L’observation de la Terre par des systèmes d’acquisition d’images permet de suivre l’évolution temporelle de phénomènes naturels tels que les séismes, les volcans ou les mouvements gravitaires. Différentes techniques existent dont l’imagerie satellitaire, la photogrammétrie terrestre et les mesures in-situ. Les séries temporelles d’images issues d’appareils photo automatiques (Time Lapse) sont une source d’informations en plein essor car elles offrent un compromis intéressant en termes de couverture spatiale et de fréquence d’observation pour mesurer les déplacements de surface de zones spécifiques. Cette thèse est consacrée à l’analyse de séries d’images issues de la photographie terrestre et de l’imagerie radar satellitaire pour la mesure du déplacement des glaciers Alpins. Nous nous intéressons en particulier aux problèmes du traitement de Time Lapse stéréo pour le suivi d’objets géophysiques dans des conditions terrain peu favorables à la photogrammétrie. Nous proposons une chaîne de traitement mono-caméra qui comprend les étapes de sélection automatique des images, de recalage et de calcul de champs de déplacement bidimensionnel (2D). L’information apportée par les couples stéréo est ensuite exploitée à l’aide du logiciel MICMAC pour reconstruire le relief et obtenir le déplacement tridimensionnel(3D). Plusieurs couples d’images radar à synthèse d’ouverture (SAR) ont également été traités à l’aide des outils EFIDIR pour obtenir des champs de déplacement 2D dans la géométrie radar sur des orbites ascendantes ou descendantes. La combinaison de mesures obtenues quasi-simultanément sur ces deux types d’orbites permet de reconstruire le déplacement 3D. Ces méthodes ont été mises en oeuvre sur des séries de couples stéréo acquis par deux appareils photo automatiques installés sur la rive droite du glacier d’Argentière et sur des images du satellite TerraSAR-X couvrant le massif du Mont-Blanc. Les résultats sont présentés sur des données acquises lors d’une expérimentation multi-instruments menée en collaboration avec l’IGN à l’automne 2013, incluant le déploiement d’un réseau de Géocubes qui ont fournit des mesures GPS. Elles sont utilisées pour évaluer la précision des résultats obtenus par télédétection proximale et spatiale sur ce type de glacier. / Earth observation by image acquisition systems allows the survey of temporal evolution of natural phenomena such as earthquakes, volcanoes or gravitational movements. Various techniques exist including satellite imagery, terrestrial photogrammetry and in-situ measurements. Image time series from automatic cameras (Time Lapse) are a growing source of information since they offer an interesting compromise in terms of spatial coverage and observation frequency in order to measure surface motion in specific areas. This PhD thesis is devoted to the analysis of image time series from terrestrial photography and satellite radar imagery to measure the displacement of Alpine glaciers. We are particularly interested in Time Lapse stereo processing problems for monitoring geophysical objects in unfavorable conditions for photogrammetry. We propose a single-camera processing chain that includes the steps of automatic photograph selection, coregistration and calculation of two-dimensional (2D) displacement field. The information provided by the stereo pairs is then processed using the MICMAC software to reconstruct the relief and get the three-dimensional (3D) displacement. Several pairs of synthetic aperture radar (SAR) images were also processed with the EFIDIR tools to obtain 2D displacement fields in the radar geometry in ascending or descending orbits. The combination of measurements obtained almost simultaneously on these two types of orbits allows the reconstruction of the 3D displacement. These methods have been implemented on time series of stereo pairs acquired by two automatic cameras installed on the right bank of the Argentière glacier and on TerraSAR-X satellite images covering the Mont-Blanc massif. The results are presented on data acquired during a multi-instrument experiment conducted in collaboration with the French Geographic National Institute (IGN) during the fall of 2013,with a network of Géocubes which provided GPS measurements. They are used to evaluate the accuracy of the results obtained by proximal and remote sensing on this type of glacier.

