MAPPING OIL SPILLS ON SEA SURFACE FROM SENTINEL 2 IMAGES USING PRINCIPAL COMPONENTS AND CATEGORICAL BOOSTING
- 1Training Center for Applied Geodesy and Photogrammetry, University of the Philippines, Diliman, 1001, Philippines
- 2Department of Geodetic Engineering, University of the Philippines, Diliman, 1001, Philippines
Keywords: Principal component analysis, Water remote sensing, Homogeneity, Image texture, Gradient Boosting
Abstract. A large oil spill in Iloilo Straight that occurred on July 3, 2020, as well as a possible deliberate, small but frequent oil spill and surfactant contamination in Manila Bay, were mapped. The method employs the Sentinel 2-1C image, which is transformed into principal components to reveal the presence of oil spills and possibly surfactants. Additionally, a gradient boosting algorithm was trained to discriminate between pixels that were contaminated with oil and those that were not. The multi-band image with three principal components with a 99% cumulative explained variance ratio highlights the occurrence of an oil spill in Iloilo Straight. Further, the classified image produced by pixel-based classification clearly distinguishes between water and oil pixels in the said area. The methodology was applied to a Sentinel 2-1C image of Manila Bay, with pixels observed/identified as oil and classified as well. The highest density of supposedly oil-contaminated pixels (large or small but frequent) was observed on the eastern side of Manila Bay (Bataan). While there were no documented oil spills concurrent to the satellite image used, historical reports on the area indicate that the likelihood of an oil spill is extremely high due to the massive amount of shipping activity. Pixels supposedly contaminated by oil spills also occur in areas near ports where oil spills could occur as a result of ship operations. Pixels with the same properties as oil contamination are also visible in areas adjacent to fishponds and aquaculture, where phytoplankton and fish contribute to surfactant contamination.