Estimation of Spatial Variations in Urban Noise Levels with a Land Use Regression Model

Abstract

Background: Outdoor noise is a source of annoyance and health problems in cities worldwide. Objective: We developed a land-use regression using a GAM Model to estimate the spatial variation of noise levels in Montreal. Methods: Noise levels were measured over a two week period during the summer of 2010 at 87 sites and during the winter of 2011 at 62 sites. A land use regression model was produced for both seasons to estimate noise levels as LAeq24h (resolution of 20 m). A leave one out cross-validation (LOOCV) was performed. Results: LAeq24h measured range from 53.4 to 73.7 dBA for the summer and from 54.1 to 77.7 dBA for the winter. The land use regression models explained 64 % of spatial variability for the summer and 40 % for the winter. The main predictors are the Normalized Difference Vegetation Index; the length of vehicular arteries, highways, and bus lines; and the proximity to an international airport. The Root mean square error ??from the LOOCV was 3.3 and 4.5 dBA for the summer and the winter respectively. Conclusion: The model explained a large part of the variability in noise levels and the RMSE remain relatively important on the noise levels scale.