A quase inacessibilidade de grandes partes do Oceano Austral torna o conhecimento da espessura do gelo marinho limitado. Esta informação é essencial para a determinação do balanço de massa deste componente da criosfera. Na transição do inverno para a primavera de 2006, uma equipe de pesquisadores, coletou uma série de perfis de espessura de gelo marinho no norte e noroeste do mar de Weddell. Eles estavam a bordo do navio de pesquisa alemão Polarstern do Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung (AWI) e utilizaram um sistema composto por um sensor eletromagnético, altímetro laser e um Sistema de Posicionamento Global Diferencial (DGPS) aerotransportado por helicóptero. Simultaneamente, a Agência Espacial Europeia (ESA), adquiriu imagens ENVISAT ASAR WSM da área de pesquisa. O objetivo principal desta tese é determinar a relação existente entre o retroespalhamento medido pelo Radar de Abertura Sintética e a espessura do gelo marinho obtida pelo HEM (Helicopter-borne ElectroMagnetic system) usando os dados citados acima. Utilizamos os programas de computador NEST®, MATLAB®, EXCEL®, ArcGIS®/ArcMAP®, para processar, analisar e selecionar as imagens, para determinar a relação entre o retroespalhamento e as medidas, quase-tempo-coincidentes, de espessura do gelo. Projetamos as trajetórias dos voos sobre as imagens obtidas nas mesmas datas e extraímos os pixels referentes aos locais onde foram medidas as espessuras de gelo marinho. Apropriamos os valores de espessura do gelo para a área de cada pixel sobre o qual se referiam. Uma análise estatística determinou que o parâmetro que melhor representa a espessura do gelo dentro da área do pixel é a média. A regressão linear é a melhor forma de ajuste das relações entre o valor de retroespalhamento do pixel e a espessura do gelo marinho contido na área deste pixel. O coeficiente de correlação linear de Pearson, resultante de análise paramétrica, indica uma forte correlação (0,75) entre retroespalhamento e espessura do gelo marinho. Porém, a análise não paramétrica de Spearman resultou em um coeficiente de correlação baixo (0,06) o que pode indicar que os dados analisados são compostos por duas populações distintas (e.g., gelo de primeiro ano e plurianual). Contudo, a análise não paramétrica de Kolmogorov-Smirnov aventa a possibilidade de que não tenhamos amostrado toda população. Esta seria a razão de não haver valores de espessuras relativas ao intervalo entre -9.21dB e -1.35dB, o que poderia induzir ao baixo valor do coeficiente de correlação na análise de Spearman. Aplicamos a equação linear: y=0,6345x+12,015 às imagens e pudemos separá-las em doze classes: uma para água e onze para gelo marinho, estas com intervalos de um metro. Isto possibilitou a observação de importantes feições oceanográficas como: canais de águas abertas; cristas de compressão, decaimento do gelo marinho, deslocamento de icebergs (como indicadores de correntes, marés e ventos), liberação de gelo por geleiras de maré, desprendimento de iceberg da plataforma de gelo Larsen C, esteiras de ondas e vórtices oceânicos. Com base no exposto, podemos afirmar que, estatisticamente, nossos resultados são robustos e significantes, com nível de confiança entre 95% e 99%. A equação que propomos é um primeiro passo para inferir-se a espessura do gelo marinho a partir de coeficientes de retroespalhamento SAR. / The almost inaccessibility of large parts of the Southern Ocean makes the knowledge on the sea-ice thickness limited. This information is essential for determining the mass balance of this cryosphere component. During the transition from winter to spring 2006, a researcher team performed several sea-ice thickness profiles in the north and northwest of the Weddell Sea. They were aboard the German research vessel Polarstern from the Alfred-Wegener-Institute, Helmholtz-Zentrum für Polar- und Meeresforschung (AWI) and utilizing for those measurements a Helicopter-borne Electromagnetic system (HEM). The HEM is composed of an electromagnetic sensor, laser altimeter, and a Differential Global Positioning System (DGPS). Simultaneously, the European Space Agency (ESA) ENVISAT ASAR WSM acquired images from the research area. The main objective of this thesis is to determine the relationship between the Synthetic Aperture Radar backscattering and the HEM’s sea-ice thickness measurements using data listed above. We used the computer programs: NEST®, MATLAB®, EXCEL®, ArcGIS® / ArcMap®, to process, analyze and select images, in order to determine the relationship between the backscattering and the quasi-time-coincident ice thickness measurements. We projected the flights trajectories on the images obtained on the same dates, extracting the pixels pertaining to the places where the sea-ice thicknesses were determined. We ascribed ice thickness values for each area covered by the pixel. A statistical analysis determined that the best ice thickness parameter within a pixel area is its mean. Linear regression is the best way to adjust the relationship between the pixel backscatter value and the sea-ice thickness contained within the pixel area. The Pearson linear correlation coefficient, resulting from parametric analysis, indicates a strong correlation (0.75) between backscatter and sea-ice thickness. However, the nonparametric Spearman analysis resulted in a low correlation coefficient (0.06), which may indicate that the analyzed data consist of two distinct populations (e.g., first-year and multi-year ice). However, the Kolmogorov-Smirnov nonparametric analysis brought up the possibility that we just have not sampled the entire population. This could explain the no existence of sea-ice thicknesses values on the interval from -9.21dB to -1.35dB, which could lead to the low correlation coefficient in the Spearman analysis. We applied the linear equation: =,+, to the images, separating them into twelve classes: one for water and eleven to sea-ice, the latter in one-meter thickness intervals. The results enabled the observation of important oceanographic features such as open water channels, pressure ridges, sea-ice decay, icebergs motion (as indicators of currents, tides and winds), glaciers discharge, iceberg calving from Larsen C ice shelf, wakes and oceanic eddies. Based on the foregoing, we can say that, statistically, our results are robust and significantly, with a confidence level from 95% to 99%. The proposed equation is a first step to inferring sea-ice thickness from SAR backscatter coefficients.

