Arctic sea ice is rapidly declining in extent, thickness, volume and age, with the majority of the decline in extent observed at the end of the melt season. Advanced melt is a thermodynamic regime and is characterized by the formation of melt ponds on the sea ice surface, which have a lower surface albedo (0.2-0.4) than the surrounding ice (0.5-0.7) allowing more shortwave radiation to enter the system. The loss of multiyear ice (MYI) may have a profound impact on the energy balance of the system because melt ponds on first-year ice (FYI) comprise up to 70% of the ice surface during advanced melt, compared to 40% on MYI. Despite the importance of advanced melt to the ocean-sea ice-atmosphere system, advanced melt and the extent to which winter conditions influence it remain poorly understood due to the highly dynamic nature of melt pond formation and evolution, and a lack of reliable observations during this time. In order to establish quantitative links between winter and subsequent advanced melt conditions, and assess the effects of scale and choice of aggregation features on the relationships, three data aggregation approaches at varied spatial scales were used to compare high resolution satellite GeoEye-1 optical images of melt pond covered sea ice to winter airborne laser scanner surface roughness and electromagnetic induction sea ice thickness measurements. The findings indicate that winter sea ice thickness has a strong association with melt pond fraction (fp) for FYI and MYI. FYI winter surface roughness is correlated with fp, whereas for MYI no association with fp was found. Satellite-borne synthetic aperture radar (SAR) data are heavily relied upon for sea ice observation; however, during advanced melt the reliability of observations is reduced. In preparation for the upcoming launch of the RADARSAT Constellation Mission (RCM), the Kolmogorov-Smirnov (KS) statistical test was used to assess the ability of simulated RCM parameters and grey level co-occurrence matrix (GLCM) derived texture features to discriminate between major ice types during winter and advanced melt, with a focus on advanced melt. RCM parameters with highest discrimination ability in conjunction with optimal GLCM texture features were used as input parameters for Support Vector Machine (SVM) supervised classifications. The results indicate that steep incidence angle RCM parameters show promise for distinguishing between FYI and MYI during advanced melt with an overall classification accuracy of 77.06%. The addition of GLCM texture parameters improved accuracy to 85.91%. This thesis provides valuable contributions to the growing body of literature on fp parameterization and SAR ice type discrimination during advanced melt. / Graduate / 2019-03-21

Les radars à synthèse d’ouverture (RSO) polarimétriques sont devenus incontournables dans le domaine de la télédétection, grâce à leur zone de couverture étendue, ainsi que leur capacité à acquérir des données dans n’importe quelles conditions atmosphériques de jour comme de nuit. Au cours des trois dernières décennies, plusieurs RSO polarimétriques ont été utilisés portant une variété de modes d’imagerie, tels que la polarisation unique, la polarisation double et également des modes dits pleinement polarimétriques. Grâce aux recherches récentes, d’autres modes alternatifs, tels que la polarisation hybride et compacte, ont été proposés pour les futures missions RSOs. Toutefois, un débat anime la communauté de la télédétection quant à l’utilité des modes alternatifs et quant au compromis entre la polarimétrie double et la polarimétrie totale. Cette thèse contribue à ce débat en analysant et comparant ces différents modes d’imagerie RSO dans une variété d’applications, avec un accent particulier sur la surveillance maritime (la détection des navires et de marées noires). Pour nos comparaisons, nous considérons un paramètre fondamental, appelé le degré de polarisation (DoP). Ce paramètre scalaire a été reconnu comme l’un des paramètres les plus pertinents pour caractériser les ondes électromagnétiques partiellement polarisées. A l’aide d’une analyse statistique détaillée sur les images polarimétriques RSO, nous proposons des estimateurs efficaces du DoP pour les systèmes d’imagerie cohérente et incohérente. Ainsi, nous étendons la notion de DoP aux différents modes d’imagerie polarimétrique hybride et compacte. Cette étude comparative réalisée dans différents contextes d’application dégage des propriétés permettant de guider le choix parmi les différents modes polarimétriques. Les expériences sont effectuées sur les données polarimétriques provenant du satellite Canadian RADARSAT-2 et le RSO aéroporté Américain AirSAR, couvrant divers types de terrains tels que l’urbain, la végétation et l’océan. Par ailleurs nous réalisons une étude détaillée sur les potentiels du DoP pour la détection et la reconnaissance des marées noires basée sur les acquisitions récentes d’UAVSAR, couvrant la catastrophe de Deepwater Horizon dans le golfe du Mexique. / Polarimetric Synthetic Aperture Radar (SAR) systems have become highly fruitful thanks to their wide area coverage and day and night all-weather capabilities. Several polarimetric SARs have been flown over the last few decades with a variety of polarimetric SAR imaging modes; traditional ones are linear singleand dual-pol modes. More sophisticated ones are full-pol modes. Other alternative modes, such as hybrid and compact dual-pol, have also been recently proposed for future SAR missions. The discussion is vivid across the remote sensing society about both the utility of such alternative modes, and also the trade-off between dual and full polarimetry. This thesis contributes to that discussion by analyzing and comparing different polarimetric SAR modes in a variety of geoscience applications, with a particular focus on maritime monitoring and surveillance. For our comparisons, we make use of a fundamental, physically related discriminator called the Degree of Polarization (DoP). This scalar parameter has been recognized as one of the most important parameters characterizing a partially polarized electromagnetic wave. Based on a detailed statistical analysis of polarimetric SAR images, we propose efficient estimators of the DoP for both coherent and in-coherent SAR systems. We extend the DoP concept to different hybrid and compact SAR modes and compare the achieved performance with different full-pol methods. We perform a detailed study of vessel detection and oil-spill recognition, based on linear and hybrid/compact dual-pol DoP, using recent data from the Deepwater Horizon oil-spill, acquired by the National Aeronautics and Space Administration (NASA)/Jet Propulsion Laboratory (JPL) Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR). Extensive experiments are also performed over various terrain types, such as urban, vegetation, and ocean, using the data acquired by the Canadian RADARSAT-2 and the NASA/JPL Airborne SAR (AirSAR) system.