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Teasing out the detail: How our understanding of marine AIS data can better inform industries, developments, and planning

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  • Shelmerdine, Richard L.

Abstract

Automatic identification system (AIS) is becoming increasingly popular with marine vessels providing accessible, up-to-date information on vessel activity in the marine environment. Although AIS has been utilised in several different fields to address specific questions, no published work has outlined the potential of AIS as a tool for a wide range of industries and users of the marine environment such as spatial planning, developments, and local marine industries (e.g. fisheries). This work demonstrates a procedure for processing, analysing, and visualisation of AIS data with example outputs and their potential uses. Over 730000 data points of AIS information for 2013 from around Shetland were processed, analysed, and mapped. Tools used included density mapping, vessel tracks, interpolations of vessel dimensions, and ship type analysis. The dataset was broken down by sector into meaningful and usable data packets which could also be analysed over time. Density mapping, derived from both point and vessel track data, proved highly informative but were unable to address all aspects of the data. Vessel tracks showed variation in vessel routes, especially around island groups. Additional uses of AIS data were addressed and included risk mapping for invasive non-native species, fisheries, and general statistics. Temporal variation of vessel activity was also discussed.

Suggested Citation

  • Shelmerdine, Richard L., 2015. "Teasing out the detail: How our understanding of marine AIS data can better inform industries, developments, and planning," Marine Policy, Elsevier, vol. 54(C), pages 17-25.
  • Handle: RePEc:eee:marpol:v:54:y:2015:i:c:p:17-25
    DOI: 10.1016/j.marpol.2014.12.010
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    References listed on IDEAS

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    1. Goerlandt, Floris & Kujala, Pentti, 2011. "Traffic simulation based ship collision probability modeling," Reliability Engineering and System Safety, Elsevier, vol. 96(1), pages 91-107.
    2. Shucksmith, Rachel & Gray, Lorraine & Kelly, Christina & Tweddle, Jacqueline F., 2014. "Regional marine spatial planning – The data collection and mapping process," Marine Policy, Elsevier, vol. 50(PA), pages 1-9.
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    9. Cai, Mingyou & Zhang, Jinfen & Zhang, Di & Yuan, Xiaoli & Soares, C. Guedes, 2021. "Collision risk analysis on ferry ships in Jiangsu Section of the Yangtze River based on AIS data," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
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    11. Johnny Grøneng Aase, 2017. "The Ortelius Incident in the Hinlopen Strait—A Case Study on How Satellite-Based AIS Can Support Search and Rescue Operations in Remote Waters," Resources, MDPI, vol. 6(3), pages 1-10, July.
    12. Xin, Xuri & Liu, Kezhong & Loughney, Sean & Wang, Jin & Yang, Zaili, 2023. "Maritime traffic clustering to capture high-risk multi-ship encounters in complex waters," Reliability Engineering and System Safety, Elsevier, vol. 230(C).

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