Spatial and Temporal Analysis of Noise Pollution Based On GIS, Agglomerative Hierarchical Clustering and Principal Component Analysis (Case Study: Tehran)

Noise is an adverse factor in the living environments of today’s communities. This type of pollution has drawn attention to itself in the three recent decades, being a major problem in larger cities and seen as one of the significant environmental problems, blood pressure leading to cardiovascular disorders.

The paper studied Tehran, Iran. The study areas consisted of Tajrish Square, Tohid and Sattarkhan crossroads, Hakim Freeway and Hemmat Freeway of Tehran. The study areas were selected based on their traffic and urban importance. The survey measured sound levels, road slope, road width, traffic, and land use (residential, commercial, administrative, and green space).  In the field method, noise pollution level was measured using a sound level meter. Due to the role of traffic parameters, slope and residential, commercial, office and green space usage parameters, the parameters were recorded for each map of harvest. The spatial and temporal dependencies were extracted using "Agglomerative hierarchical clustering" and "principal components analysis".

The results indicate the critical significance of urban traffic in noise pollution, as by a large difference it had the highest contribution to noise level, followed by green space, administrative, and commercial land use; road width, and road slope.

It is recommended that for future roads or revamping the existing ones, more lanes be implemented to produce wider roads, prevent the construction of tall buildings on the sided of main roads, and maintaining a standard distance between buildings and main roads, freeways, and other motorways.