The Southern Ocean (ca. 20% of the world ocean surface) is a key place for the regulation of Earth climate thanks to its capacity to absorb atmospheric carbon dioxide (CO2) by physico-chemical and biological mechanisms. The biological carbon pump is a major pathway of absorption of CO2 through which the CO2 incorporated into autotrophic microorganisms in surface waters is transferred to deep waters. This process is influenced by the extent of the primary production and by the intensity of the remineralization of organic matter along the water column. So, the annual cycle of sea ice, through its in situ production and remineralization processes but also, through the release of microorganisms, organic and inorganic nutrients (in particular iron)into the ocean has an impact on the carbon cycle of the Southern Ocean, notably by promoting the initiation of phytoplanktonic blooms at time of ice melting. The present work focussed on the distribution of organic matter (OM) and its interactions with the microbial network (algae, bacteria and protozoa) in sea ice and ocean, with a special attention to the factors which regulate the biological carbon pump of the Southern Ocean. This thesis gathers data collected from a) late winter to summer in the Western Pacific sector, Western Weddell Sea and Bellingshausen Sea during three sea ice cruises ARISE, ISPOL-drifting station and SIMBA-drifting station and b) summer in the Sub-Antarctic and Polar Front Zone during the oceanographic cruise SAZ-Sense. The sea ice covers were typical of first-year pack ice with thickness ranging between 0.3 and 1.2 m, and composed of granular and columnar ice. Sea ice temperature ranging between -8.9°C and -0.4°C, brines volume ranging between 2.9 to 28.2% and brines salinity from 10 to >100 were observed. These extreme physicochemical factors experienced by the microorganisms trapped into the semi-solid sea ice matrix therefore constitute an extreme change as compared to the open ocean. Sea ice algae were mainly composed of diatoms but autotrophic flagellates (such as dinoflagellates or Phaeocystis sp.) were also typically found in surface ice layers. Maximal algal biomass was usually observed in the bottom ice layers except during SIMBA where the maxima was localised in the top ice layers likely because of the snow and ice thickness which limit the light available in the ice cover. During early spring, the algal growth was controlled by the space availability (i.e. brine volume) while in spring/summer (ISPOL, SIMBA) the major nutrients availability inside sea ice may have controlled algal growth. At all seasons, high concentrations of dissolved and particulate organic matter were measured in sea ice as compared to the water column. Dissolved monomers (saccharides and amino acids) were accumulated in sea ice, in particular in winter. During spring and summer, polysaccharides constitute the main fraction of the dissolved saccharides pool. High concentrations of transparent exopolymeric particles (TEP), mainly constituted with saccharides, were present and their gel properties greatly influence the internal habitat of sea ice, by retaining the nutrients and by preventing the protozoa grazing pressure, inducing therefore an algal accumulation. The composition as well as the vertical distribution of OM in sea ice was linked to sea ice algae. Besides, the distribution of microorganisms and organic compounds in the sea ice was also greatly influenced by the thermodynamics of the sea ice cover, as evidenced during a melting period for ISPOL and during a floodfreeze cycle for SIMBA. The bacteria distribution in the sea ice was not correlated with those of algae and organic matter. Indeed, the utilization of the accumulated organic matter by bacteria seemed to be limited by an external factor such as temperature, salinity or toxins rather than by the nature of the organic substrates, which are partly composed of labile monomeric saccharides. Thus the disconnection of the microbial loop leading to the OM accumulation was highlighted in sea ice. In addition the biofilm formed by TEP was also involved in the retention of cells and other compounds(DOM, POM, and inorganic nutrients such as phosphate and iron) to the brine channels walls and thus in the timing of release of ice