A quase inacessibilidade de grandes partes do Oceano Austral torna o conhecimento da espessura do gelo marinho limitado. Esta informação é essencial para a determinação do balanço de massa deste componente da criosfera. Na transição do inverno para a primavera de 2006, uma equipe de pesquisadores, coletou uma série de perfis de espessura de gelo marinho no norte e noroeste do mar de Weddell. Eles estavam a bordo do navio de pesquisa alemão Polarstern do Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung (AWI) e utilizaram um sistema composto por um sensor eletromagnético, altímetro laser e um Sistema de Posicionamento Global Diferencial (DGPS) aerotransportado por helicóptero. Simultaneamente, a Agência Espacial Europeia (ESA), adquiriu imagens ENVISAT ASAR WSM da área de pesquisa. O objetivo principal desta tese é determinar a relação existente entre o retroespalhamento medido pelo Radar de Abertura Sintética e a espessura do gelo marinho obtida pelo HEM (Helicopter-borne ElectroMagnetic system) usando os dados citados acima. Utilizamos os programas de computador NEST®, MATLAB®, EXCEL®, ArcGIS®/ArcMAP®, para processar, analisar e selecionar as imagens, para determinar a relação entre o retroespalhamento e as medidas, quase-tempo-coincidentes, de espessura do gelo. Projetamos as trajetórias dos voos sobre as imagens obtidas nas mesmas datas e extraímos os pixels referentes aos locais onde foram medidas as espessuras de gelo marinho. Apropriamos os valores de espessura do gelo para a área de cada pixel sobre o qual se referiam. Uma análise estatística determinou que o parâmetro que melhor representa a espessura do gelo dentro da área do pixel é a média. A regressão linear é a melhor forma de ajuste das relações entre o valor de retroespalhamento do pixel e a espessura do gelo marinho contido na área deste pixel. O coeficiente de correlação linear de Pearson, resultante de análise paramétrica, indica uma forte correlação (0,75) entre retroespalhamento e espessura do gelo marinho. Porém, a análise não paramétrica de Spearman resultou em um coeficiente de correlação baixo (0,06) o que pode indicar que os dados analisados são compostos por duas populações distintas (e.g., gelo de primeiro ano e plurianual). Contudo, a análise não paramétrica de Kolmogorov-Smirnov aventa a possibilidade de que não tenhamos amostrado toda população. Esta seria a razão de não haver valores de espessuras relativas ao intervalo entre -9.21dB e -1.35dB, o que poderia induzir ao baixo valor do coeficiente de correlação na análise de Spearman. Aplicamos a equação linear: y=0,6345x+12,015 às imagens e pudemos separá-las em doze classes: uma para água e onze para gelo marinho, estas com intervalos de um metro. Isto possibilitou a observação de importantes feições oceanográficas como: canais de águas abertas; cristas de compressão, decaimento do gelo marinho, deslocamento de icebergs (como indicadores de correntes, marés e ventos), liberação de gelo por geleiras de maré, desprendimento de iceberg da plataforma de gelo Larsen C, esteiras de ondas e vórtices oceânicos. Com base no exposto, podemos afirmar que, estatisticamente, nossos resultados são robustos e significantes, com nível de confiança entre 95% e 99%. A equação que propomos é um primeiro passo para inferir-se a espessura do gelo marinho a partir de coeficientes de retroespalhamento SAR. / The almost inaccessibility of large parts of the Southern Ocean makes the knowledge on the sea-ice thickness limited. This information is essential for determining the mass balance of this cryosphere component. During the transition from winter to spring 2006, a researcher team performed several sea-ice thickness profiles in the north and northwest of the Weddell Sea. They were aboard the German research vessel Polarstern from the Alfred-Wegener-Institute, Helmholtz-Zentrum für Polar- und Meeresforschung (AWI) and utilizing for those measurements a Helicopter-borne Electromagnetic system (HEM). The HEM is composed of an electromagnetic sensor, laser altimeter, and a Differential Global Positioning System (DGPS). Simultaneously, the European Space Agency (ESA) ENVISAT ASAR WSM acquired images from the research area. The main objective of this thesis is to determine the relationship between the Synthetic Aperture Radar backscattering and the HEM’s sea-ice