An efficient method of predicting traffic noise using GIS

Nowadays, Geographic Information Systems (GIS) has been widely applied in traffic noise prediction to manage the spatial data and to realize the visualization of noise levels. But the common method we use to calculate the noise level of traffic has to sum up the noise levels of all the road segments logarithmically and that is really time-consuming. In order to accelerate the calculation process, a method of filtering road segments using GIS is proposed in this paper. This method focuses on selecting out the road segments which contribute the most to the noise level at the sensitive point. This approach can increase the computational efficiency in a large degree. Finally, this method is validated and proven to be accurate and efficient.

1. INTRODUCTION

Traffic noise prediction models have been applied in many previous studies to plan more environment-friendly roads especially since the Federal Highway Administration (FHWA) released a traffic-noise model in 1978. However, most results of digital calculation in previous studies are noise levels in certain locations and cannot provide a full view of the study area [1]. Taking advantages of the function of spatial analysis and the geographical database, Geographic Information System (GIS) has been widely applied in traffic noise prediction in recent years. Pichai Pamanikabud et al. used GIS to analyze and forecast highway traffic noise and the system he developed enabled the analysts and planners to visually see and assess the impacts of traffic noise [2]. Bengang Li et al. developed an integrated noise-GIS system which provided the general functions for modeling different kinds of noise [3]. Manoj K. Jha et al. developed a GIS-based model for identifying highway segments for noise barrier installation and for calculating the effective length of noise barriers to be installed as well [4].