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Validating Aircraft Noise Models
Proceeding Paper

Detecting and Correlating Aircraft Noise Events below Ambient Noise Levels Using OpenSky Tracking Data †

Group Waves, Information Technology, Ghent University, B-9000 Ghent, Belgium
Presented at the 8th OpenSky Symposium 2020, Online, 12–13 November 2020.
Proceedings 2020, 59(1), 13; https://doi.org/10.3390/proceedings2020059013
Published: 3 December 2020
(This article belongs to the Proceedings of 8th OpenSky Symposium 2020)
Noise annoyance due to aircraft operations extends well beyond the 55 Lden noise contours as calculated according to the Environmental Noise Directive (END). Noise mapping beyond these contours will improve the understanding of the perception, annoyance and health impact of aircraft operations. OpenSky data can provide the spatial data to create an aircraft noise exposure map for lower exposure levels. This work presents the first step of region-wide noise exposure methodology based on open source data: detecting low LAmax aircraft events in ambient noise using spectral noise measurements and correlating the detected noise events to the matching flights retrieved from the OpenSky database. In ISO 20906:2009, the specifications of noise monitoring near airports is standardized, using LAeq,1sec values for event detection. This limits the detection potential due to masking by other noise sources in areas with low maximum levels of aircraft noise and in areas with medium maximum levels of high ambient exposure areas. The typical lower detection limit in airport-based monitoring systems ranges from 55 to 60 LAeq,max, depending on the ambient levels. Using a detection algorithm sensitive to third-octave band levels, aircrafts can be detected down to 40 LAmax in ambient noise levels of a similar magnitude. The measurement approach is opportunistic: aircraft events are detected in available environmental noise data series registered for other applications (e.g., road noise, industrial noise, etc.). Most of the measurement locations are not identified as high-exposure areas for aircraft noise. Detection settings can vary to match ambient noise levels to improve the correlation success.
Keywords: ADS-B messages; aircraft noise; event detection; source attribution ADS-B messages; aircraft noise; event detection; source attribution
MDPI and ACS Style

Dekoninck, L. Detecting and Correlating Aircraft Noise Events below Ambient Noise Levels Using OpenSky Tracking Data. Proceedings 2020, 59, 13. https://doi.org/10.3390/proceedings2020059013

AMA Style

Dekoninck L. Detecting and Correlating Aircraft Noise Events below Ambient Noise Levels Using OpenSky Tracking Data. Proceedings. 2020; 59(1):13. https://doi.org/10.3390/proceedings2020059013

Chicago/Turabian Style

Dekoninck, Luc. 2020. "Detecting and Correlating Aircraft Noise Events below Ambient Noise Levels Using OpenSky Tracking Data" Proceedings 59, no. 1: 13. https://doi.org/10.3390/proceedings2020059013

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