thickness measurements using data listed above. We used the computer programs: NEST®, MATLAB®, EXCEL®, ArcGIS® / ArcMap®, to process, analyze and select images, in order to determine the relationship between the backscattering and the quasi-time-coincident ice thickness measurements. We projected the flights trajectories on the images obtained on the same dates, extracting the pixels pertaining to the places where the sea-ice thicknesses were determined. We ascribed ice thickness values for each area covered by the pixel. A statistical analysis determined that the best ice thickness parameter within a pixel area is its mean. Linear regression is the best way to adjust the relationship between the pixel backscatter value and the sea-ice thickness contained within the pixel area. The Pearson linear correlation coefficient, resulting from parametric analysis, indicates a strong correlation (0.75) between backscatter and sea-ice thickness. However, the nonparametric Spearman analysis resulted in a low correlation coefficient (0.06), which may indicate that the analyzed data consist of two distinct populations (e.g., first-year and multi-year ice). However, the Kolmogorov-Smirnov nonparametric analysis brought up the possibility that we just have not sampled the entire population. This could explain the no existence of sea-ice thicknesses values on the interval from -9.21dB to -1.35dB, which could lead to the low correlation coefficient in the Spearman analysis. We applied the linear equation: =,+, to the images, separating them into twelve classes: one for water and eleven to sea-ice, the latter in one-meter thickness intervals. The results enabled the observation of important oceanographic features such as open water channels, pressure ridges, sea-ice decay, icebergs motion (as indicators of currents, tides and winds), glaciers discharge, iceberg calving from Larsen C ice shelf, wakes and oceanic eddies. Based on the foregoing, we can say that, statistically, our results are robust and significantly, with a confidence level from 95% to 99%. The proposed equation is a first step to inferring sea-ice thickness from SAR backscatter coefficients.

A quase inacessibilidade de grandes partes do Oceano Austral torna o conhecimento da espessura do gelo marinho limitado. Esta informação é essencial para a determinação do balanço de massa deste componente da criosfera. Na transição do inverno para a primavera de 2006, uma equipe de pesquisadores, coletou uma série de perfis de espessura de gelo marinho no norte e noroeste do mar de Weddell. Eles estavam a bordo do navio de pesquisa alemão Polarstern do Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung (AWI) e utilizaram um sistema composto por um sensor eletromagnético, altímetro laser e um Sistema de Posicionamento Global Diferencial (DGPS) aerotransportado por helicóptero. Simultaneamente, a Agência Espacial Europeia (ESA), adquiriu imagens ENVISAT ASAR WSM da área de pesquisa. O objetivo principal desta tese é determinar a relação existente entre o retroespalhamento medido pelo Radar de Abertura Sintética e a espessura do gelo marinho obtida pelo HEM (Helicopter-borne ElectroMagnetic system) usando os dados citados acima. Utilizamos os programas de computador NEST®, MATLAB®, EXCEL®, ArcGIS®/ArcMAP®, para processar, analisar e selecionar as imagens, para determinar a relação entre o retroespalhamento e as medidas, quase-tempo-coincidentes, de espessura do gelo. Projetamos as trajetórias dos voos sobre as imagens obtidas nas mesmas datas e extraímos os pixels referentes aos locais onde foram medidas as espessuras de gelo marinho. Apropriamos os valores de espessura do gelo para a área de cada pixel sobre o qual se referiam. Uma análise estatística determinou que o parâmetro que melhor representa a espessura do gelo dentro da área do pixel é a média. A regressão linear é a melhor forma de ajuste das relações entre o valor de retroespalhamento do pixel e a espessura do gelo marinho contido na área deste pixel. O coeficiente de correlação linear de Pearson, resultante de análise paramétrica, indica uma forte correlação (0,75) entre retroespalhamento e espessura do gelo marinho. Porém, a análise não paramétrica de Spearman resultou em um coeficiente de correlação baixo (0,06) o que pode indicar que os dados analisados são compostos