Marine oil slicks detection using spaceborne and airborne SAR data.

Naval transportations have grown exponentially in the past few years' and the quantity of illegitimate oil discharges in the oceans has developed with the volume of traffic imposing a severe threat to marine lives and ecosystem. Oil spills dampen the capillary wave's effect hence create a dark signature on satellite image which is often called a dark object/matter that can be easily detected by SAR sensors. This study reviews the potential of quad-pol and hybrid-pol datasets in detecting oil spills. The data used for this study is the UAVSAR quad-pol and RISAT-1 hybrid/compact-pol dataset. These datasets were acquired during an oil spill experiment named the Norwegian Radar oil Spill Experiment (NORSE2015) which was carried out in the North Sea in June 2015. Basic pre-processing and decomposition modeling techniques namely Freeman and Durden, Van-Zyl, Yamaguchi, and Multiple-Component Scattering Model (MCSM) were applied on UAVSAR dataset, while Raney and Compact-Pol decompositions were applied to RISAT-1 dataset to know different surface backscattering behavior shown by the sea and oil patches. It was observed that Van-Zyl decomposition for UAVSAR and Compact-Pol decomposition for the RISAT-1 dataset gave the most suitable outcome based on the separability analysis to distinguish between oil and water. Two classification techniques Wishart Supervised Classifier (WSC) and Support Vector Machine (SVM) classifications were implemented on decomposed scattering elements of Van-Zyl and Compact-Pol. Radial Basis Function (RBF) kernel parameter values in SVM were used to precisely classify the oil patches from seawater. All the applied decomposition experiments provide good separability between water and oil. Later on, WSC and SVM had been used to finally classify both the dataset outputs. WSC had given better results with an accuracy of 83% for UAVSAR and 86% for RISAT-1, with a larger window size by minimizing the misclassification of sea class into oil spill class. Later the paper concludes the scope of further research possibilities for making a robust system for detecting the oil spills, both precisely and effectually. [ABSTRACT FROM AUTHOR]