scholarly journals Combining operational models and data into a dynamic vessel risk assessment tool for coastal regions

2015 ◽  
Vol 12 (4) ◽  
pp. 1327-1388 ◽  
Author(s):  
R. Fernandes ◽  
F. Braunschweig ◽  
F. Lourenço ◽  
R. Neves
Keyword(s):  
Risk Assessment ◽  
Real Time ◽  
Oil Spill ◽  
Situational Awareness ◽  
Assessment Tool ◽  
Weather Conditions ◽  
Traffic Monitoring ◽  
Automatic Identification ◽  
Decision Support Model ◽  
Risk Levels

Abstract. The technological evolution in terms of computational capacity, data acquisition systems, numerical modelling and operational oceanography is supplying opportunities for designing and building holistic approaches and complex tools for newer and more efficient management (planning, prevention and response) of coastal water pollution risk events. A combined methodology to dynamically estimate time and space variable shoreline risk levels from ships has been developed, integrating numerical metocean forecasts and oil spill simulations with vessel tracking automatic identification systems (AIS). The risk rating combines the likelihood of an oil spill occurring from a vessel navigating in a study area – Portuguese Continental shelf – with the assessed consequences to the shoreline. The spill likelihood is based on dynamic marine weather conditions and statistical information from previous accidents. The shoreline consequences reflect the virtual spilled oil amount reaching shoreline and its environmental and socio-economic vulnerabilities. The oil reaching shoreline is quantified with an oil spill fate and behaviour model running multiple virtual spills from vessels along time. Shoreline risks can be computed in real-time or from previously obtained data. Results show the ability of the proposed methodology to estimate the risk properly sensitive to dynamic metocean conditions and to oil transport behaviour. The integration of meteo-oceanic + oil spill models with coastal vulnerability and AIS data in the quantification of risk enhances the maritime situational awareness and the decision support model, providing a more realistic approach in the assessment of shoreline impacts. The risk assessment from historical data can help finding typical risk patterns, "hot spots" or developing sensitivity analysis to specific conditions, whereas real time risk levels can be used in the prioritization of individual ships, geographical areas, strategic tug positioning and implementation of dynamic risk-based vessel traffic monitoring.

scholarly journals Combining operational models and data into a dynamic vessel risk assessment tool for coastal regions

Ocean Science ◽  
2016 ◽  
Vol 12 (1) ◽  
pp. 285-317 ◽  
Author(s):  
R. Fernandes ◽  
F. Braunschweig ◽  
F. Lourenço ◽  
R. Neves
Keyword(s):  
Risk Assessment ◽  
Real Time ◽  
Oil Spill ◽  
Assessment Tool ◽  
Weather Conditions ◽  
Traffic Monitoring ◽  
Automatic Identification ◽  
Accident Risk ◽  
Decision Support Model ◽  
Risk Levels

Abstract. The technological evolution in terms of computational capacity, data acquisition systems, numerical modelling and operational oceanography is supplying opportunities for designing and building holistic approaches and complex tools for newer and more efficient management (planning, prevention and response) of coastal water pollution risk events. A combined methodology to dynamically estimate time and space variable individual vessel accident risk levels and shoreline contamination risk from ships has been developed, integrating numerical metocean forecasts and oil spill simulations with vessel tracking automatic identification systems (AIS). The risk rating combines the likelihood of an oil spill occurring from a vessel navigating in a study area – the Portuguese continental shelf – with the assessed consequences to the shoreline. The spill likelihood is based on dynamic marine weather conditions and statistical information from previous accidents. The shoreline consequences reflect the virtual spilled oil amount reaching shoreline and its environmental and socio-economic vulnerabilities. The oil reaching shoreline is quantified with an oil spill fate and behaviour model running multiple virtual spills from vessels along time, or as an alternative, a correction factor based on vessel distance from coast. Shoreline risks can be computed in real time or from previously obtained data. Results show the ability of the proposed methodology to estimate the risk properly sensitive to dynamic metocean conditions and to oil transport behaviour. The integration of meteo-oceanic + oil spill models with coastal vulnerability and AIS data in the quantification of risk enhances the maritime situational awareness and the decision support model, providing a more realistic approach in the assessment of shoreline impacts. The risk assessment from historical data can help finding typical risk patterns (“hot spots”) or developing sensitivity analysis to specific conditions, whereas real-time risk levels can be used in the prioritization of individual ships, geographical areas, strategic tug positioning and implementation of dynamic risk-based vessel traffic monitoring.

