Skip to main navigation Skip to search Skip to main content

Automatic Identification System data-potential resource for marine vessels drift studies in the Baltic Sea

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › Research › peer-review

2 Citations (Scopus)

Abstract

Automatic Identification System (AIS) has been employed for increasing the safety at the sea. Nowadays general information about the marine traffic can be tracked in operational mode using www.marinetraffic.com web portal. Additional information can be purchased for commercial and research purposes. Our study highlights a possibility to study the drift using an additional information available at www.marinetraffic.com-selected data on vessel position during its status 'not under command', which corresponds to the drifting vessels. Trajectories of the drift from AIS have been compared with mathematically modeled point-wise drifter paths. Copernicus Marine Environmental Monitoring Service's data for the surface current and Danish Meteorological Institute's model Harmonie data for the wind speed was employed to force the drift model. This comparison may give an indicative insight in the performance of the state-of art drift models. Drift model skill is related to (1) accuracy of the models for the surface current and the wind speed (2) selected drift model and its parameters, and (3) representation of the ship parameters in the drift model. Future research may focus on AIS data application in improving of the accuracy of operational forecasts of the vessel drift for search and rescue (and marina pollution combating) purposes; AIS data may be used for systematic bias (e.g. leeway) correction in operational models.

Original languageEnglish
Title of host publication2020 IEEE 61st Annual International Scientific Conference on Power and Electrical Engineering of Riga Technical University Rtucon 2020 Proceedings
Place of Publication[B.v.]
PublisherIEEE
ISBN (Electronic)9781728195100
ISBN (Print)9781728195100
DOIs
Publication statusPublished - 5 Nov 2020

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 14 - Life Below Water
    SDG 14 Life Below Water

OECD Field of Science

  • 2. Engineering and Technology

Keywords

  • drift model
  • Automatic Identification System

Fingerprint

Dive into the research topics of 'Automatic Identification System data-potential resource for marine vessels drift studies in the Baltic Sea'. Together they form a unique fingerprint.

Cite this