A GIS-Based Traffic Noise Model for Street Intersections

Noise pollution represents one of the major negative impacts of traffic, causing significant harm to humans as well as animal life. While traffic noise models in the literature are abundant, only a few complex models allow for modeling of noise at traffic intersections, and simpler ones are severely limited. Accordingly, this paper presents a simpler GIS-based model to estimate noise at traffic intersections. A case study using real-life traffic and noise data for a typical signalized intersection was adopted, where directional volumes were collected, and noise levels were measured. The recorded noise values were contrasted against the developed GIS-based model estimates. The GIS-based model was developed using ESRI's ArcGIS 10.5, and its Spatial Analyst extension and Model Builder programming language. Graphical and numerical analyses of the measured and modeled noise level estimates indicated: 1) significantly high correlations between the measured and estimated values, and 2) model estimates were approximately 3 dB higher than the measured ones. Therefore, a linear regression model was developed to correct the GIS-based model noise estimates. Outcomes of this research would be highly valuable for users interested in adopting a simpler method for estimating noise at traffic intersections.