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This work focuses on the contribution of modelling for the interpretation of multi- or hyperspectral optical images for the detection, characterisation and quantification of oil spills. Many parameters contribute to the spectral signature of an oil layer on the sea surface: the optical properties of the water column and of the oil, the film thickness, the surface roughness, the atmospheric radiance reaching the surface (direct and diffuse components), the geometry of observation and illumination. The number of these contributors and their combinations make the analysis of the spectral variability of oil signatures at the sea surface complex. Modelling approaches allow us to consider all those parameters and can then provide useful information to improve the interpretation of optical images. The model presented in this paper simulates the radiance of an oil layer from visible to short wave infrared spectral domains, taking into account all the above-mentioned parameters. The damping influence of the oil layer on sea surface waves is also considered. Comparisons of the simulations with in situ measurements shows a good overall agreement despite the lack of knowledge of some input parameters of the model. In combination with laboratory and in-the-field measurements, the model is then used to assess the expected contrast between water and oil and to estimate oil slick volume.

A sensor's spatial resolution has traditionally been a difficult concept to define, but all would agree that it is inextricably linked to the Ground Sampling Distance (GSD) and Instantaneous Field of View (IFOV) of an imaging sensor system. As a measure of the geospatial quality of imagery, the Modulation Transfer Function (MTF) of the system is often used along with the signal-to-noise ratio (SNR). However, their calculation is not fully standardized. Further, consistent measurements and comparisons are often hard to obtain. Therefore, in the Infrared and Visible Optical Sensors (IVOS) subgroup of the Working Group on Calibration Validation (WGCV) of the Committee for Earth Observation Satellites (CEOS), a team from various countries and professional entities who are involved in MTF measurement was established to address the issue of on-orbit MTF measurements and comparisons. As a first step, a blind comparison of MTF measurements based on the slanted edge approach has been undertaken. A set of both artificial and actual satellite edge images was developed and a first comparison of processing results was generated. In all, seven organizations contributed to the experiment and several significant results were generated in 2016. No single participant produced the best results for all test images as measured by either the closest to the mean result, or closest to the truth for the synthetic test images. In addition, close estimates of the MTF value at Nyquist did not ensure the accuracy of other MTF values at other spatial frequencies. Some algorithm results showed that the accuracy of their estimates depended upon the type of MTF curve that was being analyzed. After the initial analysis, participants were allowed to modify their methodology and reprocess the test images since, in several cases, the results contained errors. Results from the second iteration, in 2017, verified that the anomalies in the experiment's first iteration were due to errors in either coding or methodology, or both. One organization implemented a third trial to fix software errors. This emphasizes the importance of fully understanding both methodology and implementation, in order to ensure accurate and repeatable results. To extend this comparison study, a reference data set, which is composed of edge images and corresponding MTF curves, will be built. A broader audience will be able to access the edge images through the CEOS CalVal Portal (http://calvalportal.ceos.org/). This paper, which is associated with the reference data set, can serve as a new tool to either implement or check, or both, the MTF measurement that relies on the slanted edge method.

Remote sensing techniques are commonly used by Oil and Gas companies to monitor hydrocarbon on the ocean surface. 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 thickness and composition of the detected oil, 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 (Système Expérimental de Télédection Hyperfréquence Imageur), the airborne system developed by ONERA (the French Aerospace Lab), during an oil spill cleanup exercise carried out in 2015 in the North Sea, Europe. The uniqueness of this dataset lies in its high spatial resolution, low noise level and quasi-simultaneous acquisitions of different part of the EM spectrum. Specific processing techniques have been developed 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 estimating slick surface properties such as the age of the emulsion released at sea, the spatial abundance of oil and the relative concentration of hydrocarbons remaining on the sea surface., Competing Interests: The authors declare no conflict of interest.

In the earth observation domain, two classes of sensors may be distinguished: a class for which sensor performances are driven by radiometric accuracy of the images and a class for which sensor performances are driven by spatial resolution. In this latter case, as spatial resolution depends on the triplet constituted by the Ground Sampling Distance (GSD), Modulation Transfer Function (MTF), and Signal to Noise Ratio (SNR), refocusing, acting as an MTF improvement, is very important. Refocusing is not difficult by itself as far as the on-board mechanism is reliable. The difficulty is on the defocus assessment side. Some methods such as those used for the SPOT family rely on the ability of the satellite to image the same landscape with two focusing positions. This can be done with a bi-sensor configuration, with adequate focal plane, or with the satellite agility. A new generation of refocusing mechanism will be taken aboard Pleiades. As the speed of this mechanism will be much slower than the speed of the older generation, it won't be possible, despite the agility of the satellite, to image the same landscape with two focusing positions on the same orbit. That's why methods relying on MTF measurement with edge method have been studied. This paper describes the methods and the work done to assess the defocus measurement accuracy in the Pleiades context.

The edge method is a widely used way to assess the on-orbit Modulation Transfer Function (MTF). Since good quality is required for the edge, the higher the spatial resolution, the better the results are. In this case, an artificial target can be built and used to ensure a good edge quality. For moderate spatial resolutions, only natural targets are available. Hence the edge quality is unknown and generally rather poor. Improvements of the method have been researched in order to compensate for the poor quality of natural edges. This has been done through the use of symmetry and/or a transfer function model, which enables the elimination of noise. This has also been used for artificial target. In this case, the use of the model overcomes the incomplete sampling when the target is too small or gives the opportunity to assess the defocus of the sensor. This paper begins with a recall of the method followed by a presentation of the changes relying on transfer function parametric model. The transfer function model and the process corresponding to the changes are described. Applications of these changes for several satellites of the French spatial agency are presented: for SPOT 1, it enables to assess XS MTF with natural edges, for SPOT 5, it enables to use the Salon-de-Provence artificial target for MTF assessment in the HM mode, and for the foreseen Pleiades, it enables to estimate the defocus.