Dynamic Risk Assessment of Shoreline Contamination from Ships: Integrating an Oil Spill Model

2014 ◽  
Vol 2014 (1) ◽  
pp. 299678
Author(s):  
Rodrigo Fernandes ◽  
Filipe Lourenço ◽  
Frank Braunschweig ◽  
Ramiro Neves
Keyword(s):  
Risk Assessment ◽  
Real Time ◽  
Oil Spill ◽  
Numerical Models ◽  
Weather Conditions ◽  
Traffic Monitoring ◽  
Risk Levels ◽  
Dynamic Risk ◽  
Risk Algorithm ◽  
The Impact

Latest scientific and technological developments on coastal monitoring and operational oceanography have provided the opportunity of building complex and integrative decision support systems for coastal risk management. An innovative methodology to dynamically produce quantified risks has been developed, integrating numerical metocean forecasts and oil spill simulations with the existing monitoring tools. The risk rating combines the likelihood of an oil spill occurring from a vessel navigating in the study area with the assessed consequences to the shoreline. The spill likelihood is based on dynamic marine weather conditions and statistical information from previous accidents. The shoreline consequences reflect the associated oil amount reaching shoreline and the environmental and socio-economic vulnerabilities. The oil reaching shoreline is quantified with an oil spill fate and behavior model. Shoreline risk is variable in time, based on variable vessel positions (from AIS) and metocean conditions (from operational numerical models). The simultaneous calculation of the risk posed by each vessel crossing a study area is integrated, allowing the generation of a dynamic shoreline risk map for the study area. Shoreline risks can be computed in real time or from previous obtained data. The whole system has been implemented in real time on the Portuguese and Galician Coast. Since several ships cross this area, optimization was performed to allow running the oil spill model for multiple virtual spills from ships along time. The integrated oil spill model uses MOHID lagrangian particle tracking system, where all major transport and weathering processes are considered, including full 3D movement of oil particles, wave-induced currents, and a novel implementation of oil-shoreline interaction. The relevance of integrating the oil spill model in the risk algorithm is evaluated. To perform this, risk levels are compared considering the impact of virtual spilled oil reaching shoreline based on oil spill model simulations, or simply considering the vessel shoreline proximity as impact factor. The integration of an oil spill model in the shoreline risk levels, combined with adequate metocean modeling forecasts, allow a more realistic approach in the assessment of shoreline impacts, which can become even more important in case of regions with greater variability in marine weather conditions. The risk assessment from historic data can help finding typical risk patterns, “hot spots” or developing sensitivity analysis to specific conditions, whereas real time risk levels can be used in the prioritization of individual ships, geographical areas, strategic tug positioning and implementation of dynamic risk-based vessel traffic monitoring.

scholarly journals An unmanned aircraft system for maritime operations

2018 ◽  
Vol 15 (4) ◽  
pp. 172988141878633 ◽  
Author(s):  
Mario Monteiro Marques ◽  
Victor Lobo ◽  
R Batista ◽  
J Oliveira ◽  
A Pedro Aguiar ◽  
...  
Keyword(s):  
Collision Avoidance ◽  
Situational Awareness ◽  
Traffic Monitoring ◽  
Unmanned Aircraft ◽  
Automatic Identification ◽  
Identification System ◽  
Time Operation ◽  
Air System ◽  
Unmanned Air System ◽  
Aircraft System

