The influence of urban tree characteristics on environmental noise in Montreal, Canada

Abstract

BACKGROUND AND AIM: Vegetation can reduce environmental noise, but limited information exists regarding how specific characteristics of trees of the urban forest influence environmental noise. We investigated the physical characteristics of urban trees that influence environmental noise measurements in Montreal, Canada. METHODS: We used Light Detection and Ranging (LiDAR) point cloud data from 2015 to extract the characteristics of all trees across the island of Montreal. Needle and broadleaf trees were distinguished with a Random Forest algorithm. Based on individual tree characteristics, we computed the total area of the tree crown footprint, the mean tree crown centroid height, the mean volume of tree crowns, and the percentage of broadleaf trees within various buffers (250 to 1000m) around 87 noise measurement sites across the city. Noise measurements were taken over a two-week period in the spring of 2010. Random Forest regression models were used to estimate the variation in noise around measurement sites related to tree characteristics, the Normalized Difference Vegetation index (NDVI), and distances of the measurement sites to major noise sources (highways, railways, and roads). RESULTS:The 24-hour equivalent noise levels averaged across the 87 monitoring sites were 57.5 + 5.1 dBA. The mean crown centroid tree height (5.2 + 0.4m) and the total area of crown footprint (130.7k + 63.4m2) within 500m of each site location were the strongest predictors of measured noise levels. The percentage increased mean squared errors indicated that in 500m buffers, the total area of the crown footprint (29.2%) and the mean crown centroid height (12.6%) were associated with a stronger noise decrease than NDVI (3.2%); similar patterns were observed with other buffers. CONCLUSIONS:Our findings suggest that tree crown footprint and centroid height, and not just the overall amount of vegetation, may play a vital role in reducing urban noise levels. KEYWORDS: Built environment, Green space, Noise