constituents when ice melts. The sequence of release in marginal ice zone, as studied in a microcosm experiments realized in controlled and trace-metal clean conditions, was likely favourable to the development of blooms in the marginal ice zone. Moreover microorganisms derived from sea ice (mainly <10 µm) seems able to thrive and grow in the water column as also the supply of organic nutrients and Fe seems to benefit to the pelagic microbial community. Finally, the influence of the remineralization of organic matter by heterotrophic bacterioplankton on carbon export and biological carbon pump efficiency was investigated in the epipelagic (0-100 m) and mesopelagic(100-700 m) zones during the summer in the sub-Antarctic and Polar Front zones (SAZ and PFZ) of the Australian sector (Southern Ocean). Opposite to sea ice, bacterial biomass and activities followed Chl a and organic matter distributions. Bacterial abundance, biomass and activities drastically decreased below depths of 100-200 m. Nevertheless, depth-integrated rates through the thickness of the different water masses showed that the mesopelagic contribution of bacteria represents a non-negligible fraction, in particular in a diatom-dominated system./ L’océan Antarctique (± 20% de la surface totale des océans) est un endroit essentiel pour la régulation du climat de notre planète grâce à sa capacité d’absorber le dioxyde de carbone (CO2) atmosphérique par des mécanismes physico-chimique et biologique. La pompe biologique à carbone est un processus majeur de fixation de CO2 par les organismes autotrophes à la surface de l’océan et de transfert de carbone organique vers le fond de l’océan. Ce processus est influencé par l’importance de la production primaire ainsi que par l’intensité de la reminéralisation de la matière organique dans la colonne d’eau. Ainsi, le cycle annuel de la glace via sa production/reminéralisation in situ mais aussi via l’ensemencement de l’océan avec des microorganismes et des nutriments organiques et inorganiques (en particulier le fer) a un impact sur le cycle du carbone dans l’Océan Antarctique, notamment en favorisant l’initiation d’efflorescences phytoplanctoniques dans la zone marginale de glace. Plus précisément, nous avons étudié les interactions entre le réseau microbien (algues, bactéries et protozoaires) et la matière organique dans le but d’évaluer leurs impacts potentiels sur la pompe biologique de carbone dans l’Océan Austral. Deux écosystèmes différents ont été étudiés : la glace de mer et le milieu océanique grâce à des échantillons prélevés lors des campagnes de glace ARISE, ISPOL et SIMBA et lors de la campagne océanographique SAZ-Sense, couvrant une période allant de la fin de l’hiver à l’été. La glace de mer est un environnement très particulier dans lequel les microorganismes planctoniques se trouvent piégés lors de la formation de la banquise et dans lesquels ils subissent des conditions extrêmes de température et de salinité, notamment. Les banquises en océan ouvert étudiées (0,3 à 1,2 m d’épaisseur, températures de -8.9°C à -0.4°C, volumes relatifs de saumure de 2.9 à 28.2% et salinités de saumures entre 10 et jusque >100) étaient composées de glace columnaire et granulaire. Les algues de glace étaient principalement des diatomées mais des flagellés autotrophes (tels que des dinoflagellés ou Phaeocystis sp.) ont été typiquement observés dans les couches de glace de surface. Les biomasses algales maximales se trouvaient généralement dans la couche de glace de fond sauf à SIMBA où les maxima se trouvaient en surface, probablement en raison de l’épaisseur des couches de neige et de glace, limitant la lumière disponible dans la colonne de glace. Au début du printemps, la croissance algale était contrôlée par l’espace disponible (càd le volume des saumures) tandis qu’au printemps/été, la disponibilité en nutriments majeurs a pu la contrôler. A toutes les saisons, des concentrations élevées en matière organique (MO) dissoute et particulaire on été mesurées dans la glace de mer par rapport à l’océan. Des monomères dissous (sucres et acides aminés) étaient accumulés dans la glace, surtout en hiver. Au printemps et été, les polysaccharides dissous dominaient le réservoir de sucres. La MO était présente sous forme de TEP qui par leurs propriétés