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In many sea areas there is significant recreational activity, with many sailing vessels and motor boats navigating, especially in coastal areas. Search and Rescue (SAR) organizations ensure the safety of people at sea, and are relatively frequently called to perform rescue or assistance missions to people in distress. Apart from the importance of adequate operational planning and training, rescue organizations benefit from establishing a robust, effective and cost-efficient response system. Risk-informed capacity planning can serve as a decision-support tool for determining the number and location of the required search and rescue units (SRUs). The purpose of this paper is to present such a risk-informed approach, which combines analysis of historic accident and incident data of recreational boating with information derived from Geographic Information System (GIS) methods. The method is applied to a case study focusing on the risk-informed capacity evaluation of the voluntary search and rescue services in the Finnish part of the Gulf of Finland. Results indicate that the response performance for recreational boating incidents is very good in most areas.
Rocznik
Tom
Strony
55--64
Opis fizyczny
Bibliogr. 16 poz., rys., tab.
Twórcy
autor
- Aalto University, School of Engineering, Department of Applied Mechanics, Marine Technology Research Group on Maritime Risk and Safety, P.O. Box 15300, FI-00076 AALTO, Finland
- Kotka Maritime Research Association Merikotka, 7 Heikinkatu, FI-48100 Kotka, Finland
autor
- Aalto University, School of Engineering, Department of Applied Mechanics, Marine Technology Research Group on Maritime Risk and Safety, P.O. Box 15300, FI-00076 AALTO, Finland
- University of Helsinki, Department of Geosciences and Geography, P.O. Box 64, 00014 Helsinki, Finland
autor
- University of Helsinki, Department of Geosciences and Geography, P.O. Box 64, 00014 Helsinki, Finland
Bibliografia
- 1. AZOFRA, M., PEREZ-LABAJOS, C.A., BLANCO, B. & ACHUTEGUI, J.J. (2007) Optimum placement of sea rescue resource. Saf. Sci. 45. pp. 941–951.
- 2. DAVIES, J., FINLAY, M., MCLENAGHEN, T. & WILSON, D. (2006) Key risk indicators – their role in operational risk management and measurement. The advanced measurement approach to operational risk, London: Risk Books. pp. 215–246.
- 3. Deltamarin (2006) Maritime Search and Rescue on the Eastern Gulf of Finland – a study for the city of Kotka. Project 1032, Deltamarin.
- 4. GOERLANDT, F., TORABIHAGHIGHI, F. & KUJALA, P. (2014) A model for evaluating the performance and reliability of the voluntary maritime rescue system in the Gulf of Finland. Safety, Reliability and Risk Analysis: Beyond the Horizon, Amsterdam, Netherlands, pp. 1351–1356.
- 5. HÄNNINEN, S., HENTINEN, M., RYTKÖNEN, J. & MARTTILA, K. (2003) Suomen ja Viron meripelastusseurojen alihankintastrategia. Research Report 3/2003. Helsinki, Finland: Merenkulkulaitos.
- 6. GOERLANDT, F. & MONTEWKA, J. (2015) Maritime transportation risk analysis: review and analysis in light of some foundational issues. Reliab. Eng. Syst. Saf.
- 7. GOERLANDT, F., MONTEWKA, J. & KUJALA, P. (2014) Tools for an Extended Risk Assessment for Ropax Ship-Ship Collision. Vulnerability, Uncertainty, and Risk: Quantification, Mitigation, and Management, M. Beer, S.-K. Au, and J. W. Hall, Eds. American Society of Civil Engineers, pp. 2292–2302.
- 8. KOLDENHOF, Y. & VAN DER TAK C. (2013) Risk analysis on Dutch search and rescue capacity on the North Sea. Mar. Navig. Saf. Sea Transp. Navig. Probl., pp. 135–141.
- 9. KVALØY, J.T. & AVEN, T. (2005) An alternative approach to trend analysis in accident data. Reliab. Eng. Syst. Saf. 90. pp. 75–82.
- 10. LI, L. (2006) Rescue vessel location modelling. MSc thesis. Halifax, Canada: Dalhousie University, Department of Industrial Engineering.
- 11. NORRINGTON, L., QUIGLEY, J., RUSSEL, A. & VAN DER MEER R. (2008) Modelling the reliability of search and rescue operations with Bayesian belief networks. Reliab. Eng. Syst. Saf. 93 (7). pp. 940–949.
- 12. PELOT, R., DELBRIDGE, C., YAN, W., HILLIARD, C. & WOOTTON, D. (2006) Location-based risk analysis of recreational boating activity. Research Report 2006-02. Halifax, Canada: Dalhousie University.
- 13. PELOT, R., DEVEAUX, J.-P., MCWHIRTER, P. & HAWES, S. (1998) The development of a model of the demand for Search and Rescue Services provided by the Canadian Coast Guard: Phase II. Research Report 1998-01. Halifax, Canada: Dalhousie University.
- 14. ROHWEDER, J., ROGALA, B.L., JOHNSON, D., ANDERSON, S., CLARK, F., CHAMBERLIN, D., POTTER, K. & RUNYON, K. (2012) Application of wind fetch and wave models for habitat rehabilitation and enhancement projects – 2012 update. U.S. Army Corps of Engineers, Contract report.
- 15. SILJANDER, M., VENÄLÄINEN, E., GOERLANDT, F. & PELLIKKA, P. (2015) GIS-based cost distance modelling to support strategic maritime search and rescue planning: a feasibility study. Appl. Geogr. 57. pp. 54–70.
- 16. VENÄLÄINEN, E. (2014) Evaluating voluntary emergency response in the Gulf of Finland. MSc thesis. Helsinki, Finland: University of Helsinki, Department of Geosciences and Geography.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-e11eefc9-5b61-4e99-a102-258cbe0d0084