• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1463-1478
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• 2022

Maritime transport accounts for 99.7% of the exports and imports of the Republic of Korea; therefore, developing a vessel monitoring system for efficient operation is of significant interest. Several studies have focused on tracking and monitoring vessel movements based on automatic identification system (AIS) data; however, ships without AIS have limited monitoring and tracking ability. High-resolution optical satellite images can provide the missing layer of information in AIS-based monitoring systems because they can identify non-AIS vessels and small ships over a wide range. Therefore, it is necessary to investigate vessel monitoring and small vessel classification systems using high-resolution optical satellite images. This study examined the possibility of developing ship monitoring systems using Compact Advanced Satellite 500-1 (CAS500-1) satellite images by first training a deep learning model using satellite image data and then performing detection in other images. To determine the effectiveness of the proposed method, the learning data was acquired from ships in the Yellow Sea and its major ports, and the detection model was established using the You Only Look Once (YOLO) algorithm. The ship detection performance was evaluated for a domestic and an international port. The results obtained using the detection model in ships in the anchorage and berth areas were compared with the ship classification information obtained using AIS, and an accuracy of 85.5% and 70% was achieved using domestic and international classification models, respectively. The results indicate that high-resolution satellite images can be used in mooring ships for vessel monitoring. The developed approach can potentially be used in vessel tracking and monitoring systems at major ports around the world if the accuracy of the detection model is improved through continuous learning data construction.

• Journal of Korean Port Research
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• v.12 no.1
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• pp.35-46
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• 1998

The CY can be said to function in various respect as a buffer zone between the maritime and overland inflow-outflow of container. The amount of storage area needed requires a very critical appraisal at pre-operational stage. A container terminal should be designed to handle and store containers in the most efficient and economic way possible. In order to achieve this aim it is necessary to figure out or forecast numbers and types of containers to be handled, CY area required, and internal handling systems to be adopted. This paper aims to calculate the CY area required for each container handling system in Mokpo New Port. The CY area required are directly dependent on the equipment being used and the storage demand. And also the CY area required depends on the dwell time. Furthermore, containers need to be segregated by destination, weight, class, FCL(full container load), LCL(less than container load), direction of travel, and sometimes by type and often by shipping line or service. Thus the full use of a storage area is not always possible as major unbalances and fluctuations in these flow occuring all the time. The calculating CY area must therefore be taken into account in terms of these operational factors. For solving such problem, all these factors have been applied to estimation of CY area in Mokpo New Port. The CY area required in Mokpo New Port was summarized in the conclusion section.