de gel modifie l’habitat interne de la glace. Ce biofilm retient les nutriments et gêne le mouvement des microorganismes. La composition et la distribution de la MO dans la glace étaient en partie reliées aux algues de glace. De plus, la thermodynamique de la couverture de glace peut contrôler la distribution des microorganismes et de la MO, comme observé lors de la fonte de la glace à ISPOL et lors du refroidissement de la banquise à SIMBA. La distribution des bactéries n’est pas corrélée avec celle des algues et de la MO dans la glace. En effet, la consommation de la MO par les bactéries semble être limitée non pas par la nature chimique des substrats mais par un facteur extérieur affectant le métabolisme bactérien tel que la température, la salinité ou une toxine. Le dysfonctionnement de la boucle microbienne menant à l’accumulation de la MO dans la glace a donc été mis en évidence dans nos échantillons. De plus, le biofilm formé par les TEP est aussi impliquée dans l’attachement des cellules et autres composés aux parois des canaux de saumure et donc dans la séquence de largage lors de la fonte. Cette séquence semble propice au développement d’efflorescences phytoplanctoniques dans la zone marginale de glace. Les microorganismes originaires de la glace (surtout ceux de taille < 10 μm) semblent capables de croître dans la colonne d’eau et l’apport en nutriments organiques et inorganiques apparaît favorable à la croissance des microorganismes pélagiques. Enfin, l’influence des activités hétérotrophes sur l’export de carbone et l’efficacité de la pompe biologique à carbone a été évaluée dans la couche de surface (0-100 m) et mésopélagique (100-700 m) de l’océan. Au contraire de la glace, les biomasses et activités bactériennes suivaient les distributions de la chlorophyll a et de la MO. Elles diminuent fortement en dessous de 100-200 m, néanmoins les valeurs intégrées sur la hauteur de la colonne d’eau indiquent que la reminéralisation de la MO par les bactéries dans la zone mésopélagique est loin d’être négligeable, spécialement dans une région dominée par les diatomées.

Observations of Antarctic sea ice thickness are sporadic in space and time, hindering knowledge of its variability. A proxy based on stage of development data from the National Ice Center (NIC) weekly operational charts is used to create a high-resolution time series of sea ice concentration, thickness and volume for 2000-2009. Record-length mean thickness and volume of Antarctic sea ice are 66.7 cm and 7.7 x10^3 km^3. The mean growth and decay seasons in the Southern Ocean and in the Ross sector are 210 days and 155 days, but at least at least one week shorter (growth) and longer (decay) in the Amundsen/Bellingshausen sector. Over 90% of the Antarctic continental shelf is covered with sea ice for 3-5 months, and for 2 to 4 months longer periods in the Amundsen/Bellingshausen and Ross sectors. Yearly mean sea ice area (extent) in the Southern Ocean increased at a rate of 0.71 x 10^6 km^2/decade (0.70 x 10^6 km^2/decade), equivalent to a 7.7 %/decade (6.3 %/decade) rise. A comparable trend of 9.1 %/decade (8.5 %/decade) is estimated in the Ross sector, at 0.21 x 10^6 km2/decade (0.23 x 10^6 km2/decade). The opposite trend is found in the Amundsen/Bellingshausen sector: a -0.15 x 10^6 km^2/decade (-0.17 x 10^6 km^2/decade) decline, or -14.6 %/decade (-13.4 %/decade). The estimated annual increase of Antarctic sea ice thickness is 22.6 cm/decade (49.2 %/decade) and of volume is 3.78 x 10^3 km^3/decade (68.3 %/decade). The Ross sector showed similar trends for thickness, at 23.8 cm/decade (47.0 %/decade), and volume, at 1.11 x 10^3 km^3/decade (75.8 %/decade). Thickness has increased in the Amundsen/Bellingshausen sector, 20.7 cm/decade (44.8 %/decade), but with a less pronounced volume rise of 0.17 x10^3 km^3/decade (26.0 %/decade). Monthly sea ice thickness anomalies show a weak response to the El Nino Southern Oscillation (ENSO) index. A strong positive response is observed in 2008 when a negative a negative ENSO index compounded to a positive Southern Annular Mode (SAM) index. Therefore the estimated increase of sea ice thickness in the Southern Ocean could be attributed to the prevailing atmospheric conditions with a positive SAM phase over the past decade.

