Remote sensing technology is an essential link in the global monitoring of the ocean surface and radars are efficient sensors for detecting maritime pollution. When used operationally by authorities, a tradeoff must usually be made between the covered area and the quantity of information collected by the radar. To identify the most appropriate imaging mode, a methodology based on Receiver Operating Characteristic (ROC) curve analysis has been applied to an original dataset collected by two airborne systems operating at L-band, both characterized by a very low instrument noise floor. The dataset was acquired during controlled releases of mineral and vegetal oil at sea. Various polarization-dependent quantities are investigated and their ability to detect slickcovered area is assessed. A relative ordering of the main polarimetric parameters is reported in this paper. When the sensor has a sufficiently low noise floor, HV is recommended because it provides SAR Imagery for Detecting Sea Surface Slicks: Performance Assessment of Polarimetric Parameters the strongest slick-sea contrast. Otherwise VV is found to be the most relevant parameter for detecting slicks on the sea surface. Among all the investigated quad-polarimetric settings, no significant added-value compared to single-pol data was found. More specifically, it is demonstrated, by increasing the instrument noise level, that the studied polarimetric quantities which combine the four polarimetric channels have performances of detection mainly driven by the NESZ. This result, obtained by progressively adding noise to the raw SAR data, indicates that the polarimetric discrimination between clean sea and polluted area results mainly from the differentiated behavior between single-bounce scattering and noise.
Remote sensing techniques are commonly used by Oil and Gas companies to monitor hydrocarbon on the ocean surface. The interest lies not only in exploration but also in the monitoring of the maritime environment. Occurrence of natural seeps on the sea surface is a key indicator of the presence of mature source rock in the subsurface. These natural seeps, as well as the oil slicks, are commonly detected using radar sensors but the addition of optical imagery can deliver extra information such as thickness and composition of the detected oil, which is critical for both exploration purposes and efficient cleanup operations. Today, state-of-the-art approaches combine multiple data collected by optical and radar sensors embedded on-board different airborne and spaceborne platforms, to ensure wide spatial coverage and high frequency revisit time. Multi-wavelength imaging system may create a breakthrough in remote sensing applications, but it requires adapted processing techniques that need to be developed. To explore performances offered by multi-wavelength radar and optical sensors for oil slick monitoring, remote sensing data have been collected by SETHI (Système Expérimental de Télédection Hyperfréquence Imageur), the airborne system developed by ONERA (the French Aerospace Lab), during an oil spill cleanup exercise carried out in 2015 in the North Sea, Europe. The uniqueness of this dataset lies in its high spatial resolution, low noise level and quasi-simultaneous acquisitions of different part of the EM spectrum. Specific processing techniques have been developed to extract meaningful information associated with oil-covered sea surface. Analysis of this unique and rich dataset demonstrates that remote sensing imagery, collected in both optical and microwave domains, allows estimating slick surface properties such as the age of the emulsion released at sea, the spatial abundance of oil and the relative concentration of hydrocarbons remaining on the sea surface.
The increase in maritime traffic, particularly the transport of hazardous and noxious substances (HNSs), requires advanced methods of identification and characterization in environmental chemical spills. Knowledge about HNS monitoring using radar remote sensing is not as extensive as for oil spills; however, any progress on this issue would likely advance the monitoring of both chemical and oil-related incidents. To address the need for HNS monitoring, an experiment was conducted in May 2015 over the Mediterranean Sea during which controlled releases of HNS were imaged by a multifrequency radar system. The aim of this experiment was to establish a procedure for collecting evidence of illegal maritime pollution by noxious liquid substances using airborne radar sensors. In this paper, we demonstrate the ability of radar imagery to detect and characterize chemicals at sea. A normalized polarization difference parameter is introduced to quantify both the impacts of released product on the ocean surface and the relative concentration of the substance within the spill. We show that radar imagery can provide knowledge of the involved HNS. In particular, one can distinguish a product that forms a film on the top of the sea surface from another that mixes with seawater, the information that is critical for efficient cleanup operations.
Airborne remote sensing appears useful for monitoring oil spill accident or detecting illegal oil discharges. In that context, hyperspectral imagery in the SWIR range shows a high potential to describe oil spills. Indeed reflectance spectra of an oil emulsion layer show a wide variety of shapes according to its thickness or emulsion rate. Although based on laboratory measurements, it seems that these two parameters are insufficient to completely describe them. It appears that the way emulsion is performed leads to different reflectance spectra. Hence this paper will present a model which tends to simulate reflectance spectra of an oil emulsion layer over the sea water. To derive an analytical expression, some approximations and assumptions will be done. The result of this model shows high similarities with laboratory measurements and seems able to simulate most of the shapes of reflectance spectra. It also shows that a key parameter to define the shape of the reflectance spectra is the statistical distribution of water bubbles size in the emulsion. The description of this distribution function, if measurable, should be integrated into the methodology of elaboration of spectral libraries in the future.
The increase in maritime traffic, particularly the transport of hazardous and noxious substances (HNSs), requires advanced methods of identification and characterization in environmental chemical spills. Knowledge about HNS monitoring using radar remote sensing is not as extensive as for oil spills; however, any progress on this issue would likely advance the monitoring of both chemical and oil-related incidents. To address the need for HNS monitoring, an experiment was conducted in May 2015 over the Mediterranean Sea during which controlled releases of HNS were imaged by a multifrequency radar system. The aim of this experiment was to establish a procedure for collecting evidence of illegal maritime pollution by noxious liquid substances using airborne radar sensors. In this paper, we demonstrate the ability of radar imagery to detect and characterize chemicals at sea. A normalized polarization difference parameter is introduced to quantify both the impacts of released product on the ocean surface and the relative concentration of the substance within the spill. We show that radar imagery can provide knowledge of the involved HNS. In particular, one can distinguish a product that forms a film on the top of the sea surface from another that mixes with seawater, the information that is critical for efficient cleanup operations.
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