<p>Traffic flow on urban roads is a major contributor to sound pollution, which affects the community welfare detrimentally. Two-dimensional (2D) noise prediction models are limited in their capacity to precisely predict the influence of traffic-induced noise at various heights. Three-dimensional (3D) noise prediction models consider the vertical dimension, allowing for a more realistic assessment of how noise impacts buildings and their occupants at various heights. The consideration of the population exposed to noise in buildings and development of a population annoyance index are indeed crucial aspects when studying and mitigating noise pollution. The development of Geographic Information System tools for estimating the noise-exposed population and for 3D noise prediction is the significant contribution of this study in noise pollution research. This is a powerful approach for identifying noise hotspots in urban areas.</p>