A traffic big data analysis on relationships between urban planning and traffic noise level--taking Dongguan Demonstration Area, China as an example

Abstract

With the promotion of smart city research, traffic big data has become a new way to study urban traffic noise. Taking Dongguan Demonstration Area, China as an example, this research discussed the relationships between traffic noise levels and urban plannings using geographic information scienceGIS, global positioning system (GPS) techniques and OpenITS Organization OpenData. The results showed that, for the whole area, some planning factors, say global integration, local integration (R=500m), global betweenness, local betweenness (R=500m) and number of points of interest (POIs) had significant positive correlations with the daytime traffic noise levels. Among them, the number of POIs had the strongest correlation with the traffic noise levels (r=0.560 p<0.01). However, the degree of influence of each variable on traffic noise levels can be changed with geographical locations. This research also identified specific areas where traffic noise levels were negatively correlated with local integration and local betweenness, which had great potential to provide a recreational and peaceful place for people to walk. Therefore, the urban areas' centers and fringes can be studied separately to effectively control traffic noise by changing the urban plannings.