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The exploitation of microwave remote sensing for marine and maritime applications is a hot topic in the scientific community. The almost all-weather capability of acquired large-scale information on the oceans independently of illumination conditions is a key benefit ensured by microwave remote sensing. Among the several microwave remote sensing tools, it was demonstrated that polarimetric synthetic aperture radar (SAR) can provide valuable information on the oceans once proper modeling is available. Actually, there is a wide set of marine and marine applications that takes full benefits of the polarimetric information, including ship detection, sea oil pollution monitoring, sea iceberg detection and coastline extraction. Most of the polarimetric SAR-based algorithms that aim at detecting the target of interest needs to enhance the target-to-clutter ratio as much as possible in order to improve the detection accuracy. Nevertheless, the properties of sea surface polarimetric backscattering are strongly affected by both SAR imaging configuration (frequency, polarization, noise floor, incidence angle) and environmental conditions (sea state). In this study, one of the most widely and successfully used polarimetric features in the field of marine and maritime applications, namely the co-polarized phased difference, is considered. A sensitivity analysis is undertaken on a large set of polarimetric SAR measurements collected , under different frequency, incidence angle and noise floor, over sea surface characterized by different sea state conditions, that aim at assessing the influence of SAR acquisition parameters and environmental conditions on the CPD distribution. The polarimetric SAR dataset includes high-quality wide swath full-polarimetric airborne UAVSAR scenes, full-polarimetric satellite Alos-PalSAR 1 scenes, full-polarimetric satellite Radarsat-2 scenes and dual-polarimetric coherent HH+VV satellite TerraSAR-X scenes. This analysis could be of potential support in the design and development of SAR architectures/algorithms whose goal is to identify sea targets of interest.

Natural hydrocarbon seeps are broadly distributed across the Gulf of Mexico. Such seeps emit oil and gas into the water column, increasing the phytoplankton biomass and impacting regionally the productivity, carbon and nutrient cycling [1]. A fraction of this oil reaches to the sea surface and can be detected by SAR data. Although the ability of SAR data to detect oil features present in ocean's surface is wide exploited in the literature, it is known that the detection of those features is also a challenge. The SAR image interpretation became more difficult when the meteorological and oceanographically data are unavailable, the wind speed is too high or oil look-alikes are present (these features, e.g. low-wind conditions and algal blooms, can be misinterpreted as oil by conventional oil spill detector). In order to improve the SAR capability in detection oil seepages, the potential of the multi-polarization SAR data have been successfully exploited [2]. The latter have been shown to provide also a rough estimation of oil damping properties. In this study we address a contrast analysis exploiting a large time series of multi-polarization SAR measurements collected in the northwest of Gulf of Mexico (region where the presence of oil seepage is reported in the literature [3]). The time series consists of approximately 110 TerraSAR-X images acquired between June/2011 and April/2016. Our primary aims is to investigate the contrast between the oil seepages and the background using single-polarization channels by grouping the dataset according to incident angles and sea state conditions. The latter are available through in situ buoy measurements. The purpose of the first part of this study is to analysis the time variability of the oil/sea contrast and its spatial variability across the slicked area. In the second part we deal with multi-polarization techniques to analyze the oil seepage from a polarimetric viewpoint. Those analyses are undertaken exploiting polarimetric entropy, degree of polarization, co-polarized phase difference and also at addressing spatial/temporal variability of the damping properties of the surfactant. Even this case, the dataset is grouped according to incident angle and sea state condition. Finally, single-polarization results are critically contrasted with the multi-polarization ones to understand the benefits of inter channel phase to observe the sea oil seepage.