Texture analysis has been used extensively in the computer-assisted interpretation of SAR sea ice imagery. Provision of maps which distinguish relevant ice types is significant for monitoring global warming and ship navigation. Due to the abundance of SAR imagery available, there exists a need to develop an automated approach for SAR sea ice interpretation. Grey level co-occurrence probability (<i>GLCP</i>) texture features are very popular for SAR sea ice classification. Although these features are used extensively in the literature, they have a tendency to erode and misclassify texture boundaries. Proposed is an advancement to the <i>GLCP</i> method which will preserve texture boundaries during image segmentation. This method exploits the relationship a pixel has with its closest neighbors and weights the texture measurement accordingly. These texture features are referred to as <i>WGLCP</i> (weighted <i>GLCP</i>) texture features. In this research, the <i>WGLCP</i> and <i>GLCP</i> feature sets are compared in terms of boundary preservation, unsupervised segmentation ability, robustness to increasing boundary density and computation time. The <i>WGLCP</i> method outperforms the <i>GLCP</i> method in all aspects except for computation time, where it suffers. From the comparative analysis, an inconsistency with the <i>GLCP</i> correlation statistic was observed, which motivated an investigative study into using this statistic for image segmentation. As the overall goal of the thesis is to improve SAR sea ice segmentation accuracy, the concepts developed from the study are applied to the image segmentation problem. The results indicate that for images with high contrast boundaries, the <i>GLCP</i> correlation statistical feature decreases segmentation accuracy. When comparing <i>WGLCP</i> and <i>GLCP</i> features for segmentation, the <i>WGLCP</i> features provide higher segmentation accuracy.

The mapping of sea ice is an important task for understanding global climate and for safe shipping. Currently, sea ice maps are created by human analysts with the help of remote sensing imagery, including synthetic aperture radar (SAR) imagery. While the maps are generally correct, they can be somewhat subjective and do not have pixel-level resolution due to the time consuming nature of manual segmentation. Therefore, automated sea ice mapping algorithms such as the multivariate iterative region growing with semantics (MIRGS) sea ice image segmentation algorithm are needed. MIRGS was designed to work with one-channel single-polarization SAR imagery from the RADARSAT-1 satellite. The launch of RADARSAT-2 has made available two-channel dual-polarization SAR imagery for the purposes of sea ice mapping. Dual-polarization imagery provides more information for distinguishing ice types, and one of the channels is less sensitive to changes in the backscatter caused by the SAR incidence angle parameter. In the past, this change in backscatter due to the incidence angle was a key limitation that prevented automatic segmentation of full SAR scenes. This thesis investigates techniques to make use of the dual-polarization data in MIRGS. An evaluation of MIRGS with RADARSAT-2 data was performed and showed that some detail was lost and that the incidence angle caused errors in segmentation. Several data fusion schemes were investigated to determine if they can improve performance. Gradient generation methods designed to take advantage of dual-polarization data, feature space fusion using linear and non-linear transforms as well as image fusion methods based on wavelet combination rules were implemented and tested. Tuning of the MIRGS parameters was performed to find the best set of parameters for segmentation of dual-polarization data. Results show that the standard MIRGS algorithm with default parameters provides the highest accuracy, so no changes are necessary for dual-polarization data. A hierarchical segmentation scheme that segments the dual-polarization channels separately was implemented to overcome the incidence angle errors. The technique is effective but requires more user input than the standard MIRGS algorithm.

