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DATA MODEL BASED APPROACH FOR GIS-BASED MARITIME SAFETY MONITORING

Misha Tsvetkov

First published: 2019-06-20https://doi.org/10.5593/sgem2019/2.2/s11.096View metrics

Abstract

Presently, most electronic navigation charts (ENC) are vector format maps based on the S-57 data model. This model uses the descriptive and spatial characteristics of bodies of water to create hydrographic information which can be used to solve such problems as: marine traffic monitoring, vessel route planning, maritime dangerous situation detection, etc. This paper presents an approach to maritime safety monitoring on the basis of intelligent GIS technology. GIS-oriented systems are often used for maritime safety monitoring and situation assessment; these systems allow to analyze, visualize received information and what is more to support organizational decision-making processes in case of emergencies. The S-57 data model, subject domain ontology, expert systems and various other artificial intelligence technologies and tools are proposed as necessary additions for system implementation. The application of this technique is illustrated via a case study of situational route assessment for safe navigation in the busy waters of the Baltic Sea.

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Publication details

Title
DATA MODEL BASED APPROACH FOR GIS-BASED MARITIME SAFETY MONITORING
Authors
Misha Tsvetkov
Proceedings
SGEM International Multidisciplinary Scientific GeoConference EXPO Proceedings; 19th International Multidisciplinary Scientific GeoConference SGEM2019, Informatics, Geoinformatics and Remote Sensing
Publisher
STEF92 Technology
Year
2019
Pages
783-790
SWS Citekey
Tsvetkov201911783790
ISSN
1314-2704
ISBN
978-619-7408-80-5
Language
en
Publication type
Conference Paper
Keywords
References7
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  2. Baylon A.M., Santos E.M.R. “Introducing GIS to TransNav and its Extensive Maritime Application: An Innovative Tool for intelligent Decision Making?”, International Journal on Marine Navigation and Safety of Sea Transportation, vol.7, no.4, 2013, pp. 557–566.

  3. Popovich V. V. “Intelligent GIS Conceptualization, Information Fusion and Geographic Information Systems”, in Proc. IF&GIS 2013 Conf., St. Petersburg, Russia, May 2013, pp. 17–44.

  4. Smirnova O., Tsvetkov M., Sorokin R. “Intelligent GIS for monitoring and prediction of potentially dangerous situations”, in Proc. SGEM 2014 Conf., vol.1, June 17–26, 2014, pp. 659–666.

  5. ] Claramunt C., Ray C., Camossi E., Jousselme A.-L., Hadzagic M., Andrienko G.L., Andrienko N.V., Theodoridis Y., Vouros G.A., Salmon L., Maritime data integration and analysis: recent progress and research challenges, EDBT 2017: pp.192-197, 2017.

  6. Kokar M., Matheus C., and Baclawski K. “Ontology-Based Situation Awareness”, Information Fusion, vol.10, no.1, 2009, pp. 83–98.

  7. Endsley M.R. “SAGAT: A Methodology for the measurement of situation awareness”. Hawthorne, CA: Northrop Corp.

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