Abstract
For policy makers, understanding the magnitude and impact of rail noise in the community is critical to the design and implementation of effective noise mitigation programs and projects. Traditionally, policy makers have used noise monitoring and modelling to address specific questions and concerns about the level of noise and impact on the community. Though useful, current monitoring and modelling data is not easily accessible or easily analysed in a comprehensive manner. A key challenge for policy makers is to collate information from a variety of sources and present it in a format that is easy to understand and can be used to inform the delivery and evaluate the effectiveness of rail noise mitigation over time. To address this, Transport for NSW has developed a Geographical Information System (GIS) that gathers, centralises and displays different types of freight rail noise data collected from across the Sydney rail network. This system integrates:
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Complaints data i.e. the number and nature of complaints received per year for each suburb;
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Noise monitoring data collected continuously by our network of permanent noise monitoring stations located at Cardiff, Narara, Koolewong, Leura, Emu Plains, Otford and Jannali;
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Results of short term noise monitoring undertaken across the network to identify rail noise hotspots and in response to complaints; and,
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Data such as treatment areas associated with our Freight Noise Attenuation Program.
This system enables us to communicate the magnitude of the noise impacts and to track the progress we are making on reducing these noise impacts. This paper outlines how we use this system as a tool to facilitate more effective, efficient and evidence based decision-making.
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Night time is defined from 10 pm to 7 am.
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Basutu, L., Sharpe, K. (2018). Supporting Decision Making and Management of Freight Rail Noise Using GIS. In: Anderson, D., et al. Noise and Vibration Mitigation for Rail Transportation Systems. Notes on Numerical Fluid Mechanics and Multidisciplinary Design, vol 139. Springer, Cham. https://doi.org/10.1007/978-3-319-73411-8_7
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DOI: https://doi.org/10.1007/978-3-319-73411-8_7
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