SeSaM Input data

The SeSAM project integrates a diverse range of satellite, oceanographic, and climate datasets to enhance the accuracy of Sargassum detection and forecasting.
Satellite Data (For Real-Time Monitoring & Historical Analysis)

Sentinel-3 (OLCI): Ocean color data for Sargassum detection.
MODIS Aqua: Long-term observations of floating macroalgae.
Sentinel-2 (MSI): High-resolution imagery (20m) for coastal Sargassum mapping.
Landsat-8 & 9 (OLI): Historical and current tracking of Sargassum dynamics.
Climate & Oceanographic Models (For Seasonal Forecasting)

SEAS5 (ECMWF): Seasonal climate predictions, including ocean and atmospheric variability.
NEMO-Sarg1.0 Model (FORESEA Project): Simulates Sargassum growth, transport, and drift, integrating ocean circulation, wind patterns, and biological factors.
SeSAM's data-driven approach combines satellite observations with numerical modeling, offering accurate, high-resolution predictions to support coastal management and early warning systems.