Arktis är den plats där den globala uppvärmningen är som mest märkbar på hela jorden (Arktiska rådet). Därför är Arktis ett intressant område att studera ur klimatsynpunkt. Enligt Gore (2006) så kan en ökning av jordens medeltemperatur på 1,5 °C leda till att de ekvatoriala områdena får en temperaturökning på 0,5 °C medan temperaturen vid Arktis kan stiga med hela 6 °C. De senaste 30 åren har medeltemperaturen vid Arktis stigit med drygt en grad per decennium (Anisimov, 2007) medan den globala medeltemperaturen för samma period endast stigit med ca 0.15 grader per decennium. Arktis tros ha varit isfritt under en värmeperiod för ca 6000 – 8500 år sedan (Founder, 2011) men det som är unikt med den aktuella situationen är att avsmältningen går så snabbt. Mycket snabbare än naturliga cykler (Gore, 2006) och det råder inom forskarvärlden ingen tvekan om att det är de antropogena utsläppen av växthusgaser som är orsaken. Frågeställningen som ligger till grund för den här rapporten är att ta reda på vilket årtal som Arktis kommer att vara isfritt. Detta görs genom att undersöka hur den Arktiska isutsträckningen minskat under perioden 1979-2011.  Isdata till beräkningarna i den här rapporten är tagna från National Snow and Ice Data Center, Boulder, Colorado USA, och värdena för temperaturerna kommer från National Aeronautics and Space Administration (NASA). Genom att med minstakvadratanpassning göra en linjär approximation av varje års minsta värde av isutsträckningen vid Arktis för perioden 1979-2011 erhålls att Arktis kommer att vara isfritt år 2062. / The Arctic is the place where global warming is most significant in the whole world (Arctic Council). That is why the Arctic is an interesting area to study from a climate perspective. According to Gore (2006), an increase in global temperature of 1.5 °C might lead to an increase of 0.5 °C in the equatorial regions while the Arctic could receive a teperature rise by as much as 6 °C . During the past 30 years, average temperatures in the Arctic have risen by more then one degree per decade (Anisimov, 2007) while the global average teperature for the same period only increased by about 0.15 degrees per decade. Arctic is believed to have been ice-free during a heating period for about 6000 - 8500 years ago (Founder, 2011) but what is unique about the current situation is that the melting is so quickly. Much faster than natural cycles (Gore, 2006) and there is within the scientific community no doubt that the anthropogenic emissions of greenhouse gases is the cause. The issue which forms the basis for this report has been to investigate how the Arctic extent decreased over the period 1979-2011 and then to attempt to determine a year for when the Arctic will be ice free. Ice data to the calculations in this report are taken from the National Snow and Ice Data Center, Boulder, Colorado USA, and the temperature values comes from the National Aeronautics and Space Administration (NASA). By making a linear approximation with the least square method of each year’s minimum value of the Arctic sea ice extent for the period 1979-2011 it is obtained that the Arctic sea will be ice free by the year of 2062.

Texture analysis has been used extensively in the computer-assisted interpretation of SAR sea ice imagery. Provision of maps which distinguish relevant ice types is significant for monitoring global warming and ship navigation. Due to the abundance of SAR imagery available, there exists a need to develop an automated approach for SAR sea ice interpretation. Grey level co-occurrence probability (<i>GLCP</i>) texture features are very popular for SAR sea ice classification. Although these features are used extensively in the literature, they have a tendency to erode and misclassify texture boundaries. Proposed is an advancement to the <i>GLCP</i> method which will preserve texture boundaries during image segmentation. This method exploits the relationship a pixel has with its closest neighbors and weights the texture measurement accordingly. These texture features are referred to as <i>WGLCP</i> (weighted <i>GLCP</i>) texture features. In this research, the <i>WGLCP</i> and <i>GLCP</i> feature sets are compared in terms of boundary preservation, unsupervised segmentation ability, robustness to increasing boundary density and computation time. The <i>WGLCP</i> method outperforms the <i>GLCP</i> method in all aspects except for computation time, where it suffers. From the comparative analysis, an inconsistency with the <i>GLCP</i> correlation statistic was observed, which motivated an investigative study into using this statistic for image segmentation. As the overall goal of the thesis is to improve SAR sea ice segmentation accuracy, the concepts developed from the study are applied to the image segmentation problem. The results indicate that for images with high contrast boundaries, the <i>GLCP</i> correlation statistical feature decreases segmentation accuracy. When comparing <i>WGLCP</i> and <i>GLCP</i> features for segmentation, the <i>WGLCP</i> features provide higher segmentation accuracy.

