Vegetation Thresholds and Spatial Variation in Sustainable Urban Noise Mitigation: A Case Study from Charlotte, NC

Abstract

City noise is a significant health issue, particularly in expanding metropolitan areas like Charlotte, North Carolina. This research examines the potential for vegetation density to mitigate transportation noise as a sustainable solution. The analysis used the Normalized Difference Vegetation Index (NDVI), population density, and transportation noise zones from the USA Department of Transportation, evaluated at the census block group level all for 2020. To identify overall patterns, a Spatial Autoregressive (SAR) model and Geographically Weighted Regression (GWR) were used for spatial structure and local variation, with distance to high-noise transportation zones used as a proxy for extreme noise exposure. The SAR model (AIC = 8476.5; RMSE = 1174.7 m) revealed a vegetation threshold of 35.2%, beyond which the benefits of vegetation for noise buffering became more pronounced. The GWR model uncovered spatial heterogeneity in the strength of vegetation’s effect, with stronger mitigation in southern and eastern parts of Charlotte. To conclude, we propose a three-tier spatial framework to prioritize neighborhoods for green infrastructure investment, particularly those with low vegetation, higher population density, and low natural noise protection. These findings emphasize the importance of incorporating vegetation density thresholds and spatial variability into noise mitigation strategies to support sustainable urban environments.