Hostname: page-component-78c5997874-ndw9j Total loading time: 0 Render date: 2024-11-16T07:29:35.273Z Has data issue: false hasContentIssue false
  • English
  • Français

Web MCA-based Decision Support System for Incident Situations in Maritime Traffic: Case Study of Adriatic Sea

Published online by Cambridge University Press:  21 June 2017

Nenad Mladineo ,
Marko Mladineo  and
Snjezana Knezic
Nenad Mladineo*
Affiliation:
(University of Split, Faculty of Civil Engineering, Architecture and Geodesy (Matice hrvatske 15, 21000 Split, Croatia)
Marko Mladineo
Affiliation:
(University of Split, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture (Rudera Boskovica 32, 21000 Split, Croatia)
Snjezana Knezic
Affiliation:
(University of Split, Faculty of Civil Engineering, Architecture and Geodesy (Matice hrvatske 15, 21000 Split, Croatia)
*
(E-mail: [email protected])
Get access Rights & Permissions [Opens in a new window]

Abstract

This paper describes a Multi-Criteria-Analysis (MCA)-based Decision Support System (DSS) developed for the management of incidents in maritime traffic. The developed DSS helps to organise a large quantity of information related to emergency management, spatial data and “live” data (radar data, weather forecasting data), to make it available to decision makers in a comprehensible and user-friendly way. Special care has been taken to model human Decision-Making (DM) processes during incident situations. Since the DM process is always multi-criterial, a Multi-Criteria Decision-Making (MCDM) method called Preference Ranking Organisation Method for Enrichment Evaluations (PROMETHEE) is used. However, a simplified variation of PROMETHEE II has been utilised to make results more understandable to non-expert users. The aim of this research is to incorporate effective DSS in human DM processes, thus reducing the possibility of making poor decisions. The concept of Web MCA-based DSS is presented as a case study: Web DSS developed for the east coast of the Adriatic Sea.

Keywords

Marine TrafficOperations ResearchSafetyMapping
Type
Research Article
Information
The Journal of Navigation , Volume 70 , Issue 6 , November 2017 , pp. 1312 - 1334
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

