28 September 2009 New pattern recognition methods for identifying oil spills from satellite remote sensing data
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The early detection and identification of oil spills are critical prerequisites for performing cost-effective maritime salvage operations. This paper presents a new approach for distinguishing oil spills that are produced by stationary offshore sources, during their early phase of occurrence. The results were reached after analyzing over 100 images of satellite remote sensing data that were produced by either active microwave sensors like the Synthetic Aperture Radar (SAR) sensors or passive optical sensors like the Moderate Resolution Imaging Spectroradiometer (MODIS). The laws of conservation of mass and momentum that describe the dynamics of an oil spill over the water surface, were used for the development of a new detection algorithm that encompasses a parallel concept of shape conservation. The validity of this new empirical algorithm depends upon a number of assumptions that were made about the oil viscosity, temperature, water currents, wind speeds and the spills' spatial extent and duration. It can also be shown that unique texture differences can be revealed between an oil spill and other look-alikes' features like, for example, wind patterns, rain cells and algal mats by applying edge filtering operations on the patches that are under investigation, and therefore the reduction of false positives. The work presented here may have profound implications on future studies that examine the use of automatic recognitions methods, that are based on pattern and texture analysis. The results may also lead to new methodologies by which the dispersion and trajectory models of oil spills can be studied in new detail and ultimately used in environmental impact assessment operations.
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Fahad Alawadi, Fahad Alawadi, } "New pattern recognition methods for identifying oil spills from satellite remote sensing data", Proc. SPIE 7477, Image and Signal Processing for Remote Sensing XV, 74770X (28 September 2009); doi: 10.1117/12.828845; https://doi.org/10.1117/12.828845

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