Combining Passive Hyperspectral Imagery and Active Fluorescence Laser Spectroscopy for Airborne Quantitative Mapping of Oil Slicks at Sea

Efficient observation means are required for supporting operational fight against oil pollutions at sea and recovering operations, including reliable choice and guidance of maritime and airborne fighting means. Among the suite of sensors available, the potential of airborne passive hyperspectral imagery and active fluorescence laser systems for remote sensing of oil spills at sea have been studied in the past. The potential of combining these two kinds of sensors for quantitative mapping of oil slicks at sea and for supporting the recovering operations is proposed for evaluation in that pilot project. Test flights have been carried out over a controlled oil pollution at sea, using an hyperspectral imager (CASI-2) and a Fluorescence Lidar System (FLS-AU) installed onboard a fixed-wing aircraft. The data processing chain is presented, including local absolute thickness estimation from lidar data, information extraction from hyperspectral CASI images data thanks to the inversion of a simple optical model of light scattering through a thin layer of oil in the water column, as well as data fusion from both sensors allowing high resolution thickness spatial distribution maps to be produced. Location, extents, and volume of the oil spilled are the main useful quantitative parameters estimated from the maps. The ways towards the design of an operational system including both passive and active airborne optical sensors for supporting recovering operations are presented. INTRODUCTION In May 2004, three real oil spills at sea have been performed during a three days campaign off the coasts of Britanny, France. The campaign, named DEPOL04, was carried out under the responsibility of the French Navy represented by the CEPPOL (“Commission d'Etudes Pratiques sur les Pollutions”) and of the French Customs, and managed by the CEDRE (“Centre de documentation de recherche et d'expérimentations sur les pollutions accidentelles des eaux”). The potential of airborne passive hyperspectral imagery (i) (ii) and active fluorescence laser systems (iii) (iv) (v) (vi) for remote sensing of oil spills at sea have been studied in the past. This controlled oil pollution offered the opportunity to test and develop an operational system using jointly an hyperspectral imager (CASI-2) and a Fluorescence Lidar System (FLS-AU) (vii) for oil slicks detection and quantitative mapping. That pilot project is conducted by ActiMar, a French SME specialized in opera1 http://www.actimar.fr © EARSeL and Warsaw University, Warsaw 2005. Proceedings of 4th EARSeL Workshop on Imaging Spectroscopy. New quality in environmental studies. Zagajewski B., Sobczak M., Wrzesień M., (eds) tional oceanography and high resolution remote sensing, in collaboration with GET/ENSTBretagne (TIME team, CNRS UMR 2872 TAMCIC), and is funded by the RITMER program of the French Ministry of Research under the name “DETECSUIV”. Radar satellites as well as airborne reconnaissance missions are used to obtain oil slicks localization (viii). Flight lines are prepared and integrated into a flight assistance system. CASI-2 and FLS-AU are installed onboard a fixedwing aircraft (Cessna 404). Using an optimal flight configuration, 10 to 40 km2 per hour can be recorded. The whole operational aspects of the campaign can be found in (ix). In order to extract the useful parameters from CASI-2 and FLS-AU data, a specific processing chain is developed. CASI data allow high spatial resolution (1 and 2 meters) slicks maps to be produced, and the polluted surface to be estimated, after illumination corrections and definition of specific colour spaces taking advantage of observed spectral phenomena. Two CASI-2 configurations have been tested, including 18 and 32 spectral bands. The data acquisition campaign has been completed with spectroscopic measurements on the slicks at sea, onboard a small infloatable boat. A simple optical model of light scattering in the water column is presented and is shown to be relevant for understanding the intra-slick spectral variability. In-lab calibration of fluorescence spectra acquired by FLS allows thickness to be locally estimated. Those measurements are used to “calibrate” the CASI data and to extend the estimation of thickness over all the CASI pixels. That data fusion procedure is shown to be consistent with the optical model over a polluted water area including a thin layer of oil, and allows very high spatial resolution (1 meter) thickness distribution maps to be computed. Those maps show the spatial distribution of the oil thickness and allow the volume of oil spilled to be estimated. In order to show all the data processing steps, a demonstrator has been developed, starting from raw CASI-2 and FLS-AU data integration and fusion up to the visualization of high spatial resolution oil thickness maps and oil pollution quantitative results. The potential and the limits of the whole approach are discussed, regarding the parameters estimation quality. Recommendations are made for the use of those combined sensors as a reliable observation mean for supporting operational recovering operations at sea. DATA PROCESSING CASI data processing chain a. Schematics The joint use of two sensors implies to consider the limitations of both. For a single CASI data acquisition, the flight altitude should be maximized in order to reach the maximum swath if the meteorological conditions are adequate. In the present case, the flight altitude is limited by the maximum flight altitude of the FLS-AU, which is equal to 500m (about 1500ft). The speed of the acquisition should be minimized in order to acquire the maximum amount of data. The minimum speed is however limited by the capabilities of the platform. Using a Cessna 404, this minimum speed is fixed at 100kt. to avoid turbulences. Considering those flight parameters, the CASI-2 configuration over its 400-1000nm spectral range is the following: number of spectral bands: 18 (equally distributed over the spectral range) spectral resolution: 30nm spatial resolution: 1m swath: 380m The whole processing chain of CASI dataset is shown on Figure 1.