Utilisation des données de couleur de l'océan pour estimer les propriétés optiques des eaux côtières (caractérisation du signal marin dans le proche infrarouge pour les eaux turbides, développement d'algorithmes semi-analytiques, validation avec des données satellitaires)

Cette thèse est consacrée à l amélioration de l interprétation des données satellitaires de couleur de l océan dans les eaux côtières, et s intéresse à trois aspects fondamentaux et appliqués: 1) les variations du signal marin dans le proche infrarouge, qui permettent d effectuer les corrections atmosphériques au-dessus des eaux turbides ; 2) l inversion de la donnée de couleur de l océan pour retrouver des quantités physiques ou biogéochimiques, avec le développement d algorithmes semi-analytiques valides pour les eaux côtières ; 3) l élaboration et la validation d un algorithme utilisant les données satellitaires de couleur de l océan actuellement mesurées et permettant d estimer la transparence de l océan, qui est un indicateur pertinent pour le suivi environnemental. A chaque étape, des données bio-optiques mesurées in situ, des données de transparence de l océan, des simulations de transfert radiatif ou des données satellitaires permettent de tester la robustesse, la sensibilité et la validité des algorithmes. Ces travaux ouvrent des perspectives d utilisation plus complète des données de couleur de l océan pour les zones côtières.For human societies, the coastal ocean is very important for economical (harvest of the sea resources), ecological (water quality) and social (pressure of urbanization) reasons. Spaceborne ocean color sensors, owing to their spatial and temporal coverage, should provide powerful tools for monitoring of coastal zones. The present thesis is dedicated to the interpretation of remotely sensed ocean color data captured above coastal waters. Three different aspects, theoretical and applied, are studied: 1) the variations of the marine signal in the near infrared, which is crucial to perform atmospheric corrections above turbid waters, 2) the inversion of ocean color data to retrieve physical and biogeochemical properties, with the development of algorithms validated in coastal waters, 3) the elaboration and validation of an algorithm allowing the estimation of water transparency from space, the water transparency being an indicator of water quality. The general approach is to focus on the current knowledge of the optical properties of the substances, and to extract as analytically as possible the information encapsulated in the data, according to the published relationships between those properties and the radiometric data. At each step, measurements such as bio-optical data gathered in situ in various environments, water transparency data, radiative transfer simulations, or remotely sensed data allowed to test systematically the robustness and validity of the algorithms. This work paves the way to further use remotely sensed ocean color data above coastal waters, through development of semi-analytical algorithms.PARIS-BIUSJ-Thèses (751052125) / SudocPARIS-BIUSJ-Sci.Terre recherche (751052114) / SudocSudocFranceF

Spectral variations in the near-infrared ocean reflectance

The optical properties of natural waters beyond the visible range, in the near-infrared (NIR, 700-900 nm), have received little attention because they are often assumed to be mostly determined by the large absorption coefficient of pure water, and because of methodological difficulties. It is now growingly admitted that the NIR represents a potential optical source of unambiguous information about suspended sediments in turbid waters, thence the need for better understanding the NIR optical behaviour of such waters. It has recently been proposed (Ruddick et al., Limnology and Oceanography. 51, 1167-1179, 2006) that the variability in the shape of the surface ocean reflectance spectrum in the NIR is negligible in turbid waters. In the present study, we show, based on both in situ and remote sensing data, that the shape of the ocean reflectance spectrum in the NIR does vary in turbid to extremely turbid waters. Space-borne ocean reflectance data were collected using 3 different sensors (SeaWiFS, MODIS/Aqua and MERIS) over the Amazon, Mackenzie and Rio de la Plata turbid river plumes during extremely clear atmospheric conditions so that reliable removal of gas and aerosol effects on reflectance could be achieved. In situ NIR reflectance data were collected in different European estuaries where extremely turbid waters were found. In both data sets, a flattening of the NIR reflectance spectrum with increasing turbidity was observed. The ratio of reflectances at 765 nm and 865 nm, for instance, varied from ca. 2 down to 1 in our in situ data set, while a constant value of 1.61 had been proposed based on theory in a previous study. Radiative transfer calculations were performed using a range of realistic values for the seawater inherent optical properties, to determine the possible causes of variations in the shape of the NIR reflectance spectrum. Based on these simulations, we found that the most significant one was the gradual increase in the contribution of suspended sediments to the color of surface waters, which often leads to the flattening of the reflectance spectrum. Changes in the scattering and absorption properties of particles also contributed to variations in the shape of the NIR surface ocean reflectance spectrum. The impact of such variations on the interpretation of ocean color data is discussed. (C) 2011 Elsevier Inc. All rights reserved

Estimation of light penetration, and horizontal and vertical visibility in oceanic and coastal waters from surface reflectance

