Knowledge about vessel activity in port areas and around major industrial zones provides insights into economic trends, supports decision-making for shipping and port operators, and contributes to maritime safety. Vessel data from terrestrial receivers of the Automatic Identification System (AIS) have become increasingly openly available, and we demonstrate that such data can be used to infer port activities at high resolution and with precision comparable to official statistics. We analyze open-access AIS data from a three-month period in 2024 for Tokyo Bay, located in Japan's most densely populated urban region. Accounting for uneven data coverage, we reconstruct vessel activity in Tokyo Bay at $\sim\,$30~m resolution and identify 161 active berths across seven major port areas in the bay. During the analysis period, we find an average of $35\pm17_{\text{stat}}$ vessels moving within the bay at any given time, and $293\pm22_{\text{stat}}+65_{\text{syst}}-10_{\text{syst}}$ vessels entering or leaving the bay daily, with an average gross tonnage of $11{,}860^{+280}_{-\;\,50}$. These figures indicate an accelerating long-term trend toward fewer but larger vessels in Tokyo Bay's commercial traffic. Furthermore, we find that in dense urban environments, radio shadows in vessel AIS data can reveal the precise locations of inherently passive receiver stations.

翻译：掌握港口区域及主要工业区周边的船舶活动信息，有助于洞察经济趋势、支持航运与港口运营商的决策制定，并促进海上安全。来自自动识别系统（AIS）地面接收站的船舶数据日益开放可获取，本文论证了此类数据可用于高分辨率推断港口活动，其精度可与官方统计数据相媲美。我们分析了2024年为期三个月的东京湾开放获取AIS数据，该海湾位于日本人口最密集的都市区。通过考虑数据覆盖的不均匀性，我们以约30米分辨率重建了东京湾的船舶活动，并在海湾内的七个主要港区识别出161个活跃泊位。在分析期间，我们发现任意时刻海湾内平均有$35\pm17_{\text{stat}}$艘船舶在移动，每日进出海湾的船舶数量为$293\pm22_{\text{stat}}+65_{\text{syst}}-10_{\text{syst}}$艘，平均总吨位为$11{,}860^{+280}_{-\;\,50}$。这些数据表明东京湾商业航运长期呈现船舶数量减少但规模增大的加速趋势。此外，我们发现，在密集的城市环境中，船舶AIS数据中的无线电盲区可揭示固有被动接收站点的精确位置。