Akhtar, M.J. and Utne, I.B. (2014). Human fatigue's effect on the risk of maritime groundings – A Bayesian Network modeling approach. Safety Science, 62, 427–440.Google Scholar
Akyuz, E. and Celik, M. (2014). Utilisation of cognitive map in modelling human error in marine accident analysis and prevention. Safety Science, 70, 19–28.CrossRefGoogle Scholar
Arciniegas, G., Janssen, R. and Omtzigt, N. (2011). Map-based multicriteria analysis to support interactive land use allocation. International Journal of Geographical Information Science, 25(12), 1931–1947.Google Scholar
ASA. (2016). OilMapWeb. http://www.oilmapweb.com/ Accessed 30 October 2016.Google Scholar
Bajic, M. (2012). Airborne Hyperspectral Surveillance of the Ship-based Oil Pollution in Croatian Part of the Adriatic Sea. Geodetski list, 66(89), 77–100.Google Scholar
Brans, J.P. and Mareschal, B. (1991). THE PROMCALC & GAIA Decision Support System for Multicriteria Decision Aid. Centrum voor Statistiek en Operationeel Onderzoek - Vrije Universitet, Brussels, Belgium.Google Scholar
Bradaric, Z., Mladineo, N., Mladineo, M. (2011). Public web-mapping: preliminary usability evaluation. 3rd Croatian NSDI and INSPIRE Day and 7th Cartography and Geoinformation Conference, Split, Croatia.Google Scholar
Chen, S.T., Wall, A., Davies, P., Yang, Z., Wang, J. and Chou, Y.H. (2013). A Human and Organisational Factors (HOFs) analysis method for marine casualties using HFACS-Maritime Accidents (HFACS-MA). Safety Science, 60, 105–114.CrossRefGoogle Scholar
EUR-Lex. (2002). Directive 2002/59/EC of the European Parliament and of the Council. http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2002:208:0010:0027:EN:PDF, Accessed 30 October 2016.Google Scholar
ExactEarth. (2016). ExactAIS. http://www.exactearth.com/products/exactais, Accessed 30 October 2016.Google Scholar
Gilson, E. (2002). The Christian Philosophy of St. Thomas Aquinas. University of Notre Dame Press, Notre Dame, USA.Google Scholar
Guitouni, A. and Martel, J.-M. (1998). Tentative guidelines to help choosing an appropriate MCDA method. European Journal of Operational Research, 109(2), 501–521.Google Scholar
Haklay, M. and Zafiri, A. (2008). Usability engineering for GIS: learning from a screenshot. The Cartographic Journal, 45(2), 87–97.CrossRefGoogle Scholar
INGV. (2016). Adriatic Forecasting System (AFS). http://oceanlab.cmcc.it/afs/#, Accessed 30 October 2016.Google Scholar
Ishikawa, T. and Kastens, K.A. (2005) Why some students have trouble with maps and other spatial representations. Journal of Geoscience Education, 53(2), 184–197.Google Scholar
Jadrijevic, N. (2016). The model for determining competitiveness of nautical tourism ports. Ph.D. Thesis, University of Rijeka, Croatia.Google Scholar
Jankowski, P. (1995). Integrating geographical information systems and multiple criteria decision-making methods. International Journal of Geographic Information Systems, 9(3), 251–273.Google Scholar
Jankowski, P., Andrienko, N. and Andrienko, G. (2001). Map-centred exploratory approach to multiple criteria spatial decision making. International Journal of Geographical Information Science, 15(2), 101–127.Google Scholar
Janssen, R., van Herwijnen, M., Stewart, T.J. and Aerts, J.C.J.H. (2008). Multiobjective decision support for land-use planning. Environment and Planning B: Planning and Design, 35(4), 740–756.Google Scholar
Kazimierski, W. and Stateczny, A. (2015). Radar and Automatic Identification System Track Fusion in an Electronic Chart Display and Information System. Journal of Navigation, 68(6), 1141–1154.Google Scholar
Knezic, S., Mladineo, N. (2006). GIS-based DSS for priority setting in humanitarian mine-action. International Journal of Geographical Information Science, 20(5), 565–588.Google Scholar
Kramers, R.E. (2008). Interaction with maps on the internet- a user centred design approach for the Atlas of Canada. The Cartographic Journal, 45(2), 98–107.Google Scholar
Lee, C.H. (2014). Considerations in Establishing a Decision-Making process for Korea's Places of Refuge. Journal of Navigation and Port Research, 38(6), 629–636.Google Scholar
Lesslie, R.G., Hill, M.J., Hill, P., Cresswell, H.P. and Dawson, S. (2008). The application of a simple spatial multi-criteria analysis shell to natural resource management decision making. Landscape analysis and visualisation: spatial models for natural resource management and planning. Springer, Berlin, Germany.Google Scholar
