The purpose of this study is to present a statistical model which can predict the noise level of road-traffic in urban area. A spatial statistical model which can take into account spatial dependency on geographically neighboring areas is constructed from a noise map of a city in South Korea. A system of 250m×250m grid cells is placed on the city of Cheongju, South Korea, and the noise level and urban form indicators are averaged over each cell. The population-weighted mean of the noise level is subsequently regressed on the average urban form by adopting the spatial autoregressive model (SAR) and the spatial error model (SEM), as well as an ordinary least squares (OLS) model. Direct and indirect impacts are analyzed for a valid interpretation of the spatial statistical models. Factors such as GSI, FSI, traffic volume, traffic speed, road area density, and the fraction of industrial area turn out to have significant impacts on the noise level

Sustainable transportation is an essential part of a sustainable city; however, modern transportation systems with internal-combustion engines emits unacceptably high level of air-pollutants and noise. It is recognized widely that road-traffic noise has negative health impacts (such as annoyance and sleep disturbance) on exposed population in highly-populated cities. These harmful effects should be removed or at least reduced to guarantee the sustainability of modern cities. The estimation of pollutant levels at a specific location and the extent of the damage is therefore important for policy makers. This study presents a procedure to determine the levels of road-traffic noise at both day and night, and an assessment of the adverse health effects across Gwangju Metropolitan City (GMC), Republic of Korea (ROK). Road-traffic noise maps in 2-D and 3-D were generated, in order to find spatial distribution of noise levels across the city and noise level at the façade of a building-floor, respectively. The adoption of existing assessment models for the highly-annoyed (%HA) and highly-sleep-disturbed (%HSD) leads to building-based estimation of the affected population and spatial distribution of the road networks of the city. Very high noise levels were found to exist along major roads in the day and at night, with little difference between them. As a result, approximately 10% and 5% of the total population (n = 1,471,944) were estimated to experience high-level annoyance and sleep disturbance, respectively.