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Mapping ice and open water in ocean bodies is important for numerous purposes including environmental analysis and ship navigation. The Canadian Ice Service (CIS) currently has several expert ice analysts manually generate ice maps on a daily basis. The CIS would like to augment their current process with an automated ice-water discrimination algorithm capable of operating on dual-pol synthetic aperture radar (SAR) images produced by RADARSAT-2. Automated methods can provide mappings in larger volumes, with more consistency, and in finer resolutions that are otherwise impractical to generate. We have developed such an automated ice-water discrimination system called MAGIC. The algorithm first classifies the HV scene using the glocal method, a hierarchical region-based classification method. The glocal method incorporates spatial context information into the classification model using a modified watershed segmentation and a previously developed MRF classification algorithm called IRGS. Second, a pixel-based support vector machine (SVM) using a nonlinear RBF kernel classification is performed exploiting SAR grey-level co-occurrence matrix (GLCM) texture and backscatter features. Finally, the IRGS and SVM classification results are combined using the IRGS approach but with a modified energy function to accommodate the SVM pixel-based information. The combined classifier was tested on 61 ground truthed dual-pol RADARSAT-2 scenes of the Beaufort Sea containing a variety of ice types and water patterns across melt, summer, and freeze-up periods. The average leave-one-out classification accuracy with respect to these ground truths is 95.8% and MAGIC attains an accuracy of 90% or above on 88% of the scenes. The MAGIC system is now under consideration by CIS for operational use.

Scene classification is performed on countless remote sensing images in support of operational activities. Automating this process is preferable since manual pixel-level classification is not feasible for large scenes. However, developing such an algorithmic solution is a challenging task due to both scene complexities and sensor limitations. The objective is to develop efficient and accurate unsupervised methods for classification (i.e., assigning each pixel to an appropriate generic class) and for labeling (i.e., properly assigning true labels to each class). Unique from traditional approaches, the proposed bootstrap approach achieves classification and labeling without training data. Here, the full image is partitioned into subimages and the true classes found in each subimage are provided by the user. After these steps, the rest of the process is automatic. Each subimage is individually classified into regions and then using the joint information from all subimages and regions the optimal configuration of labels is found based on an objective function based on a Markov random field (MRF) model. The bootstrap approach has been successfully demonstrated with SAR sea-ice and lake ice images which represent challenging scenes used operationally for ship navigation, climate study, and ice fraction estimation. Accuracy assessment is based on evaluation conducted by third party experts. The bootstrap method is also demonstrated using synthetic and natural images. The impact of this technique is a repeatable and accurate methodology that generates classified maps faster than the standard methodology.

A proper time-frequency transform technique suppresses the blurring and smearing effect of the time-varying Doppler shift on the target image. The conventional target imaging method uses the Fourier transform for extracting the Doppler shift from the received radar pulse. Since the Doppler shift is timevarying for rotating targets, the constructed images will be degraded. In this thesis, the Doppler shift information required for the Range-Doppler image of the target is extracted by using high resolution time-frequency transform techniques. The Wigner-Ville Distribution and the Adaptive Gabor Representation with the Coarse-to-Fine and the Matching Pursuit Search Algorithms are examined techniques for the target imaging system. The modified Matching Pursuit Algorithm, the Matching Pursuit with Reduced Dictionary is proposed which decreases the signal processing time required by the Adaptive Gabor Representation. The Hybrid Matching Pursuit Search Algorithm is also introduced in this thesis work and the Coarse-to-Fine Algorithm and the Matching Pursuit Algorithm are combined for obtaining better representation quality of a signal in the time-frequency domain. The stated techniques are applied on to the sample signals and compared with each other. The application of these techniques in the target imaging system is also performed for the simulated aircrafts.

