big data for winter navigation in the northern baltic sea
TRANSCRIPT
Big data for winter navigation in the Northern Baltic Sea:
Developments and application opportunities
Prof. Dr. Floris Goerlandt
OceanPredict’19Halifax, NS, Canada, 6-10.5.2019
Dr. Mikko Lensu
Presentation outline
â–Ş AIS data as basis for understanding maritime traffic
â–Ş Trends in using AIS data
â–Ş Big maritime data: AIS data integration
â–Ş Developments and applications: examples
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Automatic Identification System: technology
Source: http://sea-eye.org [accessed 26.03.2019]
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AIS data for understanding maritime traffic
Source: http://www.marinetraffic.com [accessed 27.03.2019]
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Areas of application
Fournier M., Hilliard R.C., Rezaee S., Pelot R. 2018. WMU Journal of Maritime Affairs 17:311-345.
ENVIRONMENT SAFETY SECURITY
Fishing management
Oil spill monitoring
Ship noise pollution
Species at risk
Risk analysis
Traffic simulation
Small craft safety
Domain awareness
Counter-piracy operations
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Trends in academic publishing
Lensu M., Goerlandt F. 2019. Marine Policy 104:53-65.
Operation-focused applications Policy-focused applications
NavigationDomain
awareness…
Maritime spatial planning
Pollution impacts
…
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AIS databaseAIS data
Lensu M., Goerlandt F. 2019. Marine Policy 104:53-65.
â–Ş Full update rate
â–Ş Terrestrial stations
â–Ş Northern Baltic Sea
â–Ş 2007-2016
â–Ş 5.7 billion messages
â–Ş Coverage ca. 70%
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AIS databaseSea ice: Helsinki Multicategory Sea Ice Model (HELMI)
Lensu M., Goerlandt F. 2019. Marine Policy 104:53-65.
Concentration and drift Thickness Ridges Compression
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AIS databaseShip data
Lensu M., Goerlandt F. 2019. Marine Policy 104:53-65.
Vessel particulars Vessel types
www.marinenotes.blogspot.com[accessed 27.03]
www.arctia.fi[accessed 27.03]
www.tallink.silja.com[accessed 27.03]
www.vesselfinder.com [accessed 27.03]
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AIS databaseDerived and supporting datasets
Lensu M., Goerlandt F. 2019. Marine Policy 104:53-65.
â–Ş Derived datasetsCalculated from basic data due to being time-consumingâ–ˇ Spatio-temporal adjacency matrix
(to determine independent and assisted navigation)â–ˇ Set of connected ships
(to determine vessel groups)
â–Ş Supporting datasetsAd-hoc linkable datasets for specific applicationsâ–ˇ Descriptors of specific operationsâ–ˇ Accident data
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AIS databaseSupporting datasets: Operations description
Video construction
Operations analysis
Goerlandt F., Montewka J., Zhang W., Kujala P. 2017. Safety Science 95:198-209.
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Application: data analysisSpatial traffic statistics
Lensu M., Goerlandt F. 2019. Marine Policy 104:53-65.
Independent navigation Assisted navigation
USE
Icebreakeroperability and
planning
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Application: data analysisNavigation speed in ice
Lensu M., Goerlandt F. 2019. Marine Policy 104:53-65.
Fleet-averaged speed Normalized speedUSE
Trafficability analysis
Ship routing
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Application: data analysisIcebreaker assistance (1)
Lensu M., Goerlandt F. 2019. Marine Policy 104:53-65.
USE
Operational understanding
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Application: data analysisIcebreaker assistance (2)
Goerlandt F., Montewka J., Zhang W., Kujala P. 2017. Safety Science 95:198-209.
USE
Understanding safe convoy distance
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Application: data analysisAccident analysis
Goerlandt F., Goite H., Valdez Banda O.A., Höglund A., Ahonen-Rainio P., Lensu M. 2017. Safety Science 92:66-84.
USE
Understanding patterns under which accidents
occur
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Application: modelingIcebreaker convoy model
Zhang W., Goerlandt F., Kujala P., Qi Y. 2018. Ocean Engineering 167:317-333.
USE
Realistic model for convoy operations, for
simulator training
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Application: modelingShip performance model in ice
(independent navigation)
Montewka J., Goerlandt F., Kujala P., Lensu M. 2015. Cold Regions Science and Technology 112:14-28.
Data-driven modelfor ship speed
Data-driven modelfor ship beset in ice
USE
Trafficability analysis
Ship routing
Questions?Comments?
Prof. Dr. Floris Goerlandt
OceanPredict’19Halifax, NS, Canada, 6-10.5.2019
Dr. Mikko Lensu