International audience[1] We present algorithms for the estimation of the vertical diffuse attenuation coefficient, K-d (m(-1)), and the beam attenuation coefficient, c (m(-1)), at 490 nm from irradiance reflectance. Our aim is to retrieve as analytically as possible [K-d(490) + c(490)](-1), a proxy for vertical visibility. The two algorithms are based on the semianalytical retrieval of the absorption coefficient a (m(-1)) and the backscattering coefficient b(b) (m(-1)) from reflectance at two wavelengths, 490 and 709 nm. The use of a near-infrared wave band allows a small number of simple assumptions to be made, (1) light absorption at 709 nm is only due to pure seawater, and (2) there exists a constant ratio between the particulate backscattering coefficients at 490 and 709 nm. To estimate c(490), we developed an empirical relationship between b and b(b) for particles. Algorithm development, testing, and validation are achieved using data from the literature, a synthetic data set, and a large in situ data set of inherent and apparent optical properties measured in various environments. The algorithms are found to be valid both in coastal and oceanic waters, and largely insensitive to regional peculiarities in the inherent optical properties. The values of K-d( 490) and c( 490) are retrieved within a factor of 2.21 and 2.91 (95% confidence interval), respectively, using independent in situ data sets. This performance for K-d( 490) is better or comparable to that of recently published algorithms. This study opens the way to the development of simple semianalytical ocean color algorithms that make the best use of spectral information

Ocean transparency from space: Validation of algorithms using MERIS, MODIS and SeaWiFS data

Ocean transparency, often measured using Secchi disk, is a useful index of water quality or productivity and is used in many environmental studies. The spaceborne ocean color sensors provide synoptic and regular radiometric data and can be used for applying environmental policies if the data is converted into relevant biogeochemical properties. We adapted and developed semi-analytical and empirical algorithms to estimate the Secchi depth from satellite ocean color data in both coastal and oceanic waters. The development of the algorithms is based on the use of a comprehensive in situ bio-optical dataset The algorithms are validated using an extensive set of coincident satellite estimates and in situ measurements of the Secchi depth (so-called matchups). More than 400 matchups are compiled for the MERIS, MODIS and SeaWiFS sensors. The comparison between Secchi depth retrievals from remote sensing data and in situ measurements yields determination coefficients (R-2) between 0.50 and 0.73, depending on the sensor and algorithm. The type II linear regression slopes and intercepts vary between 0.95 and 1.46, and between -0.8 and 6.2 in, respectively. While semi-analytical algorithms provide the most promising results on in situ data, the empirical one proves to be more robust on remote sensing data because it is less sensitive to error due to erroneous atmospheric corrections. Using ocean color archives, one can derive maps of ocean transparency for different areas. Our climatology of the Secchi depth based on ocean color for the transition zone between the North Sea and Baltic Sea is compared to an historical dataset (C) 2011 Elsevier Inc. All rights reserved

Unannounced Meal Detection for Artificial Pancreas Systems Using Extended Isolation Forest

International audienceThis study aims at developing an unannounced meal detection method for artificial pancreas, based on a recent extension of Isolation Forest. The proposed method makes use of features accounting for individual Continuous Glucose Monitoring (CGM) profiles and benefits from a two-threshold decision rule detection. The advantage of using Extended Isolation Forest (EIF) instead of the standard one is supported by experiments on data from virtual diabetic patients, showing good detection accuracy with acceptable detection delays

Customization of home closed-loop insulin delivery in adult patients with type 1 diabetes, assisted with structured remote monitoring: the pilot WP7 Diabeloop study

International audienc

Patients with highly unstable type 1 diabetes eligible for islet transplantation can be managed with a closed‐loop insulin delivery system: A series of N‐of‐1 randomized controlled trials

International audienceAim To compare the efficacy of the closed‐loop Diabeloop for highly unstable diabetes (DBLHU) system with the open‐loop predictive low glucose suspend (PLGS) system in patients with highly unstable type 1 diabetes (T1D) who experience acute metabolic events. Methods DBLHU‐WP10 was an interventional, controlled, randomized, open‐label study that comprised two cycles of N‐of‐1 trials (2‐of‐1 trials). Each trial consisted of two crossover 4‐week periods of treatment with either DBLHU or PLGS in randomized order. The primary outcome was the percentage of time spent in the 70‐180 mg/dL glucose range (time in range [TIR]). Results Five out of seven randomized patients completed the aggregated 2‐of‐1 trials. TIR was significantly higher with DBLHU (73.3% ± 1.7%) compared with PLGS (43.5% ± 1.7%; P < .0001). The percentage of time below 70 mg/dL was significantly lower with DBLHU (0.9% ± 0.4%) versus PLGS (3.7% ± 0.4%; P < .0001). DBLHU was also significantly superior to PLGS in reducing hyperglycaemic excursions and improving almost all other secondary outcomes, including glucose variability and satisfaction score. No adverse event could be related to the experimental treatment. Conclusions DBLHU was superior to PLGS in improving the metabolic control of patients with highly unstable T1D who require an islet or pancreas transplant but who either have a contraindication or refuse to consent

Prospective analysis of satisfaction and usability of closed-loop Diabeloop DBLHU treatment in patients with highly unstable type 1 diabetes

International audienc