High-Resolution Mapping of Port Dynamics from Open-Access AIS Data in Tokyo Bay
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arXiv
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| Format: | Preprint |
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2026
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| _version_ | 1866908793226395648 |
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| author | Hütten, Moritz |
| author_facet | Hütten, Moritz |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_20211 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | High-Resolution Mapping of Port Dynamics from Open-Access AIS Data in Tokyo Bay Hütten, Moritz Computational Engineering, Finance, and Science Information Retrieval 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. |
| title | High-Resolution Mapping of Port Dynamics from Open-Access AIS Data in Tokyo Bay |
| topic | Computational Engineering, Finance, and Science Information Retrieval |
| url | https://arxiv.org/abs/2601.20211 |