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 km2 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, offsho...1. 支撑海洋空间规划（Marine Spatial Planning, MSP）的核心环节之一，是绘制生态过程与生物特征的空间分布格局，以及不同用户群体的社会经济利益分布。然而，商船航运——即用于运输货物或乘客的船舶活动——在海洋空间规划中往往代表性不足，常见原因被归结为缺乏支撑决策制定的精细空间显性数据。 2. 本研究以刚果共和国为研究案例，展示了如何借助公开获取的卫星衍生自动识别系统（Satellite-derived Automatic Identification System, S-AIS）数据，填补国家级尺度下航运活动海洋观测数据的空白。同时，本研究还演示了如何基于S-AIS数据生成0.05 km²分辨率的精细尺度空间数据图层（涵盖船舶活动强度、海域占用情况），进而绘制船舶压力分布图，以量化反映其对海洋环境的影响模式，以及与其他海洋用户群体产生冲突的潜在可能性。 3. 本研究揭示，客船、近海……