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Web data for computing real-world noise from civil aviation.
- Source :
-
Transportation Research Part D: Transport & Environment . Apr2019, Vol. 69, p224-249. 26p. - Publication Year :
- 2019
-
Abstract
- Highlights • Web data on civil air traffic are coupled with the ECAC model to compute airport noise. • Data for nine airports in the EU are collected, for a total of 10,752 flights. • Historical data at Heathrow, Schiphol, and Schwechat are used to validate the approach. • The proposed methodology is applicable to any airport worldwide. Abstract A large amount of data on civil air traffic is now available on the web, thanks to the recent development of flight tracker websites. This paper presents a novel methodology to exploit these data for computing real-world noise around airports. The proposed approach consists of data collection and pre-processing, flight path reconstruction, aircraft noise computation using a best-practice model (ECAC Doc.29), and rendering of ground track and noise contour maps in airport areas. Applications are shown for nine European airports, where the daily air traffic reconstructed from 10,752 collected flights compares well with official records from EUROCONTROL. Among these airports, London Heathrow, Amsterdam Schiphol and Vienna-Schwechat have been considered for the validation of the present methodology, and a good agreement is found between predicted ground noise levels and available historical data, with the largest deviations being detected in the portions of the airport areas most affected by departure events. The present work constitutes the first step to harnessing the potential of web data in aviation, unlocking unprecedented possibilities for assessing the environmental impact of civil aviation and providing policy-makers with a powerful tool for developing guidelines and regulations aimed at mitigating the detrimental effects of air traffic in densely inhabited regions. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 13619209
- Volume :
- 69
- Database :
- Academic Search Index
- Journal :
- Transportation Research Part D: Transport & Environment
- Publication Type :
- Academic Journal
- Accession number :
- 135746908
- Full Text :
- https://doi.org/10.1016/j.trd.2019.01.022