Accuracy Improvement of the Radar Backscatter Simulation from Sea Surface Covered by Oil Slick Using Fetch- Dependent Waveheight Spectrum: Comparison with the 2007 Heibei Spirit Case in the Yellow Sea
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Title
- Accuracy Improvement of the Radar Backscatter Simulation from Sea Surface Covered by Oil Slick Using Fetch- Dependent Waveheight Spectrum: Comparison with the 2007 Heibei Spirit Case in the Yellow Sea
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Author(s)
- Kim, Tae-Ho; Yang, Chan-Su; Ouchi, Kazuo
- KIOST Author(s)
- Yang, Chan Su(양찬수)
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Alternative Author(s)
- 김태호; 양찬수
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Publication Year
- 2016-03
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Abstract
- In this paper, results are presented on the comparison of X-band radar backscattering coefficient (RBC) from an oilcovered sea surface that features the Elfouhaily and Durden-Vesecky waveheight spectra. The Durden-Vesecky spectrum applies to a fully-developed sea, while the Elfouhaily spectrum accounts for the fetch of arbitrary length. Using these two waveheight spectra, a one-dimensional random rough surface is simulated by the Monte Carlo method, and the method of moments (MoM) is applied to yield the RBC. Comparison of the results with TerraSAR-X synthetic aperture radar (SAR) data acquired over the coastal waters polluted by the Hebei Spirit oil tanker shows that the Elfouhaily spectrum yields better agreement than the Durden-Vesecky spectrum for the fully-developed sea, and that the fetch- dependent Elfouhaily spectrum improves the agreement with SAR data in comparison with the fetch- independent spectrum for the fully developed sea. A possible application to estimate the amount of spilled oil is also suggested.
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ISSN
- 1738-5261
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URI
- https://sciwatch.kiost.ac.kr/handle/2020.kiost/2224
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DOI
- 10.1007/s12601-016-0020-1
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Bibliographic Citation
- OCEAN SCIENCE JOURNAL, v.51, no.2, pp.235 - 249, 2016
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Publisher
- KOREA OCEAN RESEARCH DEVELOPMENT INST
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Subject
- SYNTHETIC-APERTURE RADAR; SPILL DETECTION; OCEAN SURFACE; CROSS-SECTION; MODEL; SCATTERING; FILMS; PERMITTIVITY; WAVES
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Keywords
- numerical scattering model; waveheight spectra; fetch length; oil slick; SAR
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Type
- Article
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Language
- English
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Document Type
- Article
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