Oil Slick Detection and Drift Prediction using Satellite Imagery

This study introduces an intelligent, automated system that uses high-resolution SAR imagery together with environmental data for detecting and tracking oil slicks. By combining dark spot detection, texture and semantic analysis and deep learning, it minimizes false alarms and accurately predicts slick movement based on wind, currents and tides for realtime marine monitoring.