Using satellite AIS to improve our understanding of shipping and fill gaps in ocean observation data to support marine spatial planning

1. A key stage underpinning marine spatial planning (MSP) involves mapping the spatial distribution of ecological processes and biological features as well the social and economic interests of different user groups. One sector, merchant shipping (vessels that transport cargo or passengers), however, is often poorly represented in MSP due to a perceived lack of fine-scale spatially explicit data to support decision-making processes. 2.Here, using the Republic of Congo as an example, we show how publicly accessible satellite-derived automatic identification system (S-AIS) data can address gaps in ocean observation data for shipping at a national scale. We also demonstrate how fine-scale (0.05 km(2) resolution) spatial data layers derived from S-AIS (intensity, occupancy) can be used to generate maps of vessel pressure to provide an indication of patterns of impact on the marine environment and potential for conflict with other ocean user-groups. 3. We reveal that passenger vessels, offshore service vessels, bulk carrier and cargo vessels and tankers account for 93.7% of all vessels and vessel traffic annually, and that these sectors operate in a combined area equivalent to 92% of Congo's exclusive economic zone-far exceeding the areas allocated for other user groups (conservation, fisheries and petrochemicals). We also show that the shallow coastal waters and habitats of the continental shelf are subject to more persistent pressure associated with shipping, and that the potential for conflict among user groups is likely to be greater with fisheries, whose zones are subject to the highest vessel pressure scores than with conservation or petrochemical sectors. 4. Synthesis and applications. Shipping dominates ocean use, and so excluding this sector from decision-making could lead to increased conflict among user groups, poor compliance and negative environmental impacts. This study demonstrates how satellite-derived Automatic Identification System data can provide a comprehensive mechanism to fill gaps in ocean observation data and visualise patterns of vessel behaviour and potential threats to better support marine spatial planning at national scales.