A probabilistic method has been developed that distinguishes oil spills from other similar sea surface features in synthetic aperture radar (SAR) images. It considers both the radiometric and the geometric characteristics of the areas being tested. In order to minimize the operator intervention, it adopts automatic selection criteria to extract the potentially polluted areas from the images. The method has an a priori percentage of correct classification higher than 90% on the training dataset; the performance is confirmed on a different dataset of verified slicks. Some analyses have been conducted using images with different radiometric and geometric resolutions to test its suitability with SAR images different from European Remote Sensing (ERS) satellite ones. The system and its ability to detect and classify oil and non‐oil surface features are described. Starting from a set of verified oil spills detected offshore and over the coastline, the ability of SAR to reveal oil spills is tested by analysing w...

Automatic detection of oil spills from SAR images

Synthetic aperture radar (SAR) raw signal simulation is a powerful tool for design of oil slick detection and interpretation systems. In this paper, the ocean simulation issues are presented, and the main problems relating to the oil presence on the sea surface are treated. Attention is focused on the electromagnetic side of the problem, taking account of the sensor signatures, the dielectric, physical-chemical, and geometric nature of the oil slick, and the environmental conditions. The presented SAR simulator is based on an ocean model and an oil slick model. The former makes use of multiscale description of the ocean surface: the distributed surface model for the SAR-ocean interaction is considered by taking into account the nonlinear hydrodynamic effect for the water particle movement. The latter model implements a modification of the ocean spectrum, based on the Marangoni theory and accounting for the nonlinear wave interaction mechanism. However, the proposed SAR raw signal simulator is modular and flexible, thus allowing other possible physical models for modeling the oil slick effect over the ocean spectrum. Meaningful SAR simulation experiments are presented and discussed, elucidating the role of difference on pollutants, oil thickness, wind speed and direction, incident wavelength and angle and other radar parameters. Validation of the simulator is also presented by comparison with experimental data. A striking conclusion of the paper is that higher order moments (from the second on) of oil slick SAR image statistics are quite different compared to those pertinent to an equivalent wind speed decrease on the imaged area. This suggests a convenient way to define new appropriate oil slick signatures.

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SAR raw signal simulation of oil slicks in ocean environments

Relaxation effects in monolayers and their contribution to water wave damping

Adsorption and pollutant transport by marine aerosol

The results of point-by-point laboratory dampingvs. frequency measurements using mechanically generated ripples on a water surface covered by monomolecular film of oleic alcohol are discussed in terms of a theory that takes into account coupling of Laplace and Marangoni modes.

Ripple damping on water surface covered by a spreading film: Theory and experiment

The Marangoni wave, brought forth as a solution of the characteristic equation for ripple motion on an air-water interface covered by a film, is shown to possess a condition of minimum damping when the loss angle φ is negative, and nears −45°. Experimental evidence of this phenomenon was observed in the waving of a tank filled with distilled water and covered with a film of oleic alcohol.

R. Cini

Papers

The Marangoni wave in ripples on an air-water interface covered by a spreading film