• Proceedings of KOSOMES biannual meeting
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• 2006.05a
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• pp.41-45
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• 2006

From the 1978 Seasat synthetic aperture radar(SAR) to present systems, spaceborne SAR has demonstrated the capability to image the Earth's ocean and land features over broad areas, day and night, and under most weather conditions. The application of SAR for surveillance of commercial fishing grounds can did in the detection of illegal fishing activities and provides more efficient use cf limited aircraft or patron craft resources. In the area of vessel traffic monitoring for commercial vessels, Vessel Traffic Service (VTS) which uses the ground-based radar system has some difficulties in detecting moving ships due to the limited detection range cf about 10 miles. This paper introduces the field testing results of ship detection by RADARSAT SAR imagery, and proposes a new approach for a Vessel Monitoring System(VMS), including VTS, and SAR combination service.

• Proceedings of KOSOMES biannual meeting
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• 2007.05a
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• pp.127-132
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• 2007

From the 1978 Seasat synthetic aperture radar(SAR) to present systems, spaceborne SAR has demonstrated the capability to image the Earth's ocean and land features over broad areas, day and night, and under most weather conditions. The application of SAR for surveillance of commercial fishing grounds can aid in the detection of illegal fishing activities and provides more efficient use of limited aircraft or patrol craft resources. In the area of vessel traffic monitoring for commercial vessels, Vessel Traffic Service (VTS) which uses the ground-based radar system has some difficulties in detecting moving ships due to the limited detection range of about 10 miles. This paper introduces the field testing results of ship detection by RADARSAT SAR imagery, and proposes a new approach for a Vessel Monitoring System(VMS), including VTS, and SAR combination service.

• Proceedings of KOSOMES biannual meeting
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• 2017.04a
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• pp.19-19
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• 2017

• Journal of Navigation and Port Research
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• v.34 no.2
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• pp.91-95
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• 2010

Recently IMO and IALA have developed the strategy of e-Navigation and the concepts of VTM to enhance the safety, efficiency and security of vessel traffic and protection of the marine environment. And current technical and functional trends require vessel traffic management systems to be improved so as to control vessel traffic not only in waters of harbour area, but also within EEZ waters. Under the consideration of these circumstances, a three-layered vessel traffic management system was proposed in this paper. The proposed system consists of three sub-systems, called Local VTS, Regional VTS and National VTS, and those sub-systems are designed respectively to be suitable for managing vessel traffic within their own jurisdiction waters.

• Journal of the Korean Society of Marine Environment & Safety
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• v.23 no.2
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• pp.153-160
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• 2017

It may be reasonable to consider density per unit area over time rather than analyze traffic volume, which is simply the traffic volume per unit of time, in assessing the maritime traffic congestion of a certain area. This study contributes to the standardization of maritime traffic congestion assessment methods for the maritime traffic safety diagnosis institute while seeking a new method to minimize evaluation error due to converted traffic volume per ship tonnage level. To solve this problem, a method to evaluate maritime traffic congestion by comparing the area occupied by a vessel with the area of its route using vessel identification data from the Automatic Identification System (AIS) has been proposed. In this new model, it is possible to use actual data due to the development of information and communication technology, reducing conversion error while allowing for the evaluation of maritime traffic congestion by route.

• Journal of the Korean Society of Marine Environment & Safety
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• v.21 no.3
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• pp.253-258
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• 2015

The purpose of this study is to find suitable probability distribution function of complex distribution data like multimodal. Normal distribution is broadly used to assume probability distribution function. However, complex distribution data like multimodal are very hard to be estimated by using normal distribution function only, and there might be errors when other distribution functions including normal distribution function are used. In this study, we experimented to find fit probability distribution function in multimodal area, by using AIS(Automatic Identification System) observation data gathered in Mokpo port for a year of 2013. By using chi-squared statistic, gaussian mixture model(GMM) is the fittest model rather than other distribution functions, such as extreme value, generalized extreme value, logistic, and normal distribution. GMM was found to the fit model regard to multimodal data of maritime traffic flow distribution. Probability density function for collision probability and traffic flow distribution will be calculated much precisely in the future.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.53 no.4
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• pp.423-429
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• 2017

