AI-Powered Antarctic Navigation Intelligence
Forecast sea-ice conditions, predict iceberg trajectories and identify safer, fuel-efficient navigation routes for Antarctic research vessels using multi-source satellite, oceanographic and meteorological datasets.
Key Decision Support Capabilities
Government of India Polar Science Framework1. SEA-ICE FORECAST
Forecast Antarctic Sea-Ice Concentration using spatiotemporal ConvLSTM + U-Net deep learning over 6–72h horizons.
2. ICEBERG INTELLIGENCE
Detect, track and forecast iceberg trajectories (A23a, D30) using satellite SAR and environmental hydrodynamic drift physics.
3. NAVIGATION RISK
Generate spatial-temporal 4D risk maps combining ice concentration, iceberg hazard buffers, weather, and GEBCO bathymetry.
4. ROUTE OPTIMIZATION
Generate vessel-aware routes optimized for safety, fuel consumption and ETA using Pareto-A* graph search.
🇮🇳Indian Scientific Stations in Antarctica (NCPOR Operations)
Current environmental status and maritime approach access corridors.
Multi-Source Satellite & Earth Observation
Continuous ingestion from NSIDC/NOAA passive microwave radiometry, Copernicus Sentinel-1 Synthetic Aperture Radar (SAR), ERA5 atmospheric wind vectors, and GEBCO 2024 bathymetry.
View Data CatalogueTransparent AI Validation & Backtesting
Rigorous validation against historical expeditions: ConvLSTM sea-ice forecasts maintain 2.84% MAE, and iceberg trajectory models achieve 4.18 km 24h Average Displacement Error (ADE).
Inspect Model Metrics