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

Recently, GIS applied to environmental protection has been an emphasis in the world. According to the development of the industry, traffic noise has become to be a great environmental pollution. And it also affects people's life seriously. Thus, developing a prediction system of traffic noise will provide more advices for environmental planning. This research develops a GIS based urban road traffic noise prediction system by using GIS control.Firstly, it studies on GIS and its applying in environmental protection fields. Then it researches on the characteristics, actuality and managing methods of urban road traffic noise. The model adopted for traffic noise prediction is put forward by Bengang Li in Peking University. This model is performed following Chinese GB standards, so it is more suitable for Chinese urban road. Meanwhile, it designs a small GIS software platform by combining the main characteristic of the GIS control and the theory of model. It introduces the structure and working process of this system as well as several main program modules. The software of system is developed by Visual Basic 6.0 and MapObjects 2.1 control. And it also uses SQL Sever to realize analysis, storage and management of the mass geographic data. Finally, this system can implement functions as following: predict, analyse, search and output the traffic noise value of the received points in the living building which is near by the street; simulate some method to reduce the noise value, such as adding greenbelts or sound barriers; scientific management of geographic data, such as traffic noise values; realize all kinds of functions to operate the map.Since GIS is seldom applied in environmental noise prediction fields, this research has some meaning. It can publish accurate and identical channels for information's coming, accelerate the update rate of environmental information, and increase the use efficiency of environmental information resources by studying and implement the urban road traffic noise prediction system. Besides, it can also reduce the burden of these people who work on it for environmental planning and estimating.