Articles | Volume 12, issue 1
https://doi.org/10.5194/os-12-285-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/os-12-285-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
23 Feb 2016
Research article |
| 23 Feb 2016
Combining operational models and data into a dynamic vessel risk assessment tool for coastal regions
R. Fernandes
CORRESPONDING AUTHOR
MARETEC – Marine Environment and Technology Centre,
Instituto Superior Técnico, Universidade de Lisboa, Avenida Rovisco
Pais, 1049-001, Lisbon, Portugal
now at: Action Modulers, Estrada Principal, 29, 2640-583, Mafra, Portugal
F. Braunschweig
Action Modulers, Estrada Principal, 29, 2640-583, Mafra,
Portugal
F. Lourenço
Action Modulers, Estrada Principal, 29, 2640-583, Mafra,
Portugal
now at: Aubay Portugal, Av. República, 101 –
3 E, 1050-190 Lisbon, Portugal
MARETEC – Marine Environment and Technology Centre,
Instituto Superior Técnico, Universidade de Lisboa, Avenida Rovisco
Pais, 1049-001, Lisbon, Portugal
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Cited
14 citations as recorded by crossref.
- Models and computational algorithms for maritime risk analysis: a review G. Lim et al. 10.1007/s10479-018-2768-4
- Modeling chronic oil pollution from ships S. Liubartseva et al. 10.1016/j.marpolbul.2023.115450
- Development and validation of a morphological model for multiple sediment classes G. Franz et al. 10.1016/j.ijsrc.2017.05.002
- Vessel Traffic Risk Assessment Based on Uncertainty Analysis in the Risk Matrix M. Sun & Z. Zheng 10.3390/a11050060
- A dynamic risk assessment method to address safety of navigation concerns around offshore renewable energy installations R. Mehdi et al. 10.1177/1475090219837409
- Temporal features of non-accident critical events impact from tides around the Yangtze Estuary and adjacent coastal waters C. Yao et al. 10.1017/S0373463321000862
- Evolution pathway of process risk of marine traffic with the STAMP model and a genetic algorithm: A simulation of LNG-fueled vessel in-and-out harbor S. Hu et al. 10.1016/j.oceaneng.2022.111133
- Ship collision risk assessment: A multi-criteria decision-making framework based on Dempster–Shafer evidence theory N. Wang et al. 10.1016/j.asoc.2024.111823
- The Joint IOC (of UNESCO) and WMO Collaborative Effort for Met-Ocean Services N. Pinardi et al. 10.3389/fmars.2019.00410
- Validation of the 3D-MOHID Hydrodynamic Model for the Tagus Coastal Area H. de Pablo et al. 10.3390/w11081713
- Probabilistic approach for characterising the static risk of ships using Bayesian networks D. Dinis et al. 10.1016/j.ress.2020.107073
- AIS in maritime research M. Svanberg et al. 10.1016/j.marpol.2019.103520
- Models and computational algorithms for maritime risk analysis: a review G. Lim et al. 10.1007/s10479-018-2768-4
- An oil risk management system based on high-resolution hazard and vulnerability calculations A. Azevedo et al. 10.1016/j.ocecoaman.2016.11.014
12 citations as recorded by crossref.
- Models and computational algorithms for maritime risk analysis: a review G. Lim et al. 10.1007/s10479-018-2768-4
- Modeling chronic oil pollution from ships S. Liubartseva et al. 10.1016/j.marpolbul.2023.115450
- Development and validation of a morphological model for multiple sediment classes G. Franz et al. 10.1016/j.ijsrc.2017.05.002
- Vessel Traffic Risk Assessment Based on Uncertainty Analysis in the Risk Matrix M. Sun & Z. Zheng 10.3390/a11050060
- A dynamic risk assessment method to address safety of navigation concerns around offshore renewable energy installations R. Mehdi et al. 10.1177/1475090219837409
- Temporal features of non-accident critical events impact from tides around the Yangtze Estuary and adjacent coastal waters C. Yao et al. 10.1017/S0373463321000862
- Evolution pathway of process risk of marine traffic with the STAMP model and a genetic algorithm: A simulation of LNG-fueled vessel in-and-out harbor S. Hu et al. 10.1016/j.oceaneng.2022.111133
- Ship collision risk assessment: A multi-criteria decision-making framework based on Dempster–Shafer evidence theory N. Wang et al. 10.1016/j.asoc.2024.111823
- The Joint IOC (of UNESCO) and WMO Collaborative Effort for Met-Ocean Services N. Pinardi et al. 10.3389/fmars.2019.00410
- Validation of the 3D-MOHID Hydrodynamic Model for the Tagus Coastal Area H. de Pablo et al. 10.3390/w11081713
- Probabilistic approach for characterising the static risk of ships using Bayesian networks D. Dinis et al. 10.1016/j.ress.2020.107073
- AIS in maritime research M. Svanberg et al. 10.1016/j.marpol.2019.103520
Saved (preprint)
Latest update: 21 Jan 2025
Short summary
A combined methodology to estimate time and space variable shoreline risk levels from ships has been developed, integrating metocean forecasts and oil spill simulations with vessel tracking automatic identification systems (AIS) and coastal vulnerability indices. Results show the ability of the proposed methodology to estimate the risk properly sensitive to dynamic metocean conditions and oil transport behaviour, enhancing the maritime situational awareness and the decision support model.
A combined methodology to estimate time and space variable shoreline risk levels from ships has...
