Integration of optical and radar remote sensing images for classifying and monitoring oil spills at sea
Abstract
Remote sensing data has been widely used in the world in the study of oil spill pollution at sea. This paper presents a study combining the use of Sentinel 2 MSI optical remote sensing and Sentinel 1 radar images to detect and classify oil spills. Sentinel 2 MSI data is used to calculate the OSI (oil spill index) based on visible bands, while Sentinel 1 data is used to calculate the backscatter value, from which oil spills are classified by the thresholding method. The integration of multi-type remote sensing data allows to enhance the density of the input dataset, helping to improve the effectiveness of monitoring marine oil spill pollution.
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