Coastal Crete: A Digital Twin of the Ocean for Oil Spill Identification and Forecasting

Developed within the Iliad Digital Twin of the Ocean (DTO) project, Coastal Crete provides advanced marine forecasting for oil spill detection and response. The system integrates satellite data, in-situ observations, and machine learning to predict oil spill trajectories and minimize environmental impacts. Using a multi-model approach, it combines WRF-DA, NEMO, and WAVEWATCH III models for high-resolution forecasts. Making use of Sentinel-1 SAR imagery, a deep learning approach was developed for near-real-time oil spill detection. The methodology is based on a U-net Neural Network, which is compared with the statistical methodology based on pythons’ SNAPpy library. The operational forecasting system employs MEDSLIK-II for oil spill transport modeling and visualization via the GeoMachine platform, ensuring rapid decision-making for marine safety and environmental protection.