Remote sensing of marine oil slicks with hyperspectral camera and an extended database

Abstract

In the field of offshore oil slicks at the sea surface, radar or optical imagery can provide much useful information. Regarding optical imagery, detection relies on the differences between the reflectance of water alone and oil-covered water. As soon as the thickness of the oil layer is large enough to induce a spectral difference between the reflectance of water and oil-covered water, spectral indices are good candidates for detection. Thereafter, identification and quantification require extended optical and physical knowledge regarding oil properties. To this end, various products have been characterized in the laboratory. Hyperspectral reflectance and transmission measurements have been performed for various pure or emulsified products. This has enabled the definition of two theoretical thickness boundaries: a minimal thickness leading to a noticeable spectral attenuation effect on the reflectance between oil and water and a maximal thickness after which the spectral reflectance no longer evolves with thickness. For some products, these theoretical minimal and maximal thicknesses may not be realistic values for slicks at the sea surface, meaning that they will never be reached. However, they do give a thickness range in which thickness assessment could be performed with optical imagery and modeling. To go deeper into the understanding of oil behavior at sea, experimentation has also been done using a large tank filled with sea water, thus providing more realistic spectral signatures than in the laboratory. From this experiment, the thickness of a small amount of oil freely spread on a plane water surface has been assessed and compared with the boundaries established using the laboratory measurements. The database of spectral signatures built for product identification has been extended with the thickness boundaries and the experimental thicknesses for quantification purpose. This database has been successfully used to identify a product detected on an airborne hyperspectral image and to assess the corresponding oil slick volume, in the case of the NOFO2015 emulsion.