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
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.
Radar and optical sensors are operationally used by authorities or petroleum companies for detecting and characterizing maritime pollution. The interest lies not only in exploration but also in the monitoring of the maritime environment. Occurrence of natural seeps on the sea surface is a key indicator of the presence of mature source rock in the subsurface. These natural seeps, as well as the oil slicks, are commonly detected using radar sensors but the addition of optical imagery can deliver extra information such as the oil real fraction, which is critical for both exploration purposes and efficient cleanup operations. Today state-of-the-art approaches combine multiple data collected by optical and radar sensors embedded on-board different airborne and spaceborne platforms, to ensure wide spatial coverage and high frequency revisit time. Multi-wavelength imaging system may create a breakthrough in remote sensing applications, but it requires adapted processing techniques that need to be developed. To explore performances offered by multi-wavelength radar and optical sensors for oil slick monitoring, remote sensing data have been collected by SETHI, the airborne system developed by ONERA, during an oil spill cleanup exercise carried out in 2015 in the North Sea, Europe. The uniqueness of this data set lies in its high spatial resolution, low noise level and quasi-simultaneous acquisitions of different part of the electromagnetic spectrum. Specific processing techniques have been developed in order to extract meaningful information associated with oil-covered sea surface. Analysis of this unique and rich dataset demonstrates that remote sensing imagery, collected in both optical and microwave domains, allows to estimate slick surface properties such as the spatial abundance of oil and the relative concentration of hydrocarbons on the sea surface.
Maritime pollution by chemical products occurs at much lower frequency than spills of oil, however the consequences of a chemical spill can be more wide-reaching than those of oil. While detection and characterization of hydrocarbons have been the subject of numerous studies, detection of other chemical products at sea using remote sensing has been little studied and is still an open subject of research. To address this knowledge gap, an experiment was conducted in May 2015 over the Mediterranean Sea during which controlled releases of hazardous and noxious substances were imaged by an airborne SAR sensor at X- and L-band simultaneously. In this paper we discuss the experimental procedure and report the main results from the airborne radar imaging campaign.
Airborne remote sensing appears useful for monitoring oil spill accident or detecting illegal oil discharges. In that context, hyperspectral imagery in the SWIR range shows a high potential to describe oil spills. Indeed reflectance spectra of an oil emulsion layer show a wide variety of shapes according to its thickness or emulsion rate. Although based on laboratory measurements, it seems that these two parameters are insufficient to completely describe them. It appears that the way emulsion is performed leads to different reflectance spectra. Hence this paper will present a model which tends to simulate reflectance spectra of an oil emulsion layer over the sea water. To derive an analytical expression, some approximations and assumptions will be done. The result of this model shows high similarities with laboratory measurements and seems able to simulate most of the shapes of reflectance spectra. It also shows that a key parameter to define the shape of the reflectance spectra is the statistical distribution of water bubbles size in the emulsion. The description of this distribution function, if measurable, should be integrated into the methodology of elaboration of spectral libraries in the future.