Statistics-based functional classification of roads in the urban area of Milan

On-line monitoring of road traffic noise in urban areas is becoming an important issue in modern cities. The dimensions of monitored areas are usually large and a spatial sampling strategy must be adopted to limit financial costs and, at the same time, guarantee the required accuracy and provide representative noise maps. The dataset considered in the present work is formed by 75 time histories of the 24-h continuous acoustic monitoring of road traffic noise in terms of the hourly equivalent level LAeqh taken at 35 different sites, including all the 8 functional road categories (from A to F and sub-classes). However, this classification generally does not reflect the actual use of roads. For this reason, the dataset was explored by means of a cluster analysis to find similarities among the 24-h continuous acoustic monitoring of the hourly equivalent LAeqh level. Once normalized, the resulting profiles provide a tool to pool roads according to their time pattern of noise.