Modelling urban noise in CityGML ADE

Case of the Netherlands

Conference Paper (2017)
Author(s)

Kavisha Kumar (TU Delft - Urban Data Science)

H. Ledoux (TU Delft - Urban Data Science)

Tom Commandeur (TU Delft - Urban Data Science)

J.E. Stoter (TU Delft - Urban Data Science)

Research Group
Urban Data Science
Copyright
© 2017 Kavisha Kumar, H. Ledoux, T.J.F. Commandeur, J.E. Stoter
DOI related publication
https://doi.org/10.5194/isprs-annals-IV-4-W5-73-2017
More Info
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Publication Year
2017
Language
English
Copyright
© 2017 Kavisha Kumar, H. Ledoux, T.J.F. Commandeur, J.E. Stoter
Research Group
Urban Data Science
Pages (from-to)
73-81
Reuse Rights

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Abstract

Road traffic and industrial noise has become a major source of discomfort and annoyance among the residents in urban areas. More than 44 % of the EU population is regularly exposed to road traffic noise levels over 55 dB, which is currently the maximum accepted value prescribed by the Environmental Noise Directive for road traffic noise. With continuously increasing population and number of motor vehicles and industries, it is very unlikely to hope for noise levels to diminish in the near future. Therefore, it is necessary to monitor urban noise, so as to make mitigation plans and to deal with its adverse effects. The 2002/49/EC Environmental Noise Directive aims to determine the exposure of an individual to environmental noise through noise mapping. One of the most important steps in noise mapping is the creation of input data for simulation. At present, it is done semi-automatically (and sometimes even manually) by different companies in different ways and is very time consuming and can lead to errors in the data. In this paper, we present our approach for automatically creating input data for noise simulations. Secondly, we focus on using 3D city models for presenting the results of simulation for the noise arising from road traffic and industrial activities in urban areas. We implemented a few noise modelling standards for industrial and road traffic noise in CityGML by extending the existing Noise ADE with new objects and attributes. This research is a steping stone in the direction of standardising the input and output data for noise studies and for reconstructing the 3D data accordingly.