature mapping, in each of the adopted elements. An acoustic and non-acoustic analysis of spatial distribution of the researched object features with the application of the adopted assessment indicators has been conducted. In particular, as assessment indicators, the following have been used: landscape entropy (H), L Aeq (noise_sr), Simpson's diversity index (SIDI), area and length of transportation network (R a , R l), buildings (GSI) and number of stories (FSI), predominance of land cover (LIPI), equality of class distribution (SIEI), and geodiversity index (G d). The statistical analysis of the validity of the aforementioned indices has also been carried out. For the purpose of noise annoyance assessment modeling, the application of statistically relevant assessment indicators has been proposed with the special use of the neural network method.

Seeking the Nexus Between Building Acoustics and Urban Form: A Systematic Review

“…Building-related features in outdoor studies showed a combination of findings while some found building density raising the noise level [ 17 •, 21 ], some others indicated that the number of buildings, floor space index include negative correlations with noise level [ 18 ]. On the other hand, building geometry shows more consensus on findings, where complex building geometry, height, length, number of floors, and commercial type of building include positive correlations with noise levels.…”

“…The study reported some key associations both for environmental and transportation-related noise factors. In another study, Paszkowski and Sobiech [ 18 ] calculated urban noise factors by using GIS. Operationalizing entropy, diversity, and transport data, the study mainly used building factors, such as floor space index, number of buildings, land cover, and building proportions, by using the neural network technique.…”

Effect of Landscape Elements and Structures on the Acoustic Environment on Wildlife Overpasses Located in Rural Areas

“…The decision on the actual number of the hexagonal fields into which to divide the area was taken at the map development stage. A similar approach was described in reference [51], when analysing annoyance to people caused by traffic noise in built-up areas. However, one of the most important principles of the comparative assessment of noise maps is to ensure homogeneity of the factors under analysis, which also has an effect on the level of noise but play a secondary role in a given case.…”

The assessment of acoustic effects of exploited road vehicles with the use of subjective features of sound

“…In work [18], it was examined, how the time change of the structure of road traffic influences the assessment of noise annoyance. Different grades of annoyance for the same L Aeq were obtained, which was due to the varying average percentile of loudness in sons (N 10 or N 5 ).…”

“…The results of the undertaken research, in the field of developing road noise assessment in the external environment, indicate clearly that the expression of this assessment with noise indicators is limited and insufficient. It is stated, that significant impact on the subjective assessment of noise has, among others the time structure of the signal, or the distribution of subjective features in the domain of time and frequency [6,18].…”