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  • 标题:A Harmonized Data Model for Noise Simulation in the EU
  • 本地全文:下载
  • 作者:Kavisha Kumar ; Hugo Ledoux ; Richard Schmidt
  • 期刊名称:ISPRS International Journal of Geo-Information
  • 电子版ISSN:2220-9964
  • 出版年度:2020
  • 卷号:9
  • 期号:2
  • 页码:121
  • DOI:10.3390/ijgi9020121
  • 语种:English
  • 出版社:MDPI AG
  • 摘要:This paper presents our implementation of a harmonized data model for noise simulations in the European Union (EU). Different noise assessment methods are used by different EU member states (MS) for estimating noise at local, regional, and national scales. These methods, along with the input data extracted from the national registers and databases, as well as other open and/or commercially available data, differ in several aspects and it is difficult to obtain comparable results across the EU. To address this issue, a common framework for noise assessment methods (CNOSSOS-EU) was developed by the European Commission’s (EC) Joint Research Centre (JRC). However, apart from the software implementations for CNOSSOS, very little has been done for the practical guidelines outlining the specifications for the required input data, metadata, and the schema design to test the real-world situations with CNOSSOS. We describe our approach for modeling input and output data for noise simulations and also generate a real world dataset of an area in the Netherlands based on our data model for simulating urban noise using CNOSSOS.
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