La télédétection spatiale de la couleur de l’océan implique l’élimination de la contribution atmosphérique, appelée correction atmosphérique (CA). Au-dessus des eaux claires, cette dernière se base sur l’hypothèse que l’eau est totalement absorbante dans le Proche Infra-Rouge (PIR) pour estimer la réflectance atmosphérique et déterminer la réflectance marine. À l’opposé, au-dessus des eaux côtières turbides, la contribution du signal marin n’est pas négligeable dans le PIR. De ce fait, différentes méthodes alternatives ont été proposées. La thèse se consacre à l’évaluation des algorithmes de CA proposés et leur amélioration pour le capteur Ocean and Land Colour Instrument (OLCI) au-dessus des eaux côtières en exploitant sa synergie avec le capteur Sea and Land Surface Temperature Radiometer (SLSTR). Dans ce but, des mesures radiométriques in-situ ont été acquises dans deux zones côtières françaises contrastées : Manche orientale et Guyane Française, avec le spectro-radiomètre ASD, suivant un nouveau protocole d’acquisition et de post-traitement. Le post-traitement s’est basé sur le coefficient de variabilité et la différence relative de la médiane dans le contrôle de qualité, en plus du score d’assurance de qualité (QAS). Suivant l’analyse statistique basée en partie sur l’angle spectral moyenné (SAM), l’inter-comparaison radiométrique de l’ASD avec les autres radiomètres (TriOS-above et Radeau), a révélé la cohérence des mesures ASD. L’utilisation de ces dernières a permis l’inter-comparaison de la performance de cinq algorithmes de CA, où l’algorithme Polymer est le plus performant d’après un système à points avec une seule métrique. Cependant aucun algorithme a atteint le maximum de points soulignant la grande marge de progression à accomplir, surtout en eau côtière. Dans cette optique, trois relations spectrales de la réflectance des aérosols ont été testées sur une base de données simulées suivant la synergie OLCI/SLSTR. Une autre relation, Full Spectrum AC (FSAC) a été développée initialement en combinant deux relations existantes, après l’élimination de l’hypothèse du pixel noir dans l’ultra-violet (UV) et l’intégration d’un schéma itératif. L’inter-comparaison des relations révèle la cohérence de FSAC qui est légèrement moins performante qu’une relation publiée. L’application de FSAC sur des images OLCI/SLSTR ouvrirait des perspectives dans l’amélioration de la CA au-dessus des eaux côtières. / The ocean color remote sensing involves the removal of the atmospheric contribution, the so-called atmospheric correction (AC). Over clear waters, the latter is based on the hypothesis that the sea water is totally absorbent in the Near Infra-Red (NIR), to estimate the atmospheric reflectance and to determine the water reflectance. By contrast, over coastal turbid waters, the marine signal is not negligible in the NIR. Accordingly, different alternative methods were proposed. The thesis is committed to evaluate the proposed AC algorithms and their improvement for the Ocean and Land Colour Instrument (OLCI) sensor over coastal waters exploiting its synergy with the Sea and Land Surface Temperature Radiometer (SLSTR) sensor. For this purpose, radiometric in-situ measurements were acquired in two contrasted French coastal areas : Eastern English Channel and FrenchGuiana, with the ASD spectro-radiometer, according to a newly developed measurement and post-processing protocol. The post-processing was based on the coefficient of variability and the median relative difference, in addition to the Quality Assurance Score (QAS). Following the statistical analysis in part based on the Spectral Angle Mean (SAM), the radiometric inter-comparison of the ASD and other radiometers (TriOS-above and TriOS in-water), shows the consistency of the ASD measurements. The use of these measurement leads to carry out the performance inter-comparison of five AC algorithms, where the Polymer algorithm is the most efficient according to a unique metric scoring system. However, neither algorithm obtained the maximum score, highlighting the big room for improvement, especially for coastal waters. With this in mind; three spectral relationships of aerosols reflectance were tested with a simulated data set based on OLCI/SLSTR synergy. Another relationship, Full Spectrum AC (FSAC) was initially developed combining two existing relationships, after excluding the black pixel hypothesis in the Ultra-Violet and integrating a iterative scheme. The relationships inter-comparison shows consistency ofFSAC which is slightly less performing than one published relationship. The application of FSAC on OLCI/SLSTR images could have perspectives to improve the AC over coastal waters.

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The goal of this research was to improve ocean colour chlorophyll a (Chla) retrievals in the coastal Case 2 waters of the Salish Sea by characterizing the main drivers of optical variability and using this information to parameterize empirical algorithms based on an optical classification. This was addressed with three specific objectives: (1) build a comprehensive spatio-temporal data set of in situ optical and biogeochemical parameters, (2) apply a hierarchical clustering analysis to classify above-water remote sensing reflectance (Rrs) and associated bio-optical regimes, (3) optimize and validate class-specific empirical algorithms for improved Chla retrievals. Biogeochemical and optical measurements, acquired at 145 sites, showed considerable variation; Chla (mean=1.64, range: 0.10 – 7.20 µg l-1), total suspended matter (TSM) (3.09, 0.82 – 20.69 mg l-1), and absorption by chromophoric dissolved organic matter (a_cdom (443)) (0.525, 0.007 – 3.072 m-1), thus representing the spatial and temporal variability of the Salish Sea. A comparable range was found in the measured optical properties; particulate scattering (b_p (650)) (1.316, 0.250 – 7.450 m-1), particulate backscattering (b_bp (650)) (0.022, 0.005 – 0.097 m-1), total beam attenuation coefficient (c_t (650)) (1.675, 0.371 – 9.537 m-1), and particulate absorption coefficient (a_p (650)) (0.345, 0.048 – 2.020 m-1). Empirical orthogonal function (EOF) analysis revealed 95% of the Rrs variance was highly correlated to b_p (r = 0.90), b_bp (r = 0.82), and TSM concentration (r = 0.80), suggesting a strong influence from riverine systems in this region. Hierarchical clustering on the normalized Rrs revealed four spectral classes. Class 1 is defined by high overall Rrs magnitudes in the red, indicating more turbid waters, Class 2 showed high Rrs values in the red and well defined fluorescence and absorption features, indicated by a high Chla and TSM presence, Class 3 showed low TSM influence and more defined Chla signatures, and Class 4 is characterized by overall low Rrs values, suggesting more optically clear oceanic waters. Spectral similarities justified a simplification of this classification into two dominant water classes – (1) estuarine class (Classes 1 and 2) and (2) oceanic class (Classes 3 and 4) – representing the dominant influences seen here. In situ Chla and above-water remote sensing reflectance measurements, used to validate and parameterize the OC3M/OC3S3, two-band ratio, FLH and, modified FLH (ModFLH) empirical algorithms, showed a systematic overestimation of low Chla concentrations and underestimation of higher Chla values for all four algorithms when tuned to regional data. FLH and ModFLH algorithms performed best for these data (R2 ~ 0.40; RMSE ~ 0.32). Algorithm accuracy was significantly improved for the class-specific parametrizations with the two-band ratio showing a strong correlation to the Chla concentrations in the estuarine class (R2 ~ 0.71; RMSE ~ 0.33) and the ModFLH algorithm in the oceanic class (R2 ~ 0.70; RMSE ~ 0.26). These results demonstrated the benefit of applying an optical classification as a necessary first step into improving Chla retrievals from remotely sensed data in the contrasted coastal waters of the Salish Sea. With accurate Chla information, the health of the Salish Sea can be viably monitored at spatial and temporal scales suitable for ecosystem management. / Graduate / 0416 / stephen.uvic@gmail.com