por duas populações distintas (e.g., gelo de primeiro ano e plurianual). Contudo, a análise não paramétrica de Kolmogorov-Smirnov aventa a possibilidade de que não tenhamos amostrado toda população. Esta seria a razão de não haver valores de espessuras relativas ao intervalo entre -9.21dB e -1.35dB, o que poderia induzir ao baixo valor do coeficiente de correlação na análise de Spearman. Aplicamos a equação linear: y=0,6345x+12,015 às imagens e pudemos separá-las em doze classes: uma para água e onze para gelo marinho, estas com intervalos de um metro. Isto possibilitou a observação de importantes feições oceanográficas como: canais de águas abertas; cristas de compressão, decaimento do gelo marinho, deslocamento de icebergs (como indicadores de correntes, marés e ventos), liberação de gelo por geleiras de maré, desprendimento de iceberg da plataforma de gelo Larsen C, esteiras de ondas e vórtices oceânicos. Com base no exposto, podemos afirmar que, estatisticamente, nossos resultados são robustos e significantes, com nível de confiança entre 95% e 99%. A equação que propomos é um primeiro passo para inferir-se a espessura do gelo marinho a partir de coeficientes de retroespalhamento SAR. / The almost inaccessibility of large parts of the Southern Ocean makes the knowledge on the sea-ice thickness limited. This information is essential for determining the mass balance of this cryosphere component. During the transition from winter to spring 2006, a researcher team performed several sea-ice thickness profiles in the north and northwest of the Weddell Sea. They were aboard the German research vessel Polarstern from the Alfred-Wegener-Institute, Helmholtz-Zentrum für Polar- und Meeresforschung (AWI) and utilizing for those measurements a Helicopter-borne Electromagnetic system (HEM). The HEM is composed of an electromagnetic sensor, laser altimeter, and a Differential Global Positioning System (DGPS). Simultaneously, the European Space Agency (ESA) ENVISAT ASAR WSM acquired images from the research area. The main objective of this thesis is to determine the relationship between the Synthetic Aperture Radar backscattering and the HEM’s sea-ice thickness measurements using data listed above. We used the computer programs: NEST®, MATLAB®, EXCEL®, ArcGIS® / ArcMap®, to process, analyze and select images, in order to determine the relationship between the backscattering and the quasi-time-coincident ice thickness measurements. We projected the flights trajectories on the images obtained on the same dates, extracting the pixels pertaining to the places where the sea-ice thicknesses were determined. We ascribed ice thickness values for each area covered by the pixel. A statistical analysis determined that the best ice thickness parameter within a pixel area is its mean. Linear regression is the best way to adjust the relationship between the pixel backscatter value and the sea-ice thickness contained within the pixel area. The Pearson linear correlation coefficient, resulting from parametric analysis, indicates a strong correlation (0.75) between backscatter and sea-ice thickness. However, the nonparametric Spearman analysis resulted in a low correlation coefficient (0.06), which may indicate that the analyzed data consist of two distinct populations (e.g., first-year and multi-year ice). However, the Kolmogorov-Smirnov nonparametric analysis brought up the possibility that we just have not sampled the entire population. This could explain the no existence of sea-ice thicknesses values on the interval from -9.21dB to -1.35dB, which could lead to the low correlation coefficient in the Spearman analysis. We applied the linear equation: =,+, to the images, separating them into twelve classes: one for water and eleven to sea-ice, the latter in one-meter thickness intervals. The results enabled the observation of important oceanographic features such as open water channels, pressure ridges, sea-ice decay, icebergs motion (as indicators of currents, tides and winds), glaciers discharge, iceberg calving from Larsen C ice shelf, wakes and oceanic eddies. Based on the foregoing, we can say that, statistically, our results are robust and significantly, with a confidence level from 95% to 99%. The proposed equation is a first step to inferring sea-ice thickness from SAR backscatter coefficients.

