Hostname: page-component-78c5997874-j824f Total loading time: 0 Render date: 2024-11-16T07:28:12.029Z Has data issue: false hasContentIssue false

Maritime Traffic Analysis of the Strait of Istanbul based on AIS data

Published online by Cambridge University Press:  27 July 2017

Yigit C. Altan*
Affiliation:
(Department of Civil Engineering, Bogazici University, Istanbul, Turkey) (Department of Civil Engineering, Bahcesehir University, Istanbul, Turkey)
Emre N. Otay
Affiliation:
(Department of Civil Engineering, Bogazici University, Istanbul, Turkey)
*

Abstract

The Strait of Istanbul is one of the most congested and risky waterways in the world. Navigation patterns have been investigated using Automatic Indentification System (AIS) data collected over a long period. 1·5 billion AIS messages, gathered over a year from 309,000 moving vessels in the Strait were stored in a Structured Query Language (SQL) database. Grid-based analysis is used to track the time, number, position, type, dimension, heading, speed and course over ground of ships. Local traffic, whose effect on maritime risk has often been neglected, is found to dominate transit traffic by a ratio of eight to one. Vessel distributions indicate that the most common lengths of vessels are 100 m and 170 m. Draught analysis shows a net transfer of goods from north to south. Southbound vessels are more likely to exceed the enforced speed limit due to predominant currents. Courses indicate that the local traffic strongly affects navigation patterns, especially at sectors with sharp turns. All these results help to understand the navigation patterns of ships and give the necessary input to assist in predicting maritime risk.

