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|Title:||The Use of Ancillary Metocean Data for the Oil Spill Probability Assessment in SAR Images|
|Authors:||MUELLENHOFF OLIVER; BULGARELLI BARBARA; FERRARO DI SILVI E CASTIGLIONE GUIDO; TOPOUZELIS K.|
|Citation:||FRESENIUS ENVIRONMENTAL BULLETIN vol. 17 no. 9b|
|Publisher:||PARLAR SCIENTIFIC PUBLICATIONS (P S P)|
|Type:||Articles in periodicals and books|
|Abstract:||Accidental pollution at sea can be reduced but never completely eliminated, on the other side, deliberate illegal discharges from ships can indeed be reduced by the strict enforcement of existing regulations and the control, monitoring and surveillance of maritime traffic. Anyhow, operational oil discharges is a common practice and represents the main source of marine pollution from ships. Because of this situation the demand for efficient detection and mapping of oil pollution in the sea is growing. One of the key instruments to monitor and detect oil spills at sea are Synthetic Aperture Radar (SAR) systems. SAR systems are able to detect spills on the sea surface indirectly, because of the effect on the wind generated short gravity – capillary waves. The oil film damps these waves which are the primary backscatter agents of the radar signals. Unfortunately, oil slicks are not the only phenomena which can appear as a dark feature in a SAR image. The contrast between the spill and its surroundings depends on a number parameters like wind speed, wave height, and the amount and type of oil released. Under certain air/sea boundary layer conditions, other sea surface manifestations of natural origin may result to SAR expressions or false targets, similar to those due to an oil spill. They are usually referred to as look-alikes objects. The largest challenge in detection of oil spills in SAR images remains in the accurate discrimination between oil spills and look-alikes. Dark patches in SAR images can result from different sources like reduced wind speed or from reduced wind stress due to colder sea surface temperatures and other features. The knowledge of environmental conditions like wind, currents, precipitation and other concomitant marine and atmospheric phenomena like internal waves, upwelling, grease ice, algae blooms etc. as well as contextual information about slick position relative to surrounding objects (ships, maritime routes, rigs, platforms, natural seeps) of the past and at the time of the SAR acquisition is in many cases essential for the definition of the reliability of oil spill detections. The compilation of probability maps of occurrence of look-alike oil phenomena which are derived from ancillary metocean data and contextual information is to be used in the process of categorising the oil spill detections in SAR images. This paper describes a new approach in categorising the detected oil spills from the SAR image analysis in three different levels of probability based on metocean and contextual background information.|
|JRC Institute:||Space, Security and Migration|
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