Modélisation de signaux temporels hautes fréquences multicapteurs à valeurs manquantes : Application à la prédiction des efflorescences phytoplanctoniques dans les rivières et les écosystèmes marins côtiers

Abstract : Because of the growing interest for environmental issues and to identify direct and indirect effects of anthropogenic activities on ecosystems, environmental monitoring programs have recourse more and more frequently to high resolution, autonomous and multi-sensor instrumented stations. These systems are implemented in harsh environment and there is a need to stop measurements for calibration, service purposes or just because of sensors failure. Consequently, data could be noisy, missing or out of range and required some pre-processing or filtering steps to complete and validate raw data before any further investigations. In this context, the objective of this work is to design an automatic numeric system able to manage such amount of data in order to further knowledge on water quality and more precisely with consideration about phytoplankton determinism and dynamics. Main phase is the methodological development of phytoplankton bloom forecasting models giving the opportunity to end-user to handle well-adapted protocols. We propose to use hybrid Hidden Markov Model to detect and forecast environment states (identification of the main phytoplankton bloom steps and associated hydrological conditions). The added-value of our approach is to hybrid our model with a spectral clustering algorithm. Thus all HMM parameters (states, characterisation and dynamics of these states) are built by unsupervised learning. This approach was applied on three data bases: first one from the marine instrumented station MAREL Carnot (Ifremer) (2005-2009), second one from a Ferry Box system implemented in the eastern English Channel en 2012 and third one from a freshwater fixed station in the river Deûle in 2009 (Artois Picardie Water Agency). These works fall within the scope of a collaboration between IFREMER, LISIC/ULCO and Artois Picardie Water Agency in order to develop optimised systems to study effects of anthropogenic activities on aquatic systems functioning in a regional context of massive blooms of the harmful algae, Phaeocystis globosa.
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Submitted on : Tuesday, May 24, 2016 - 11:53:07 AM
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Kévin Rousseeuw. Modélisation de signaux temporels hautes fréquences multicapteurs à valeurs manquantes : Application à la prédiction des efflorescences phytoplanctoniques dans les rivières et les écosystèmes marins côtiers. Traitement du signal et de l'image [eess.SP]. Université du Littoral Côte d'Opale, 2014. Français. ⟨NNT : 2014DUNK0374⟩. ⟨tel-01320681⟩

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