Type
Research Article
Copyright
Copyright © The Royal Institute of Navigation 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Altan, Y. (2016). Analysis and Modeling of Maritime Traffic and Ship Collision in the Strait of Istanbul Based on Automatic Vessel Tracking System (Doctoral Thesis). Bogazici University Google Scholar
Aydogdu, Y.V., Yurtoren, C., Park, J. and Park, Y. (2012) ‘A Study on Local Traffic Management to Improve Marine Traffic Safety in the Istanbul Strait’, The Journal of Navigation, 65, 99112.CrossRefGoogle Scholar
Breithaupt, S.A., Copping, A., Tagestad, J. and Whiting, J. (2017). Maritime Route Delineation using AIS Data from the Atlantic Coast of the US. Journal of Navigation, 70, 379394.Google Scholar
Chen, J., Lu, F. and Peng, G. (2015). A quantitative approach for delineating principal fairways of ship passages through a strait. Ocean Engineering, 103, 188197.Google Scholar
Cucinotta, F., Guglielmino, E. and Sfravara, F. (2017). Frequency of Ship Collisions in the Strait of Messina through Regulatory and Environmental Constraints Assessment. The Journal of Navigation, doi: 10.1017/S0373463317000157.Google Scholar
Debnath, A.K. and Chin, H.C. (2016). Modelling Collision Potentials in Port Anchorages: Application of the Navigational Traffic Conflict Technique (NTCT). The Journal of Navigation, 69(1), 183196.CrossRefGoogle Scholar
Goerlandt, F., Montewka, J., Zhang, W. and Kujala, P. (2017). An analysis of ship escort and convoy operations in ice conditions. Safety Science, 95, 198209.CrossRefGoogle Scholar
Gucma, L. and Przywarty, M. (2008). The model of oil spills due to ships collisions in Southern Baltic area. TransNav: International Journal on Marine Navigation and Safety of Sea Transportation, 2(4), 415419. Available at: https://www.infona.pl/resource/bwmeta1.element.baztech-3ef33fce-b6fc-4530-91bc-d338a71cf2f2, https://www.infona.pl/resource/bwmeta1.element.baztech-3ef33fce-b6fc-4530-91bc-d338a71cf2f2/content/partDownload/8cdcb1e9-daf2-3ff4-8821-8290e7a43755.Google Scholar
Gunnar, Aarsæther K and Moan, T. (2009). Estimating Navigation Patterns from AIS. The Journal of Navigation, 62(4), 587.Google Scholar
HELCOM. (2011). Report on shipping accidents in the Baltic Sea area during 2011. Available at: http://www.helcom.fi/Lists/Publications/Annual report on shipping accidents in the Baltic Sea area during 2011.pdf.Google Scholar
Kornhauser, A.L., Clark, W.A. (1995). Quantitative forecast of vessel casualties resulting from additional oil tanker traffic through the Bosphorus. ALK Associates Inc. Report, September, Princeton, NJGoogle Scholar
Maimun, A., Nursyirman, I.F., Sian, A.Y., Samad, R. and Oladokun, S. (2013). Using AIS Data for Navigational Risk Assessment in Restricted Waters. In Marine Technology and Sustainable Development, 245254. doi: 10.4018/978-1-4666-4317-8.ch015.Google Scholar
Meng, Q., Weng, J. and Li, S. (2014). Analysis with Automatic Identification System Data of Vessel Traffic Characteristics in the Singapore Strait. Transportation Research Record, (2426), 3343.Google Scholar
Mou, J.M., van der Tak, C. and Ligteringen, H. (2010). Study on collision avoidance in busy waterways by using AIS data. Ocean Engineering, 37(5–6), 483490.Google Scholar
Mulyadi, Y., Kobayashi, E., Wakabayashi, N., Pitana, T. and Wahyudi, (2014). Development of ship sinking frequency model over Subsea Pipeline for Madura Strait using AIS data. WMU Journal of Maritime Affairs, 13(1), 4359.Google Scholar
Otay, E.N. and Özkan, S. (2003). Stochastic Prediction of Maritime Accidents in the strait of Istanbul. Proceedings of the 3rd International Conference on Oil Spills in the Mediterranean and Black Sea regions, pp. 92104.Google Scholar
Shu, Y., Daamen, W., Ligteringen, H. and Hoogendorn, S.P. (2017). Influence of extreme external conditions and vessel encounters on vessel behavior in ports and waterways using Automatic Identification System data. Ocean Engineering, 131(July 2016), 114.Google Scholar
Silveira, P.A.M., Teixeira, A.P. and Soares, C.G. (2013). Use of AIS Data to Characterise Marine Traffic Patterns and Ship Collision Risk off the Coast of Portugal. The Journal of Navigation, 66, 879898.Google Scholar
Tan, B. and Otay, E.N. (1999). Modeling and analysis of vessel casualties resulting from tanker traffic through narrow waterways. Naval Research Logistics, 46(8), 871892.3.0.CO;2-I>CrossRefGoogle Scholar
TSMTR. (1998). Turkish Straits Maritime Traffic Regulation. Official Gazette 06-11-1998: 23515 Repeat Published.Google Scholar
Wu, L., Xu, Y., Wang, Q., Wang, F. and Xu, Z. (2016a). Mapping Global Shipping Density from AIS Data. The Journal of Navigation, 70(1), 67-81.Google Scholar
Wu, X., Mehta, A.L., Zaloom, V.A. and Craig, B.N. (2016b). Analysis of waterway transportation in Southeast Texas waterway based on AIS data. Ocean Engineering, 121, 196209.Google Scholar
Xiao, F., Ligteringen, H., Van Gulijk, C and Ale, B. (2015). Comparison study on AIS data of ship traffic behaviour. Ocean Engineering, 95, 8493.Google Scholar
Yazici, M.A. and Otay, E.N. (2009). A Navigational Safety Support Model for the Strait of Istanbul. The Journal of Navigation, 62, 609630.Google Scholar
Zaman, M.B., Kobayashi, E., Wakabayashi, N., Khanfir, S., Pitana, T. and Maimun, A. (2013). Fuzzy FMEA model for risk evaluation of ship collisions in the Malacca Strait: based on AIS data. Journal of Simulation, 8(1), 91104.Google Scholar
Zhang, W., Goerlandt, F., Kujala, P. and Wang, Y. (2016). An advanced method for detecting possible near miss ship collisions from AIS data. Ocean Engineering, 124, pp. 141156.Google Scholar
Zhang, H., Xiao, Y. and Yang, X. (2010). AIS-based analysis of ships’ routeing system. The 2nd International Conference on Computer and Automation Engineering, ICCAE 2010, 494498. doi: 10.1109/ICCAE.2010.5451258.Google Scholar