Neural networks for the oil spill detection using ERS-SAR data

A neural network approach for semi-automatic detection of oil spills in ERS-SAR imagery is presented. The network input is a vector containing the values of a set of features, previously calculated by using dedicated routines, characterizing the oil spill candidate either from the point of view of its geometry or of its physical behaviour. The algorithm classification performance has been evaluated on a data set containing verified examples of oil spill and look-alike.