L’imagerie polarimétrique permet d’estimer certaines caractéristiques d’un milieu qui peuvent ne pas être révélées par imagerie d’intensité standard. Cependant, les mesures effectuées peuvent être fortement perturbées par des fluctuations inhérentes aux processus physiques d’acquisition. Ces fluctuations sont difficiles à atténuer, notamment à cause de la fragilité des milieux observés ou de l’inhomogénéité des images acquises. Il est alors utile de caractériser la précision des estimations qu’il est possible d’obtenir. Dans cette thèse, cette question est abordée au travers de deux applications d’imagerie polarimétrique : la microscopie non-linéaire de second harmonique résolue en polarisation (PSHG) pour l’analyse de l’organisation structurale d’objets biomoléculaires, et l’imagerie radar polarimétrique interférométrique à synthèse d’ouverture (PolInSAR) pour l’estimation des paramètres du couvert forestier. Pour la première application, la précision d’estimation en présence de bruit de Poisson est caractérisée pour l’ensemble des assemblages moléculaires présentant une symétrie cylindrique, ce qui permet notamment d'aboutir à une procédure de détection des mesures qui ne permettent pas d’atteindre une précision d’estimation requise. Pour l’imagerie PolInSAR, on analyse une modalité d'acquisition intéressante pour les futures missions satellitaires. En particulier, on étudie dans ce contexte la précision d'estimation de la hauteur de végétation en présence de bruit de speckle en s'appuyant sur l'analyse du contraste polarimétrique. Une interprétation simple des comportements de cette modalité d'acquisition est obtenue dans la sphère de Poincaré. / Polarimetric imaging allows one to estimate some characteristics of a medium which might not be revealed by standard intensity imaging. However, the measurements can be strongly perturbed by fluctuations that are inherent in the physical acquisition processes. These fluctuations are difficult to attenuate, for instance because of the fragility of the observed media or because of the inhomogeneity of the obtained images. It is then useful to characterize the estimation precision that can be reached. In this thesis, this question is addressed through two polarimetric imaging applications: polarized-resolved second-harmonic generation non-linear microscopy (PSHG) for the analysis of the structural organization of biomolecular objects, and polarimetric interferometric synthetic aperture radar imaging (PolInSAR) for the estimation of vegetation parameters. For the first application, the estimation precision in the presence of Poisson noise is characterized for any molecular assembly that presents a cylindrical symmetry. This study results in particular in a procedure to detect the measurements that do not lead to a required precision. For PolInSAR imaging, we analyze an acquisition system that is interesting for future spatial missions. In particular, the estimation precision of the vegetation height is studied in this context in the presence of speckle noise by relying on the analysis of the polarimetric contrast. A simple interpretation of the behavior of this acquisition system is obtained in the Poincaré sphere.

Chapter 2 The sea surface microlayer is a biogenic thin layer, comprising less than one millimeter of the ocean surface. This surface layer has gained much attention due to its dampening effect on ocean capillary ripples. The chemistry of the air-sea interface has been studied for decades; however, the structure and function of the marine bacterial community within the sea surface microlayer are still understudied. Although various sea surface microlayer sampling techniques were developed over the past decades, aseptic bacterial sampling in the open ocean is a rather challenging task. In this study, a new approach is presented. It is designed for bacterial sampling of the sea surface microlayer, which intends to reduce sampling contamination from the vessel, subsurface water and the investigators. A 47mm polycarbonate membrane was utilized at each sampling site. In addition, the metagenomic approach using the new generation 454 high-throughput DNA sequencing system was employed to compensate for the small sample size. Two sample sets were collected in summer 2010 and fall 2011 from the sea surface microlayer and underlying water (20 cm deep). A contamination assessment was carried out to determine that contamination might have been caused during the use of the sampling techniques. A total of 14,120 bacterial 16S rRNA gene sequences with an average length of 437.8 bp were obtained. A total of 1,254 Operational Taxonomic Units (OTUs) were constructed and 268 genera were identified. The results indicated that the bacterial compositions of the sea surface microlayer samples were distinct from those of the underlying water samples. This experiment demonstrated that the new generation sequencing platform and microbial metagenomics analysis software together served as powerful tools to gain a deeper understanding of microbial