| Author: | Gao, Yunfang |
| Title: | Development of GIS-based urban road traffic noise model in Hong Kong |
| Degree: | M.Sc. |
| Year: | 2014 |
| Subject: | Traffic noise -- Measurement. Traffic noise -- China -- Hong Kong. Geographic information systems -- China -- Hong Kong. Hong Kong Polytechnic University -- Dissertations |
| Department: | Faculty of Construction and Environment |
| Pages: | xi, 114 leaves : color illustrations ; 30 cm |
| Language: | English |
| Abstract: | Currently, urban road traffic noise pollution is one of the major environmental issues that affects people's health and daily lives, it is necessary to develop a strategic planning and management tool for road traffic noise control. Noise mapping is considered as one of the useful means to visualize the environmental noise conditions. There are dedicated commercial software for environmental noise calculation and mapping software, but these prediction tools are expensive, not very flexible and have its limitations. Noise pollution is a spatial-dependent phenomenon which is strongly corrected to the morphology of terrain. A geographic information system (GIS) is suitable to analyze and process geographically referenced information. Thus, the goal of this study is to develop a GIS-based customized road traffic noise mapping tool to produce noise maps in Hong Kong. In order to improve the efficiency of computation, a simplified noise prediction model was developed. Visual Studio programming environment from Microsoft with C#, ArcGIS Engine components and personal geo-database from ESRI were used to implement this noise prediction tool. This prediction tool is available for basic GIS operations, noise calculation and query of road segments and reception points, generating colored noise maps with contours and noise map output. As a case study, this noise prediction tool was used to create noise map of Kowloon Tong in Hong Kong to test the performance of this noise mapping tool and do accuracy validation in the central part of Kowloon. Regarding accuracy, three hypothesis tests are applied. The calculated noise levels from this noise prediction tool are 1 dB(A) underestimated at 5% significance level and there is no difference between the predicted and measured noise level when the predicted noise levels are larger than 50dB(A) at 5% significance level. However, lots of factors would influence the accuracy of prediction results. The accuracy mainly depends on the mathematical noise model, the quality of input data and the validity of measured noise levels. |
| Rights: | All rights reserved |
| Access: | restricted access |
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| File | Description | Size | Format | |
|---|---|---|---|---|
| b27591086.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 3.13 MB | Adobe PDF | View/Open |
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