Free Marine and Ocean GIS Data Sources for Coastal and Maritime Mapping
Discover free global marine and ocean GIS datasets including EEZ boundaries, marine protected areas, shipping lanes, sea surface temperature, and mangrove mapping data.
Marine and ocean data is essential for maritime spatial planning, fisheries management, conservation, and climate research. Here are the best free global datasets.
EEZ Boundaries
The Flanders Marine Institute EEZ Boundaries provide the authoritative global dataset of Exclusive Economic Zone boundaries for all coastal states.
- Format: GeoJSON / Shapefile
- Best for: Maritime jurisdiction and ocean governance mapping
Marine Protected Areas
The World Database on Protected Areas (WDPA) provides the most comprehensive global database of terrestrial and marine protected area boundaries, managed by UNEP-WCMC and IUCN.
- Coverage: 260,000+ protected areas
- Update frequency: Monthly
- Best for: Conservation planning and biodiversity assessment
Shipping Lanes & AIS Traffic
Global shipping lane data provides vessel traffic density from NOAA MarineCadastre and satellite AIS sources for maritime navigation analysis.
- Best for: Port planning, maritime safety, and marine spatial planning
Sea Surface Temperature
The NOAA OISST Sea Surface Temperature dataset provides daily global SST at ~28km resolution from 1981 to present, blending satellite and in-situ observations.
- Coverage: Global ocean
- Resolution: 0.25° (~28km)
- Best for: El Niño monitoring, marine ecosystem studies, and fisheries management
Global Mangrove Watch
The Global Mangrove Watch provides annual mangrove extent maps at 25m resolution from 1996 to present for all 121 mangrove-holding countries.
- Resolution: 25m
- Temporal: Annual (1996–present)
- Best for: Mangrove conservation and blue carbon assessment
Combining Marine Datasets
- Start with EEZ boundaries for jurisdictional context.
- Overlay MPAs and mangroves for conservation planning.
- Combine SST with climate data for marine ecosystem analysis.
- Use GeoDataViewer Studio to visualize these layers together.
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