Li, K.X., Yin, J., Bang, H.S., Yang, Z. and Wang, J. (2012). Bayesian network with quantitative input for maritime risk analysis. Transportmetrica A: Transport Science, 10(2), 89–118.Google Scholar
Marine Electronics & Communications. (2016). Ecdis designed to prevent collisions. http://www.marinemec.com/news/view,ecdis-designed-to-prevent-collisions_42426.htm. Accessed: 2 April 2017.Google Scholar
MarineTraffic. (2016). AIS Marine Traffic. https://www.marinetraffic.com, Accessed 30 October 2016.Google Scholar
Mladineo, M., Mladineo, N. and Knezic, S. (2011). New aspects of emergency decision support for ships in distress. Natural and Technological Risk Reduction through Global Cooperation - Proceedings of 18th TIEMS Annual Conference, 573–582.Google Scholar
Mladineo, N., Margeta, J., Brans, J.P. and Mareschal, B. (1987). Multicriteria ranking of alternative locations for small scale hydro plants. European Journal of Operational Research, 31, 215–222.Google Scholar
Mladineo, N., Lozic, I., Stosic, S., Mlinaric, D. and Radica, T. (1992). An evaluation of multicriteria analysis for DSS in public policy decision. European Journal of Operational Research, 61, 219–229.Google Scholar
Mladineo, N., Knezic, S. and Grzetic, Z., (2009). Development of integrated emergency management model for ships in distress, Let's meet where the continents meet - Proceedings of 16th TIEMS Annual Conference, 352–361.Google Scholar
Mladineo, N., Knezic, S. and Jajac, N. (2011). Decision Support System for Emergency Management on Motorway Networks. Transportmetrica, 7(1), 45–62.Google Scholar
Mladineo, N., Mladineo, M. and Stosic, M. (2014). Web-based Decision Support for Incident Situation in the Adriatic Sea. 2014 ESRI European User Conference Proceedings, Split, Croatia.Google Scholar
NOAA. (2016). GNOME. http://response.restoration.noaa.gov/gnome, Accessed 30 October 2016.Google Scholar
Nivala, A.M., Brewster, S. and Sarjakoski, L.T. (2008). Usability evaluation on web mapping sites. The Cartographic Journal, 45, 129–138.Google Scholar
Pelizaro, C., Arentze, T. and Timmermans, H. (2009). GRAS: a spatial decision support system for green space planning. Planning support systems: best practice and methods. Part II. Springer, Dordrecht, Germany.Google Scholar
Pietrzykowski, Z., Wolejsza, P. and Borkowski, P. (2017). Decision Support in Collision Situations at Sea. Journal of Navigation, 70(3), 447–464.CrossRefGoogle Scholar
Recatalá, L. and Zinck, J. (2008). Land-use planning in the Chaco plain (Burruyacú, Argentina): Part 2: generating a consensus plan to mitigate land-use conflicts and minimize land degradation. Environmental Management, 42(2), 200–209.Google Scholar
Skarlatidou, A. and Haklay, M. (2006). Public web-mapping: preliminary usability evaluation. Proceedings of GIS research UK 2005, Nottingham, UK.Google Scholar
Skarlatidou, A., Haklay, M. and Cheng, T. (2011). Trust in Web GIS: the role of the trustee attributes in the design of trustworthy Web GIS applications. International Journal of Geographical Information Science, 25(12), 1913–1930.CrossRefGoogle Scholar
Stosic, M. (2016). Our inconclusiveness to respond on incidents at sea is alarming (in Croatian - “Nasa neuvjerljivost u rjesavanju incidentnih situacija na moru zabrinjava”). http://www.defender.hr/naslovnica-izdvojeno/nasa-neuvjerljivost-u-rjesavanju-incidentnih-situacija-na-moru-zabrinjava, Accessed: 30 October 2016.Google Scholar
Van Elzakker, C.P.J.M. (2005). From map use research to usability research in geo-information processing. Proceedings of the 22nd international cartographic conference. A Coruña, Spain.Google Scholar
Vriens, D.J. (2004). Information and Communication Technology for Competitive Intelligence. Idea Group Inc, Hershey, USA.Google Scholar
UnistGIS. (2015). University of Split – GIS Lab. http://unistgis.maps.arcgis.com, Accessed: 30 October 2016.Google Scholar
Unwin, D. (2005). Fiddling on a different planet. Geoforum, 36, 681–684.Google Scholar
Urbanski, J., Morgas, W. and Kopacz, Z. (2008). The Safety and Security Systems of Maritime Navigation. Journal of Navigation, 61(3), 529–535.Google Scholar
Walsh, P.G. (2005). Augustine: De Civitate Dei - Books I and II. Liverpool University Press, Liverpool, UK.Google Scholar
Zhao, Z., Ji, K., Xing, X., Zou, H. and Zhou, S. (2014). Ship Surveillance by Integration of Space-borne SAR and AIS – Further Research. Journal of Navigation, 67(2), 295–309.Google Scholar