The Development Of A GIS Based Urban Road Traffic Noise Prediction System

With the rapid development of road infrastructure in the city, the noise pollution of road traffic is becoming increasingly serious. In order to control the urban road traffic noise and to improve the urban living environment effectively, it is necessary to develop a system which could manage the urban noise information of road traffic and offer information services such as predicting the traffic noise, simulating effective ways of reducing noise and etc. In this research, such a system based on geographic information system is developed.This paper analyzes the characteristics, current situations and management methods of the urban road traffic noise. After researching the current application situations of combining traffic noise prediction with GIS both in China and abroad, this paper introduces two models: one is the U.S.A. FHWA noise prediction model, which is highly improved and with a high predicting precision; the other is the Ministry of Communications standard prediction model, which is put forward according to the characteristic of traffic noise in China. Based on research of the two prediction models' formulations, adaptation conditions and relevant revisions, a GIS based noise prediction system with comparatively complete functions is developed. This development uses GIS component technology and follows software engineering principles. MapObjects control is used as the main development tool in visual basic integrated environments. By providing the basic functions of GIS, this system can be used as tool for scientific management of the geographic information in the city. As the system has integrated noise prediction models, it can not only predict and analyze the traffic noise, but also can provide flexible search methods and different ways to display the prediction results. In addition, it also provides simulation measures, such as building sound barrier, lawn, forest, to reduce the traffic noise.This system provides many useful practical functions. By setting up a scientific management and decision platform for the improvement of noise environment in the city, it can lighten the burden of environmental workers and improve the efficiency of environmental management. This research is significant since GIS is seldom applied in environmental noise prediction fields. It also provides a reference mode for developing applications using GIS in the noise prediction field.