communities within the sea surface microlayer. Furthermore, it is suggested that the newly employed sampling methods could be used to obtain a snapshot of bacterial community structure as well as environmental conditions. Chapter 3 Synthetic aperture radar (SAR) remote sensing captures various fine-scale features on the ocean surface such as coastal discharge, oil pollution, vessel traffic, algal blooms and sea slicks. Although numerous factors potentially affect the SAR imaging process, the influence of biogenic and anthropogenic surfactants has been suggested as one of the primary parameters, especially under relatively low wind conditions. Surfactants have a tendency to dampen the short gravity-capillary ocean waves causing the sea surface to smoothen, thus allowing the radar to detect areas of surfactants. Surfactants are found in sea slicks, which are the accumulation of organic material shaped as elongated bands on the ocean’s surface. Sea slicks are often observable with the naked eye due to their glassy appearance and can also be seen on SAR images as dark scars. While the sources of surfactants can vary, some are known to be associated with marine bacteria. Countless numbers of marine bacteria are present in the oceanic environment, and their biogeochemical contributions cannot be overlooked. Not only do marine bacteria produce surfactants, but they also play an important role in the transformation of surfactants. In this study, we profiled the surfactant-associated bacteria composition within the biogenic thin layer of the ocean surface more commonly referred as the sea surface microlayer (SML). Bacterial samples were collected from the SML for comparative analysis from both within and outside of sea slick areas as well as the respective underlying subsurface water. The bacterial microlayer sampling coincided with SAR satellite, RADARSAT-2, overpasses to demonstrate the simultaneous in-situ measurements during a satellite image capture. The SML sampling method was designed to enable aseptic bacterial sampling. A 47 mm polycarbonate membrane was utilized at each sampling site to obtain a snapshot of the bacterial community structure at a specific space and time. Also, a new generation high-throughput sequencing method was employed to compensate for the small sample size acquired. A total of 27,006 nucleotide sequences (16S rRNA genes) with an average 437.8 bp in length were analyzed. The results revealed the presence of industrially important surfactant-producing marine bacteria, Acinetobacter, Bacillus, Corynebacterium and surfactant-degrading marine bacteria, Escherichia. In addition, Pseudomonas was detected which can be either a producer, decomposer or both. Recognizing that there is still a large number of marine bacterial species that have not been taxonomically classified nor recognized as surfactant-associated species, the effects on SAR imaging due to a high number of surfactant-associated marine bacteria is expected. This study has provided the basis for the biological importance for fine-scale synthetic aperture satellite imaging. Moreover, this new approach is expected to have applications in monitoring biological and chemical properties of the sea surface across the globe.

Satellite geodesy plays an important role in earth observation. This dissertation presents three applications of satellite geodesy in environmental and climate change. Three satellite geodesy techniques are used: high-precision Global Positioning System (GPS), the Gravity Recovery and Climate Experiment (GRACE) and Interferometric Synthetic Aperture Radar (InSAR). In the first study, I use coastal uplift observed by GPS to study the annual changes in mass loss of the Greenland ice sheet. The data show both spatial and temporal variations of coastal ice mass loss and suggest that a combination of warm atmospheric and oceanic condition drove these variations. In the second study, I use GRACE monthly gravity change estimates to constrain recent freshwater flux from Greenland. The data show that Arctic freshwater flux started to increase rapidly in the mid-late 1990s, coincident with a decrease in the formation of dense Labrador Sea Water, a key component of the deep southward return flow od the Atlantic Meridional Overturning Circulation (AMOC). Recent freshening of the polar oceans may be reducing formation of Labrador Sea Water and hence may be weakening the AMOC. In the third study, I use InSAR to monitor ground deformation caused by CO2 injection at an enhanced oil recovery site in west Texas. Carbon capture and storage can reduce CO2 emitted from power plants, and is a promising way to mitigate anthropogenic warming. From 2007 to 2011, ~24 million tons of CO2 were sequestered in this field, causing up to 10 MPa pressure buildup in a reservoir at depth, and surface uplift up to 10 cm. This study suggests that surface displacement observed by InSAR is a cost-effective way to estimate reservoir pressure change and monitor the fate of injected fluids at waste disposal and CO2 injection sites.

