Noise Pollution Analysis Using Geographic Information System, Agglomerative Hierarchical Clustering and Principal Component Analysis in Urban Sustainability (Case Study: Tehran)

Abstract

In this study, a new approach has been used with SPSS and MATLAB analysis to study urban road traffic noise distribution mapping, to obtain the representative road traffic noise maps. The observation has been performed at a high traffic highway. The factors influencing noise level (traffic, road width, slope, and residential or administrative–commercial land) use were surveyed and recorded for each point and their local and time dependencies were computed. According to the analysis, the maximum value of goodness of fit index for the traffic and noise level relationship was 0.64, followed by 0.489 for the percentage of residential land use. The result of this study showed that the vehicle speed, width of the road, and the land use can affect different sound levels emitted by moving vehicles on road. The model predicts that by increasing one vehicle per hour, an increase in noise level by 0.002 dB will happen.