4.6 Article

The remote sensing inversion theory of offshore oil slick thickness based on a two-beam interference model

Journal

SCIENCE CHINA-EARTH SCIENCES
Volume 54, Issue 5, Pages 678-685

Publisher

SCIENCE CHINA PRESS
DOI: 10.1007/s11430-010-4154-1

Keywords

two-beam interference; oil slick thickness; remote sensing; reflectance

Funding

  1. National Natural Science Foundation of China [40971186, 41001196]
  2. Key Laboratory of Digital Earth, Center for Earth Observation and Digital Earth, Chinese Academy of Sciences [2010LDE007]

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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.

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