Le bruit de chatoiement (speckle) lié aux systèmes d'imagerie cohérente a des conséquences sur l'analyse et l'interprétation des images radar à synthèse d'ouverture (RSO). Pour corriger ce défaut, nous profitons de séries temporelles d'images RSO bien recalées. Nous améliorons le filtre adaptatif temporel non-local à l'aide de méthodes performantes de débruitage adaptatif et proposons un filtrage temporel adaptatif basé sur les patchs. Pour réduire le biais du débruitage, nous proposons une méthode originale, rapide et efficace de débruitage multitemporel. L'idée principale de l'approche proposée est d'utiliser l'image dite "de ratio", donnée par le rapport entre l'image et la moyenne temporelle de la pile. Cette image de ratio est plus facile à débruiter qu'une image isolée en raison de sa meilleure stationnarité. Par ailleurs, les structures fines stables dans le temps sont bien préservées grâce au moyennage multitemporel. Disposant d'images débruitées, nous proposons ensuite d'utiliser la méthode du rapport de vraisemblance généralisé simplifié pour détecter les zones de changement ainsi que l'amplitude des changements et les instants de changements intéressants dans de longues séries d'images correctement recalées. En utilisant le partitionnement spectral, on applique le rapport de vraisemblance généralisé simplifié pour caractériser les changements des séries temporelles. Nous visualisons les résultats de détection en utilisant l'échelle de couleur 'jet' et une colorisation HSV. Ces méthodes ont été appliquées avec succès pour étudier des zones cultivées, des zones urbaines, des régions portuaires et des changements dus à des inondations. / The inherent speckle which is attached to any coherent imaging system affects the analysis and interpretation of synthetic aperture radar (SAR) images. To take advantage of well-registered multi-temporal SAR images, we improve the adaptive nonlocal temporal filter with state-of-the-art adaptive denoising methods and propose a patch based adaptive temporal filter. To address the bias problem of the denoising results, we propose a fast and efficient multitemporal despeckling method. The key idea of the proposed approach is the use of the ratio image, provided by the ratio between an image and the temporal mean of the stack. This ratio image is easier to denoise than a single image thanks to its improved stationarity. Besides, temporally stable thin structures are well-preserved thanks to the multi-temporal mean. Without reference image, we propose to use a patch-based auto-covariance residual evaluation method to examine the residual image and look for possible remaining structural contents. With speckle reduction images, we propose to use simplified generalized likelihood ratio method to detect the change area, change magnitude and change times in long series of well-registered images. Based on spectral clustering, we apply the simplified generalized likelihood ratio to detect the time series change types. Then, jet colormap and HSV colorization may be used to vividly visualize the detection results. These methods have been successfully applied to monitor farmland area, urban area, harbor region, and flooding area changes.

<div>Synthetic Aperture Radar (SAR) is a technique to synthesize a large antenna array using the motion of a small antenna. When it comes to remote sensing, mapping, and change detection, SAR has been shown to be a good candidate by its ability to penetrate moisture and vegetation, and the avilibility of phase information for precise interferometric measurements [1] [13].</div><div><br></div><div><div>This study was motivated by the fact that satellite and high-altitude SAR has limited data availability in terms of temporal resolution and the cost of every measurement. It is believed that SAR systems mounted on smaller UAV or ground vehicles could provide a much better coverage of the target in time, and in dierent geometry.</div></div><div><br></div><div><div>We proposed a L-band SAR system based on Software-Defined Radio to be mounted on automotive platform. Novel motion estimation and compensation, as well as autofocusing techniques were developed to aid the SAR signal processing under much more demanding environment - the instability of radar platforms. It is expected this research development could bring down the cost of SAR being used as a remote sensing solution, and allow SAR system to be mounted on much smaller platforms by overcoming the instability of the track using novel signal processing methods, and eventually making SAR measurement available in places and times that was previously impossible.</div></div>

Le Synthetic Aperture Radar (SAR) aéroporté permet d’obtenir des images hautes résolutions, en compensant un déphasage lié au déplacement de l’avion. Il n’est cependant pas adapté à l’imagerie des cibles mobiles, celles-ci introduisant un déphasage supplémentaire, dépendant de leur vitesse et de leur accélération. En utilisant un système SAR multivoies, il est cependant possible de réaliser des traitements adaptés aux cibles mobiles, dont les principes sont proches du Space-Time Adaptive Processing (STAP). Le Synthetic Aperture Radar (SAR) aéroporté permet d’obtenir des images hautes résolutions, en compensant un déphasage lié au déplacement de l’avion. Il n’est cependant pas adapté à l’imagerie des cibles mobiles, celles-ci introduisant un déphasage supplémentaire, dépendant de leur vitesse et de leur accélération. En utilisant un système SAR multivoies, il est cependant possible de réaliser des traitements adaptés aux cibles mobiles, dont les principes sont proches du Space-Time Adaptive Processing (STAP). / Airborne Synthetic Aperture Radar (SAR) provides high-resolution images, by compensating a phase shift linked to the platform movement. However, this processing is not suited for imaging moving target, for they introduce an additional phase shift, depending on their velocity and acceleration. By using a multichannel SAR system, it is possible to correctly process moving targets. Such a processing is closely related to Space-Time Adaptive Processing (STAP) principles. Airborne Synthetic Aperture Radar (SAR) provides high-resolution images, by compensating a phase shift linked to the platform movement. However, this processing is not suited for imaging moving target, for they introduce an additional phase shift, depending on their velocity and acceleration. By using a multichannel SAR system, it is possible to correctly process moving targets. Such a processing is closely related to Space-Time Adaptive Processing (STAP) principles.