Unmanned air systems are becoming ever more important in modern societies but raise a number of unresolved problems. There are legal issues with the operation of these vehicles in nonsegregated airspace, and a pressing requirement to solve these issues is the development and testing of reliable and safe mechanisms to avoid collision in flight. In this article, we describe a sense and avoid subsystem developed for a maritime patrol unmanned air system. The article starts with a description of the unmanned air system, that was developed specifically for maritime patrol operations, and proceeds with a discussion of possible ways to guarantee that the unmanned air system does not collide with other flying objects. In the system developed, the position of the unmanned air system is obtained by the global positioning system and that of other flying objects is reported via a data link with a ground control station. This assumes that the detection of those flying objects is done by a radar in the ground or by self-reporting via a traffic monitoring system (such as automatic identification system). The algorithm developed is based on game theory. The approach is to handle both the procedures, threat detection phase and collision avoidance maneuver, in a unified fashion, where the optimal command for each possible relative attitude of the obstacle is computed off-line, therefore requiring low processing power for real-time operation. This work was done under the research project named SEAGULL that aims to improve maritime situational awareness using fleets of unmanned air system, where collision avoidance becomes a major concern.

scholarly journals A Risk Assessment Tool for Resumption of Research Activities During the COVID-19 Pandemic

2020 ◽  
Author(s):  
Suzanne M Simkovich ◽  
Lisa M. Thompson ◽  
Maggie Clark ◽  
Kalpana Balakrishnan ◽  
Alejandra Bussalleu ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Research Team ◽  
Assessment Tool ◽  
Infection Risk ◽  
Protective Measures ◽  
Risk Levels ◽  
Risks And Benefits ◽  
Research Activities ◽  
Environmental Health Research ◽  
Need To Evaluate

Abstract Rationale: The spread of severe acute respiratory syndrome coronavirus-2 has suspended many non-COVID-19 related research activities. Where restarting research activities is permitted, investigators need to evaluate the risks and benefits of resuming data collection and adapt procedures to minimize risk. Objectives: In the context of the multicountry Household Air Pollution Intervention (HAPIN) trial, we developed a framework to assess the risk of each trial activity and to guide protective measures. Our goal is to maximize integrity of reseach aims while minimizing infection risk based on the latest understanding of the virus. Methods: We drew on a combination of expert consultations, risk assessment frameworks, institutional guidance and literature to develop our framework. We then systematically graded clinical, behavioral, laboratory and field environmental health research activities in four countries for both adult and child subjects using this framework. Results: Our framework assesses risk based on staff proximity to the participant, exposure time between staff and participants, and potential aerosolization while performing the activity. One of of four risk levels, from minimal to unacceptable, is assigned and guidance on protective measures is provided. Those activities which can potentially aerosolize the virus are deemed the highest risk. Conclusions: By applying a systematic, procedure-specific approach to risk assessment for each trial activity, we can compare trial activities using the same criteria. This approach allows us to protect our participants and research team and to uphold our ability to deliver on the research commitments we have made to our participants, local communities, and funders. The trial is registered with clinicaltrials.gov (NCT02944682).

scholarly journals Near Real-time S-AIS

Pomorstvo ◽  
2018 ◽  
Vol 31 (2) ◽  
pp. 211-218
Author(s):  
Davor Šakan ◽  
Igor Rudan ◽  
Srđan Žuškin ◽  
David Brčić
Keyword(s):  
Data Processing ◽  
Real Time ◽  
Service Providers ◽  
Traffic Monitoring ◽  
Environmental Research ◽  
Automatic Identification ◽  
Identification System ◽  
Maritime Industry ◽  
Recent Developments ◽  
Processing Techniques

The Automatic identification System (AIS) has been mainly designed to improve safety and efficiency of navigation, environmental protection, coastal traffic monitoring simplifying identification and communication. Additionally, historical AIS data have been used in many other areas of maritime safety, economic and environmental research. The probability of the detection of terrestrial AIS signals from space was presented in 2003, following the advancements in micro satellite technology. Through constant development, research and cooperation between governmental and private sectors, Satellite AIS (S-AIS) has been continuously evolving. Advancements in signal and data processing techniques have resulted in an improved detection over vast areas outside of terrestrial range. Some of the challenges of S-AIS technology include satellite revisit times, message collision and ship detection probability. Data processing latency and lacking the continuous real-time coverage made it less reliable for end user in certain aspects of monitoring and data analysis. Recent developments and improvements by leading S-AIS service providers have reduced latency issues. Complementing with terrestrial AIS and other technologies, near real-time S-AIS can further enhance all areas of the global maritime monitoring domain with emerging possibilities for maritime industry.

