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• W2078449685 abstract "Abstract Determining oil slick thickness plays an important role in assessing oil spill volume and its environmental impacts on the ocean. In this study, we used a Hyperion image of an oil spill accident area and seawater and fresh crude oil samples collected in the Bohai Sea of China. A well-controlled laboratory experiment was designed to simulate spectral responses to different oil slick thicknesses. Spectral resampling and normalization methods were used to reduce the differences in spectral reflectances between the experimental background seawater sample and real background seawater. Fitting the analysis with laboratory experimental data results showed a linear relationship between normalized oil slick reflectance and normalized oil slick thickness [20th band (R 2=0.92938, n=49, p<0.01), 26th band (R 2=0.93806, n=49, p<0.01), 29th band (R 2=0.93288, n=49, p<0.01)]. By using these statistical models, we successfully determined the normalized oil slick thickness with the Hyperion image. Our results indicate that hyperspectral remote sensing technology is an effective method to monitor oil spills on water. The spectral ranges of visible green and red light were the optimal bands for estimating oil slick thickness in case 2 water. The high, stabilized spectral reflectance of background seawater will be helpful in oil slick thickness inversion." @default.
• W2078449685 created "2016-06-24" @default.
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• W2078449685 date "2013-01-01" @default.
• W2078449685 modified "2023-10-18" @default.
• W2078449685 title "Determining oil slick thickness using hyperspectral remote sensing in the Bohai Sea of China" @default.
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• W2078449685 doi "https://doi.org/10.1080/17538947.2012.695404" @default.
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