Oil Spill Segmentation

Oil spill segmentation aims to automatically identify and delineate oil spills within satellite imagery, primarily using Synthetic Aperture Radar (SAR) data, to facilitate rapid response and cleanup efforts. Current research heavily utilizes deep learning, employing encoder-decoder architectures like ResNet-50 with DeepLabV3+, and novel networks designed to leverage the inherent statistical distributions of SAR backscatter values for improved segmentation accuracy, even with limited training data. These advancements are crucial for enhancing the efficiency and effectiveness of marine environmental protection by enabling faster and more accurate detection and assessment of oil spills.