The mapping of sea ice is an important task for understanding global climate and for safe shipping. Currently, sea ice maps are created by human analysts with the help of remote sensing imagery, including synthetic aperture radar (SAR) imagery. While the maps are generally correct, they can be somewhat subjective and do not have pixel-level resolution due to the time consuming nature of manual segmentation. Therefore, automated sea ice mapping algorithms such as the multivariate iterative region growing with semantics (MIRGS) sea ice image segmentation algorithm are needed. MIRGS was designed to work with one-channel single-polarization SAR imagery from the RADARSAT-1 satellite. The launch of RADARSAT-2 has made available two-channel dual-polarization SAR imagery for the purposes of sea ice mapping. Dual-polarization imagery provides more information for distinguishing ice types, and one of the channels is less sensitive to changes in the backscatter caused by the SAR incidence angle parameter. In the past, this change in backscatter due to the incidence angle was a key limitation that prevented automatic segmentation of full SAR scenes. This thesis investigates techniques to make use of the dual-polarization data in MIRGS. An evaluation of MIRGS with RADARSAT-2 data was performed and showed that some detail was lost and that the incidence angle caused errors in segmentation. Several data fusion schemes were investigated to determine if they can improve performance. Gradient generation methods designed to take advantage of dual-polarization data, feature space fusion using linear and non-linear transforms as well as image fusion methods based on wavelet combination rules were implemented and tested. Tuning of the MIRGS parameters was performed to find the best set of parameters for segmentation of dual-polarization data. Results show that the standard MIRGS algorithm with default parameters provides the highest accuracy, so no changes are necessary for dual-polarization data. A hierarchical segmentation scheme that segments the dual-polarization channels separately was implemented to overcome the incidence angle errors. The technique is effective but requires more user input than the standard MIRGS algorithm.

The synthetic aperture radar (SAR) onboard Earth observing satellites has been acknowledged as an integral tool for many applications in monitoring the marine environment. Some of these applications include regional sea-ice monitoring and detection of illegal or accidental oil discharges from ships. Nonetheless, a practicality of the usage of SAR images is greatly hindered by the presence of speckle noises. Such noise must be eliminated or reduced to be utilized in real-world applications to ensure the safety of the marine environment. Thus this thesis presents a novel two-phase total variation optimization segmentation approach to tackle such a challenging task. In the total variation optimization phase, the Rudin-Osher-Fatemi total variation model was modified and implemented iteratively to estimate the piecewise smooth state by minimizing the total variation constraints. In the finite mixture model classification phase, an expectation-maximization method was performed to estimate the final class likelihoods using a Gaussian mixture model. Then a maximum likelihood classification technique was utilized to obtain the final segmented result. For its evaluation, a synthetic image was used to test its effectiveness. Then it was further applied to two distinct real SAR images, X-band COSMO-SkyMed imagery containing verified oil-spills and C-band RADARSAT-2 imagery mainly containing two different sea-ice types to confirm its robustness. Furthermore, other well-established methods were compared with the proposed method to ensure its performance. With the advantage of a short processing time, the visual inspection and quantitative analysis including kappa coefficients and F1 scores of segmentation results confirm the superiority of the proposed method over other existing methods.

Thesis (M.Eng.)--Memorial University of Newfoundland, 2002. / Bibliography: leaves 115-116.

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