Neural Network Algorithm for Oil Spill Automatic Detection from Multi Mode Radarsat-1 Sar Satellite Data
نویسنده
چکیده
Abstract: The main objective of this work is to utilize automatic detection algorithm for oil spill pixels in multimode (Standard beam S2, Wide beam W1 and fine beam F1) RADARSAT-1 SAR satellite data and ENVISAT ASAR that were acquired in the Malacca Straits, and Gulf of Mexico, respectively. In doing so, neural network (NN) algorithm is implemented for oil spill detection. The results show that NN is the best indicator for oil spill detection as it can discriminate oil spill from its surrounding such as look-alikes, sea surface and land. The NN shows higher performance in automatic detection of oil spill in RADARSAT-1 SAR data with standard deviation of 0.12. In conclusion, NN algorithm is an appropriate algorithm for oil spill automatic detection and W1 beam mode is appropriate for oil spill and look-alikes discrimination and detection. It can also said that ASA-APP-1P imagery with HV polarization provided better detection of oil spill using neural network algorithm.
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