Oil spill detection and prediction in the NW Mediterranean Sea: new multifractal methods for SAR analysis
Tipus de documentComunicació de congrés
Condicions d'accésAccés restringit per política de l'editorial
The oil pollution of Gulf of Lion in the NW Mediterranean has been studied with SAR images during the period 1999 -2005. We have analyzed these SAR images with respect to other surface features such as wind, river plumes, eddies and convergence areas. Some results of our statistical analysis are presented showing that the NW Mediterranean is most polluted along the main ship traffic routes, but comparatively less that near other routes in the Indic and the Pacific. The oils spill index is higher than one. The sizes of the detected oil spills vary over a large range, and if the statistics of the largest accidents are also considered on a longer timescale, we show that Zipf's Law, relating the frequency and the size of the spill in a hyperbolic fashion is applicable. Advanced image analysis techniques, such as the calculation of the multi-fractal dimensions of the observed SAR signatures, have been applied to distinguish between natural slicks and antropogenic spills. Fractal dimensions can also be used to predict the time of release of the spill, non-dimensionalised with local turbulent dissipation. The multi-scale appearance and the topological structure of the slicks and spills may also be used as a useful measure of the diffusivity, yielding additional information which in turn may improve automated detection algorithms and be used in numerical models.
CitacióRedondo, J.; Platonov, A. Oil spill detection and prediction in the NW Mediterranean Sea: new multifractal methods for SAR analysis. A: European Conference on Computational Fluid Dynamics. "Proceedings of the V European Conference on Computational Fluid Dynamics ECCOMAS CFD 2010 J. C. F. Pereira, A. Sequeira and J. M. C. Pereira (Eds) Lisbon, Portugal,14-17 June 2010". Lisbon: 2010, p. 1-12.
Versió de l'editorhttp://upcommons.upc.edu/e-prints/urlFiles?idDrac=9591409