Chevallier, R.Shapiro, M.Engberg, Z.Soler Arnedo, Manuel FernandoDelahaye, D.2024-01-222024-01-222023-07-01Chevallier, R.; Shapiro, M.; Engberg, Z.; Soler, M.; Delahaye, D. Linear Contrails Detection, Tracking and Matching with Aircraft Using Geostationary Satellite and Air Traffic Data. Aerospace 2023, 10, 578 (36 p.). https://doi.org/10.3390/aerospace100705782226-4310https://hdl.handle.net/10016/39421Climate impact models of the non- (Formula presented.) emissions of aviation are still subject to significant uncertainties. Condensation trails, or contrails, are one of these non- (Formula presented.) effects. In order to validate the contrail simulation models, a dataset of observations covering the entire lifetime of the contrails will be required, as well as the characteristics of the aircraft which produced them. This study carries on the work on contrail observation from geostationary satellite by proposing a new way to track contrails and identify the flight that produced it using geostationary satellite infrared images, weather data as well as air traffic data. It solves the tracking and the identification problem as one, each process leveraging information from the other to achieve a better overall result. This study is a new step towards a consistent contrail dataset that could be used to validate contrail models.27eng© 2023 by the authors. Licensee MDPI, Basel, Switzerland.This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.Atribución-NoComercial-SinDerivadas 3.0 EspañaCondensation TrailsContrail TrackingImage SegmentationInstance SegmentationMatching Contrails With AircraftNon-Co2 Climate Impact Of AviationSatellite Imageryresearch articleAeronáuticaFísicaIngeniería Mecánicahttps://doi.org/10.3390/aerospace10070578open access17, 57827Aerospace10AR/0000033697