A Survey on Detection of Oil-Spill in Satellite-Based Synthetic Aperture Radar (SAR) Images Using Neural Network

The use of satellite and airborne remote sensing has become standard practice for global oil spill monitoring. When oil leaks into the water, it is an immediate crisis. Monitoring oil spill on the sea surface is made possible using optical remote sensing. On the sea's surface, there is a moving oil leak. An essential part of preventing and mitigating oil spills is quick and effective monitoring of the location, size, and effects of the spill. Only a small sample of data may be collected due to the influence of cloud and weather, the limits of the satellite revisit duration, and other factors. The capacity to learn sample characteristics using a single supervised classifier in the case of small samples is constrained, which can not meet the needs of accurately monitor oil spill. By using neural network the oil spill regions has been extracted in radar image. In this paper we will be studying the survey of various papers related to oil spill detection.