GIS-Based Model for Highway Noise Analysis
Publication: Journal of Infrastructure Systems
Volume 15, Issue 2
Abstract
Elevated noise levels due to vehicular traffic are cause of grave concern in residential areas. They can significantly reduce property values. Most of the highway noise literature has been focused in predicting noise levels, estimating cost of installing noise barriers, and assessing effectiveness of noise barriers in reducing the amount of noise. The Federal Highway Administration’s traffic noise model (TNM) is typically used to estimate noise levels due to vehicular traffic in the vicinity of residential properties. One key problem in highway noise analysis that has received limited attention is to automatically identify highway segments along which installation of noise barriers may be warranted due to elevated noise levels. This can be made possible by integrating the geographic information system’s (GIS’s) spatial modeling capability and the TNM methodology. In this paper, a GIS-based model for identifying highway segments for noise barrier installation is developed that uses TNM for noise level prediction. The method can automatically detect highway segments where installation of noise barriers may be warranted. In addition, the method also calculates effective length of noise barriers to be installed. An example is performed using Maryland’s GIS database to demonstrate the capability of the proposed model. The proposed model can also work with highway alignment optimization models by identifying segments with unacceptable noise levels. Noise abatement costs for those segments can be calculated and considered in the optimal search ensuring minimum noise impact to residential communities. Several enhancements to the model remain to be worked on in the future. It is recognized that the positional accuracy of GIS data may limit the practical application of the proposed approach. Additional research is needed to address this issue.
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Acknowledgments
The writers are thankful to many valuable comments of the three anonymous reviewers, which improved the quality of the paper. This work was performed at the Center for Advanced Transportation and Infrastructure Engineering Research (CATIER; www.eng.morgan.edu/∼catier) at the Morgan State University.
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Information & Authors
Information
Published In
Journal of Infrastructure Systems
Volume 15 • Issue 2 • June 2009
Pages: 88 - 94
Copyright
© 2009 ASCE.
History
Received: Nov 15, 2004
Accepted: Nov 19, 2007
Published online: May 15, 2009
Published in print: Jun 2009
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