L'Indonésie, l’une de plus grands archipels, a été menacé avec la pollution provenant de la marée noire. Le gouvernement d’Indonésie en coopération avec le gouvernement Français a développé un système d'observation de l'océan par satellite afin de supporter de développement durable. Ce système est intégré dans les systèmes d'océanographie opérationnelle dans le cadre du projet de développement des infrastructures de l'océanographie spatiale (INDESO). Le contexte de cette thèse est dans le cadre du projet INDESO notamment dans applications d’INDESO pour suivre des déversements de pétrole dans les mers d’Indonésie. Dans ce contexte,cette thèse propose de nouvelles méthodologies et analyses. Cette thèse comportait deux contributions principales. La première contribution est sur la récupération des paramètres de dérive des déversements d'hydrocarbures à partir d'une analyse conjointe des observations SAR (Synthetic Aperture Radar) et des résultats d'un modèle de transport de déversement de pétrole. Dans cette première partie, nous estimons les paramètres de dérive de pétrole. On a exploité un modèle de transport de déversement de pétrole lagrangien,de sorte que la dérive simulée de déversement d'hydrocarbures modèles puisse correspondre à l'observation de satellite. Pour confirmer l'origine du déversement de pétrole détecté à une date donnée par une observation de SAR, nous avons effectué des simulations avec différentes dates de début de fuite, duré de fuite et différentes valeurs de pondération deux facteurs dominants i.e. vent et courant. Nous avons développé une nouvelle méthode pour l'assimilation de ces paramètres de fuite de pétrole à comparer avec d'une détection dérivée d'un déversement d'hydrocarbures. Nous avons appliqué la méthodologie proposée sur le plus grand accident en Indonésie, l'accident de Montara. La deuxième contribution est l'évaluation globale du risque de déversement d'hydrocarbures en Indonésie. Nous sommes concentrés sur la zone de gestion des pêches de l'Indonésie. Dans cette analyse, nous avons proposé une méthodologie qui considère le déversement de pétrole, qui a des sources différentes et leurs impacts à l'environnement, mais aussi sur les perspectives sociales et économiques. Pour l'évaluation de la vulnérabilité des zones marines protégées, nous avons également exploité le modèle de 2D lagrangien. L'accent mis sur les zones de gestion des pêches (FMA) afin de fournir une analyse synoptique sur l'ensemble du territoire maritime d’Indonésie. Chaque FMA présente les caractéristiques spécifiques des paramètres environnementaux etsocio-économiques. Nous avons évalué le risque de déversement d'hydrocarbures dans chaque zone de gestion sur la base de tous ces facteurs. Le résultat de cette étude peut être utilisé dans la planification d'une action pour réduire les impacts négatifs du déversement d'hydrocarbures. / Indonesia as the biggest archipelago has a major threat coming from oil spill. Due to the increasing concerns of environment protection for sustainable development, the government of Indonesia in cooperation with government of France developed an ocean observation system with one of its pilot applications is oil spills monitoring. This system is integrated in the operational oceanography systems within the project of Infrastructure Development of Space Oceanography (INDESO). The context of this thesis is in the frame of INDESO project particularly in the monitoring of oil spill in the Indonesian seas. Within the context above, this thesis propose new methodologies and analyses. This thesis involved two main contributions. The first contribution addressed the retrieval of oil spill drift parameters from a joint analysis of SAR observations of an oil spill and of outputs of a Lagrangian oil spill transport model. In this first part, we estimate oil spill drift parameters. The proposed framework exploited a Lagrangian oil spill transport model such that the simulated oil spill drift could match a SAR-based observation of an oil spill. In the considered 2D Lagrangian model there were two dominant factors, i.e. wind and surface current. To confirm the origin of the oil spill detected on a given date through a SAR observation, we performed simulations with various leakage starting dates, leakage durations, and different values of wind and current weighing coefficients. We developed a novel framework for the assimilation of these oil leakage parameters from a SAR-derived detection of an oil spill. We applied the proposed methodology on the most famous oil spill accident in Indonesia, the Montara case. The second contribution was the global assessment of oil spill risk inIndonesia. We focused on the 11 Indonesia Fisheries Management Area to support the sustainability development of marine and fisheries. In this analysis we proposed methodology that considered the oil spillfrom different source and their impacts not only to the environment, but also from social and economic perspectives. For the assessment of vulnerability of Marine Protected Areas to oil spill pollution, we also exploited the oil spill trajectory model. The focus was given to Fisheries Management Areas as a means to provide synoptic analysis over theentire Indonesian maritime territory. Using different information from many institutional reports, we collected and analyzed the potential source of oil spill in each FMA. Each FMA has specific characteristics in terms environmental and socioeconomic features. We assessed the oil spill risk in each FMA based on all these factors. The result of this study can be used in the mitigation planning to reduce the negative impacts of oil spill.

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.