As invigoration plan of the marine tourism, Busan City has the plan to operate the cruise ship inside of the harbor, but the area has narrow water way with heavy traffic. As a result it is requested to evaluate the safety for the preparation of actual navigation. In this study, the Ship Handling Simulation (SHS) Assessment was conducted, which is regulated by the Maritime Traffic Safety Audit Scheme (MTSAS) in compliance with the Marine Safety Law and the Maritime Traffic Risk Assessment System based on the Electronic Chart Display and Information System (ECDIS). The proximity assessment, control assessment and subjective assessment were implemented, which is enacted by the Marine Safety Law by using the SHS. In the case of proximity assessment, the probability of trespass was not analyzed. As the control assessment, the swept path was measured at 11.7 m and 11.5 m for port entry and port departure respectively, which exceeded the width of the model vessel, 10.4 m over; it was considered as a marginal factor. As a result of the subjective evaluation of the navigator, there would be no difficulty on ship maneuvering by paying particular attention to the mooring vessel nearby the Busan Bridge and Yeongdo Bridge as well as the coming vessel from the invisible sea area when the vessel is entering and departing the port. The Marine Traffic Risk Assessment System analyzed as [Cautious] level until the vessel passed the Busan bridge and the curved area at 5 kts and it became to [Dangerous] level from where it left 75 m to the Busan Bridge. When the vessel passed the Busan Bridge and the curved area at 10 kts and entered the narrow area, it indicated the [Dangerous] level and became to [Very dangerous] level from where it left 410 m to the Busan bridge. In conclusion, the vessel should maintain at the speed of 5 kts to reduce the risk when it passes this area.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.5
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• pp.780-790
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• 2022

Quantitative risk levels must be presented by analyzing the causes and consequences of accidents and predicting the occurrence patterns of the accidents. For the analysis of marine accidents related to vessel traffic, research on the traffic such as collision risk analysis and navigational path finding has been mainly conducted. The analysis of the occurrence pattern of marine accidents has been presented according to the traditional statistical analysis. This study intends to present a marine accident prediction model using the statistics on marine accidents related to vessel traffic. Statistical data from 1998 to 2021, which can be accumulated by month and hourly data among the Korean domestic marine accidents, were converted into structured time series data. The predictive model was built using a long short-term memory network, which is a representative artificial intelligence model. As a result of verifying the performance of the proposed model through the validation data, the RMSEs were noted to be 52.5471 and 126.5893 in the initial neural network model, and as a result of the updated model with observed datasets, the RMSEs were improved to 31.3680 and 36.3967, respectively. Based on the proposed model, the occurrence pattern of marine accidents could be predicted by learning the features of various marine accidents. In further research, a quantitative presentation of the risk of marine accidents and the development of region-based hazard maps are required.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2015.07a
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• pp.18-20
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• 2015

In ports of Korea, the marine traffic flow is congested due to a large number of vessels coming in and going out. In order to improve the safety and efficiency of these vessels, South Korea is operating with a Vessel Traffic System, which is monitoring its waters 24-7. However despite these efforts of the VTS (Vessel Traffic System) officers, marine accidents are occurring in their assigned districts and it is made a danger situation every 20minute. On this paper, we listened to Busan VHF channel for 3days and applied to collision risk model. With collision risk model, We deducted a moment which advise or recommend to vessel. We suggested a collision risk model as VTSO support system.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.3
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• pp.239-245
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• 2016

In the midst of continuing international recession, the rate of maritime traffic and marine leisure markets are consistently growing. The Republic of Korea controls the marine traffic volume through vessel traffic centers and various other management facilities. Nevertheless, the continuous growth and complexity of marine traffic is resulting in repeated occurrences of marine accidents. Recovery is very difficult in cases of human injuries or deaths caused by marine accidents due to its nature, and the scale of marine accidents is also becoming greater with advanced ship building technologies. Passenger ships, oil tankers, and other such vessels used for specific purposes requires a more detailed navigational status surveillance and analysis, and numerous research has been conducted with an objective for monitoring such special purpose vessels. However, the data elements transmitted from the ocean to the shore station are limited to AIS and ARPA. We are implementing IoT ship sensor collection and a syncing system capable of transmitting various ship sensing data to the shore station, and also proposing a Safe Navigation Status Analysis System utilizing the collected data.