用开放定位数据重建波罗的海船舶活动，精度高且无需完整覆盖。
Maritime Activities Observed Through Open-Access Positioning Data: Moving and Stationary Vessels in the Baltic Sea
- 基于AIS数据清洗与旅程建模，提升低质量数据可用性
- 平均每秒超4000艘船在航，日均300多艘进出该区域
- 可识别港口位置，适合海事管理与环境评估人员参考
了解过往和当前的海上活动模式对航行安全、环境评估和商业运营至关重要。越来越多的服务通过地面接收器公开提供自动识别系统（AIS）的定位数据。我们证明，即使数据质量有限、接收器覆盖不全，也能高精度重构沿海船舶活动。针对2024年8月至10月波罗的海三个月的公开AIS数据，本文提出（i）数据清洗与重建方法以提升数据质量，（ii）一种旅程模型，将AIS消息数据转化为船舶数量、交通估算及空间分辨率达约400米的船舶密度图。同时提供动态与静态活动的船舶计数及其不确定性。密度图可用于识别港口位置，并推断波罗的海最繁忙的海岸区域。结果显示，平均有超过4000艘船舶同时在该海域运行，每日超过300艘船舶进出。结果与依赖专有数据的先前研究相比误差在20%以内。
原文摘要 · Abstract (English)
Understanding past and present maritime activity patterns is critical for navigation safety, environmental assessment, and commercial operations. An increasing number of services now openly provide positioning data from the Automatic Identification System (AIS) via ground-based receivers. We show that coastal vessel activity can be reconstructed from open access data with high accuracy, even with limited data quality and incomplete receiver coverage. For three months of open AIS data in the Baltic Sea from August to October 2024, we present (i) cleansing and reconstruction methods to improve the data quality, and (ii) a journey model that converts AIS message data into vessel counts, traffic estimates, and spatially resolved vessel density at a resolution of $\sim$400 m. Vessel counts are provided, along with their uncertainties, for both moving and stationary activity. Vessel density maps also enable the identification of port locations, and we infer the most crowded and busiest coastal areas in the Baltic Sea. We find that on average, $\gtrsim$4000 vessels simultaneously operate in the Baltic Sea, and more than 300 vessels enter or leave the area each day. Our results agree within 20\% with previous studies relying on proprietary data.
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