Dynamic analysis of traffic noise across various land uses based on real-time data

Traffic noise is one of the most significant forms of environmental pollution in urban areas. It can have negative impacts on both road users and residents living near highways. The high growth rate of motor vehicles from year to year in Kendari City has triggered an increase in traffic noise levels. This study aims to analyze the distribution of traffic noise across various land uses by utilizing real-time data. Noise measurements were conducted using a sound level meter (SLM) at several sampling points representing residential, commercial, service, office, school, and public facility areas. The SLM was positioned 1 m and 10 m away from the edge of the road. According to the findings of the analysis, Kendari City’s traffic noise levels have exceeded the environmental noise threshold. The study found that the main factors contributing to high noise levels are traffic volume and low vehicle speed. Areas with high traffic volumes, such as service, commercial, and office zones, produce higher noise exposure compared to other land use types. Land uses located near social activity centers are significantly impacted by noise exposure. Real-time data-based noise mapping is highly effective in designing sustainable urban transportation and spatial planning policies in cities with heterogeneous traffic categories.