Offshore oil slicks are significant for both the monitoring of marine spill accidents and the detection of marine oil resources.The use of remote sensing technology to detect the thickness of oil slicks is a major are...Offshore oil slicks are significant for both the monitoring of marine spill accidents and the detection of marine oil resources.The use of remote sensing technology to detect the thickness of oil slicks is a major area of research.The reflected light from oil slicks changes with the thickness of the oil.This is the theoretical basis of research on optical remote sensing of offshore oil slicks.A two-beam interference model that considers the offshore oil slick as a flat plate has been developed in this study.A quantitative remote sensing model which describes a series of processes that use oil slick thickness and reflectance as variables is established.The use of the Fresnel equation to analyze parameters in the model indicated that the key property of the quantitative relationship between the oil slick thickness and reflectance was ultimately the disappearance or extinction of the oil slick.This model has been tested and verified by data from offshore oil slick spectral response experiments.Results showed that the oil slick thickness remote sensing model can be theoretically analyzed and is efficient.The research indicated that the major cause of variations in the spectral response as a function of oil slick thickness was the different light-scattering characteristics.These characteristics can be used in remote sensing applications to identify the different types of offshore oil slicks.The theoretical interpretation of each parameter in this model led to the development of a look-up table of the model parameters which will improve the efficiency of future offshore oil slick remote sensing.展开更多
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 fr...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,pB0.01),26th band(R^(2)=0.93806,n=49,pB0.01),29th band(R^(2)=0.93288,n=49,pB0.01)].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.展开更多
基金supported by National Natural Science Foundation of China (Grant Nos. 40971186 and 41001196 )the Open Research Fund of Key Laboratory of Digital Earth,Center for Earth Observation and Digital Earth,Chinese Academy of Sciences (Grant No. 2010LDE007)
文摘Offshore oil slicks are significant for both the monitoring of marine spill accidents and the detection of marine oil resources.The use of remote sensing technology to detect the thickness of oil slicks is a major area of research.The reflected light from oil slicks changes with the thickness of the oil.This is the theoretical basis of research on optical remote sensing of offshore oil slicks.A two-beam interference model that considers the offshore oil slick as a flat plate has been developed in this study.A quantitative remote sensing model which describes a series of processes that use oil slick thickness and reflectance as variables is established.The use of the Fresnel equation to analyze parameters in the model indicated that the key property of the quantitative relationship between the oil slick thickness and reflectance was ultimately the disappearance or extinction of the oil slick.This model has been tested and verified by data from offshore oil slick spectral response experiments.Results showed that the oil slick thickness remote sensing model can be theoretically analyzed and is efficient.The research indicated that the major cause of variations in the spectral response as a function of oil slick thickness was the different light-scattering characteristics.These characteristics can be used in remote sensing applications to identify the different types of offshore oil slicks.The theoretical interpretation of each parameter in this model led to the development of a look-up table of the model parameters which will improve the efficiency of future offshore oil slick remote sensing.
基金supported by National Natural Science Foundation of China(Grant No.41001196)the Open Research Fund of Key Laboratory of Marine Spill Oil Identification and Damage Assessment Technology,SOA(Grant No.201212)the Open Research Fund of Key Laboratory of Digital Earth,Center for Earth Observation and Digital Earth,Chinese Academy of Sciences(Grant No.2010LDE007).
文摘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,pB0.01),26th band(R^(2)=0.93806,n=49,pB0.01),29th band(R^(2)=0.93288,n=49,pB0.01)].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.