scholarly journals Development and Field Evaluation of a Spray Drift Risk Assessment Tool for Vineyard Spraying Application

Agriculture ◽  
2019 ◽  
Vol 9 (8) ◽  
pp. 181 ◽  
Author(s):  
Bourodimos ◽  
Koutsiaras ◽  
Psiroukis ◽  
Balafoutis ◽  
Fountas
Keyword(s):  
Risk Assessment ◽  
Assessment Tool ◽  
Plant Protection ◽  
Weather Forecast ◽  
Field Evaluation ◽  
Weather Conditions ◽  
Plant Protection Products ◽  
Meteorological Conditions ◽  
Spray Drift ◽  
Evaluation Tool

Spray drift is one of the most important causes of pollution from plant protection products and it puts the health of the environment, animals, and humans at risk. There is; thus, an urgent need to develop measures for its reduction. Among the factors that affect spray drift are the weather conditions during application of spraying. The objective of this study was to develop and evaluate a spray drift evaluation tool based on an existing model by TOPPS-Prowadis to improve the process of plant protection products’ application and to mitigate spray drift for specific meteorological conditions in Greece that are determined, based on weather forecast, by reassessing the limits for wind speed and direction, temperature, and air relative humidity set in the tool. The new limits were tested by conducting experimental work in the vineyard of the Agricultural University of Athens with a trailed air-assisted sprayer for bush and tree crops, using the ISO 22866:2005 methodology. The results showed that the limits set are consistent with the values of the spray drift measured and follows the tool’s estimates of low, medium, and high risk of spray drift.

Professional Discretion and the Predictive Validity of a Juvenile Risk Assessment Instrument

2016 ◽  
Vol 15 (2) ◽  
pp. 103-118 ◽  
Author(s):  
James T. McCafferty
Keyword(s):  
Risk Assessment ◽  
Predictive Validity ◽  
Assessment Tool ◽  
Assessment Instrument ◽  
Adjusted Risk ◽  
Risk Levels ◽  
Risk Assessment Instrument ◽  
Actuarial Risk ◽  
Using Data ◽  
The Impact

The ability for professionals to override the results of an actuarial risk assessment tool is an essential part of effective correctional risk classification; however, little is known about how this important function affects the predictive validity of these tools. Using data from a statewide sample of juveniles from Ohio, this study examined the impact of professional adjustments on the predictive validity of a juvenile risk assessment instrument. This study found that the original and adjusted risk levels were significant predictors of recidivism, but the original risk levels were stronger predictors of recidivism than the adjusted risk levels that accounted for overrides.

scholarly journals Near Real-time S-AIS

Pomorstvo ◽  
2018 ◽  
Vol 31 (1) ◽  
pp. 211-218 ◽  
Author(s):  
Davor Šakan ◽  
Igor Rudan ◽  
Srđan Žuškin ◽  
David Brčić
Keyword(s):  
Data Processing ◽  
Real Time ◽  
Service Providers ◽  
Traffic Monitoring ◽  
Environmental Research ◽  
Automatic Identification ◽  
Identification System ◽  
Maritime Industry ◽  
Recent Developments ◽  
Processing Techniques

The Automatic identification System (AIS) has been mainly designed to improve safety and efficiency of navigation, environmental protection, coastal traffic monitoring simplifying identification and communication. Additionally, historical AIS data have been used in many other areas of maritime safety, economic and environmental research. The probability of the detection of terrestrial AIS signals from space was presented in 2003, following the advancements in micro satellite technology. Through constant development, research and cooperation between governmental and private sectors, Satellite AIS (S-AIS) has been continuously evolving. Advancements in signal and data processing techniques have resulted in an improved detection over vast areas outside of terrestrial range. Some of the challenges of S-AIS technology include satellite revisit times, message collision and ship detection probability. Data processing latency and lacking the continuous real-time coverage made it less reliable for end user in certain aspects of monitoring and data analysis. Recent developments and improvements by leading S-AIS service providers have reduced latency issues. Complementing with terrestrial AIS and other technologies, near real-time S-AIS can further enhance all areas of the global maritime monitoring domain with emerging possibilities for maritime industry.

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