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), LAeq (noise_sr), Simpson’s diversity index (SIDI), area and length of transportation network (Ra, Rl), buildings (GSI) and number of stories (FSI), predominance of land cover (LIPI), equality of class distribution (SIEI), and geodiversity index (Gd). 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.
Highlights
The problem of noise pollution in urban environment is troublesome in the place of residence
An original approach to acoustic research in the urban environment based on identification, separation, and assessment of object features within the basic fields of the studied area has been proposed
The application of neural network as a method of modeling noise annoyance assessment has been proposed on the basis the obtained results of spatial distribution of indicators and noise annoyance
Summary
The problem of noise pollution in urban environment is troublesome in the place of residence. The commonly used approach to the noise pollution assessment in the place of residence is limited to determining the quantitative indicator by means of reflective modeling and mapping: environment sites as well as distribution of the sound level [4]. This approach causes certain limitation in assessing noise pollution hazard only to physical features of sound, whereas on the other hand, it overlooks the meaning and significance of the psychoacoustic aspects of noise, including noise annoyance. Research conducted in this area is justified by applying advanced modeling methods in evaluating the environment endangered by noise [9]. It is assumed that the solutions applied will be based on taking into consideration physical parameters of acoustic signal assessment, and on the evaluation of spatial distribution of selected measurements of objects in the urban environment
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