An analysis of the radar backscatter from oil-covered sea surfaces using moment method and Monte-Carlo simulation: preliminary results
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Title
- An analysis of the radar backscatter from oil-covered sea surfaces using moment method and Monte-Carlo simulation: preliminary results
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Author(s)
- Yang, Chan-Su; Park, Seong-Min; Oh, Yisok; Ouchi, Kazuo
- KIOST Author(s)
- Yang, Chan Su(양찬수)
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Alternative Author(s)
- 양찬수
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Publication Year
- 2013-01
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Abstract
- An analysis of the radar backscattering from the ocean surface covered by oil spill is presented using a microwave scattering model and Monte-Carlo simulation. In the analysis, a one-dimensional rough sea surface is numerically generated with an ocean waveheight spectrum for a given wind velocity. A two-layered medium is then generated by adding a thin oil layer on the simulated rough sea surface. The electric fields backscattered from the sea surface with two-layered medium are computed with the method of moments (MoM), and the backscattering coefficients are statistically obtained with N independent samples for each oil-spilled surface using the Monte-Carlo technique for various conditions of surface roughness, oil-layer thickness, frequency, polarization and incidence angle. The numerical simulation results are compared with theoretical models for clean sea surfaces and SAR images of an oil-spilled sea surface caused by the Hebei (Hebei province, China) Spirit oil tanker in 2007. Further, conditions for better oil spill extraction are sought by the numerical simulation on the effects of wind speed and oil-layer thickness at different incidence angles on the backscattering coefficients.
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ISSN
- 0253-505X
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URI
- https://sciwatch.kiost.ac.kr/handle/2020.kiost/3282
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DOI
- 10.1007/s13131-013-0267-7
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Bibliographic Citation
- ACTA OCEANOLOGICA SINICA, v.32, no.1, pp.59 - 67, 2013
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Publisher
- SPRINGER
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Subject
- SPILL DETECTION; OCEAN SURFACE; WAVE SPECTRA; SAR; SATELLITE; SLICKS; FILMS
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Keywords
- method of moments; Monte-Carlo technique; oil spills; backscattering coefficient
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Type
- Article
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Language
- English
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Document Type
- Article
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