Emily Hague , Alice Walters , Anna Moscrop , Emma Steel , Katie Dyke , Lauren Hartny-Mills , Alison Lomax , Rebecca Dudley , Pippa Garrard , Jenny Hampson , Sadie Gorvett , Hannah Lightley , Craig Mackie , Juliane Lehmann , Sebastian Olias , Carsten Hilgenfeld , Debbie Cole , Sarah MacDonald-Taylor , Carole Davis , Bernard Siddle , Lauren McWhinnie
{"title":"AIS data underrepresents vessel traffic around coastal Scotland","authors":"Emily Hague , Alice Walters , Anna Moscrop , Emma Steel , Katie Dyke , Lauren Hartny-Mills , Alison Lomax , Rebecca Dudley , Pippa Garrard , Jenny Hampson , Sadie Gorvett , Hannah Lightley , Craig Mackie , Juliane Lehmann , Sebastian Olias , Carsten Hilgenfeld , Debbie Cole , Sarah MacDonald-Taylor , Carole Davis , Bernard Siddle , Lauren McWhinnie","doi":"10.1016/j.marpol.2025.106719","DOIUrl":null,"url":null,"abstract":"<div><div>Automatic Identification System (AIS) data is often used as a proxy to quantify vessel densities and estimate their associated impacts (e.g. emissions, underwater noise, likelihood of collision with marine megafauna), yet it is increasingly acknowledged that AIS data does not fully capture all vessels that may be present within a given area. Therefore, impacts that are evaluated using only AIS-based vessel data (e.g. counts) are likely underestimating the volume of vessel traffic, and thus the potential and scale that effects may occur. The extent of this underestimation is unclear due to the lack of data on the volume and distribution of vessels that are not transmitting AIS. To investigate this, > 1800 hours of land-based and at-sea visual surveys were conducted across nine Scottish Marine Regions between 2019 and 2024, collecting data on coastal vessel activity (<10 km of shore). These data were compared with corresponding AIS data to quantify AIS vs non-AIS traffic. Non-AIS vessels were present during 67 % of the total time surveyed. Of the vessels recorded, only 43 % were broadcasting AIS. AIS transmission rates were varied between seasons (range = 38–55 %), regions (range = 20–58 %), and by vessel type (range = 0–95 %). Given AIS data is increasingly being used to quantify vessel activity and predict associated impacts, it is vital that further consideration is given to the volume of vessel traffic absent from these datasets and predictive efforts. Underestimation of actual vessel traffic present, and the potential associated impacts may lead to inadequate policies, management or mitigation efforts.</div></div>","PeriodicalId":48427,"journal":{"name":"Marine Policy","volume":"178 ","pages":"Article 106719"},"PeriodicalIF":3.5000,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Marine Policy","FirstCategoryId":"90","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0308597X25001344","RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL STUDIES","Score":null,"Total":0}
引用次数: 0
Abstract
Automatic Identification System (AIS) data is often used as a proxy to quantify vessel densities and estimate their associated impacts (e.g. emissions, underwater noise, likelihood of collision with marine megafauna), yet it is increasingly acknowledged that AIS data does not fully capture all vessels that may be present within a given area. Therefore, impacts that are evaluated using only AIS-based vessel data (e.g. counts) are likely underestimating the volume of vessel traffic, and thus the potential and scale that effects may occur. The extent of this underestimation is unclear due to the lack of data on the volume and distribution of vessels that are not transmitting AIS. To investigate this, > 1800 hours of land-based and at-sea visual surveys were conducted across nine Scottish Marine Regions between 2019 and 2024, collecting data on coastal vessel activity (<10 km of shore). These data were compared with corresponding AIS data to quantify AIS vs non-AIS traffic. Non-AIS vessels were present during 67 % of the total time surveyed. Of the vessels recorded, only 43 % were broadcasting AIS. AIS transmission rates were varied between seasons (range = 38–55 %), regions (range = 20–58 %), and by vessel type (range = 0–95 %). Given AIS data is increasingly being used to quantify vessel activity and predict associated impacts, it is vital that further consideration is given to the volume of vessel traffic absent from these datasets and predictive efforts. Underestimation of actual vessel traffic present, and the potential associated impacts may lead to inadequate policies, management or mitigation efforts.
期刊介绍:
Marine Policy is the leading journal of ocean policy studies. It offers researchers, analysts and policy makers a unique combination of analyses in the principal social science disciplines relevant to the formulation of marine policy. Major articles are contributed by specialists in marine affairs, including marine economists and marine resource managers, political scientists, marine scientists, international lawyers, geographers and anthropologists. Drawing on their expertise and research, the journal covers: international, regional and national marine policies; institutional arrangements for the management and regulation of marine activities, including fisheries and shipping; conflict resolution; marine pollution and environment; conservation and use of marine resources. Regular features of Marine Policy include research reports, conference reports and reports on current developments to keep readers up-to-date with the latest developments and research in ocean affairs.