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One of the objectives of the NAOMI (New Advanced Observation Method Integration) research project, fruit of a
partnership between Total and ONERA, is to work on the detection, the quantification and the characterization of
offshore hydrocarbon at the sea surface using airborne remote sensing. In this framework, work has been done to
characterize the spectral signature of hydrocarbons in lab in order to build a database of oil spectral signatures. The main
objective of this database is to provide spectral libraries for data processing algorithms to be applied to airborne VNIRSWIR
hyperspectral images.
A campaign run by the NOFO institute (Norwegian Clean Seas Association for Operating Companies) took place in
2015 to test anti-pollution equipment. During this campaign, several hydrocarbon products, including an oil emulsion,
were released into the sea, off the Norwegian coast. The NOFO team allowed the NAOMI project to acquire data over
the resulting oil slicks using the SETHI system, which is an airborne remote sensing imaging system developed by
ONERA. SETHI integrates a new generation of optoelectronic and radar payloads and can operate over a wide range of
frequency bands. SETHI is a pod-based system operating onboard a Falcon 20 Dassault aircraft, which is owned by
AvDEF. For these experiments, imaging sensors were constituted by 2 synthetic aperture radar (SAR), working at X and
L bands in a full polarimetric mode (HH, HV, VH, VV) and 2 HySpex hyperspectral cameras working in the VNIR (0,4
to 1 μm) and SWIR (1 to 2,5 μm) spectral ranges.
A sample of the oil emulsion that was used during the campaign was sent to our laboratory for analysis. Measurements
of its transmission and of its reflectance in the VNIR and SWIR spectral domains have been performed at ONERA with
a Perkin Elmer spectroradiometer and a spectrogoniometer. Several samples of the oil emulsion were prepared in order
to measure spectral variations according to oil thickness, illumination angle and aging. These measurements have been
used to build spectral libraries. Spectral matching techniques, relying on these libraries have been applied to the airborne
hyperspectral acquisitions. These data processing approaches enable to characterize the oil emulsion by estimating the
properties taken into account to build the spectral library, thus going further than unsupervised spectral indices that are
able to detect the presence of oil.
The paper will describe the airborne hyperspectral data, the measurements performed in the laboratory, and the
processing of the optical images with spectral indices for oil detection and with spectral matching techniques for oil
characterization. Furthermore, the issue of mixed oil-water pixels in the hyperspectral images due to limited spatial
resolution will be addressed by estimating the areal fraction of each.
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