Optimising port arrival statistics: Enhancing timeliness through Automatic Identification System (AIS) data

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Abstract

Today, there is a greater demand to produce more timely official statistics at a more granular level. National Statistical Institutes (NSIs) are more and more looking to novel data sources to meet this demand. This paper focuses on the use of one such source to compile more timely and detailed official statistics on port visits. The data source used is sourced from the Automatic Identification System (AIS) used by ships to transmit their position at sea. The primary purpose of AIS is maritime safety. While some experimental statistics have been compiled using this data, this paper evaluates the potential of AIS as a data source to compile official statistics with respect to port visits. The paper presents a novel method called 'Stationary Marine Broadcast Method' (SMBM) to estimate the number of port visits using AIS data. The paper also describes how the H3 Index, a spatial index originally developed by Uber, is added to each transmission in the data source. While the paper concludes that the AIS based estimates won't immediately replace the official statistics, it does recommend a pathway to using AIS-based estimates as the basis for official port statistics in the future.

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APA

Van Der Wielen, N., McGurk, J., & Barrett, L. (2024). Optimising port arrival statistics: Enhancing timeliness through Automatic Identification System (AIS) data. Statistical Journal of the IAOS, 40(2), 421–434. https://doi.org/10.3233/SJI-230100

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