• Korean Journal of Remote Sensing
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• v.35 no.6_1
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• pp.999-1009
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• 2019

The importance of high-resolution sea ice maps of the Arctic Ocean is increasing due to the possibility of pioneering North Pole Routes and the necessity of precise climate prediction models. In this study,sea ice classification algorithms for two deep learning models were examined using Sentinel-1 A/B SAR data to generate high-resolution sea ice classification maps. Based on current ice charts, three classes (Open Water, First Year Ice, Multi Year Ice) of training data sets were generated by Arctic sea ice and remote sensing experts. Ten sea ice classification algorithms were generated by combing two deep learning models (i.e. Simple CNN and Resnet50) and five cases of input bands including incident angles and thermal noise corrected HV bands. For the ten algorithms, analyses were performed by comparing classification results with ground truth points. A confusion matrix and Cohen's kappa coefficient were produced for the case that showed best result. Furthermore, the classification result with the Maximum Likelihood Classifier that has been traditionally employed to classify sea ice. In conclusion, the Convolutional Neural Network case, which has two convolution layers and two max pooling layers, with HV and incident angle input bands shows classification accuracy of 96.66%, and Cohen's kappa coefficient of 0.9499. All deep learning cases shows better classification accuracy than the classification result of the Maximum Likelihood Classifier.

• Korean Journal of Remote Sensing
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• v.25 no.5
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• pp.423-434
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• 2009

The Arctic environment is sensitive to change of sea-ice distribution. The increase and decrease of sea ice work to an index of globe warming progress. In order to predict the progress of hereafter earth global warming, continuous monitoring regarding a change of the sea ice area in the Arctic should be performed. The remote sensing based on an artificial satellite is most effective on the North Pole. The sea ice observation using a passive microwave sensor has been continued from 1970's. The determination of sea ice extent and ice type is one of the great successes of the passive microwave imagers. In this paper, to investigate the seasonal and inter-annual variation of sea-ice distribution we used here the sea ice data from July 2002 to May 2009 around the Arctic within $60^{\circ}N$ for the AMSR-E 12.5km sea-ice concentration, a passive microwave sensor. From an early analysis of these data, the arctic sea-ice extent has been steadily decreasing at a rate of about 3.1%, accounting for about $2{\times}10^5\;km^2$, which was calculated for the sea-ice cover reaching its minimum extent at the end of each summer. It is also revealed that this trend corresponds to a decline in the multi-year ice that is affected mainly by summer sea surface and air temperature increases. The extent of younger and thinner (first-year) ice decreased to the 2007 minimum, but rapidly recovered in 2008 and 2009 due to the dramatic loss in 2007. Seasonal variations of the sea-ice extent show significant year-to-year variation in the seasons of January-March in the Barents and Labrador seas and August-October in the region from the East Siberian and Chukchi seas to the North Pole. The spatial distribution of multi-year ice (7-year old) indicates that the perennial ice fraction has rapidly shrunk recently out of the East Siberian, Laptev, and Kara seas to the high region of the Arctic within the last seven years and the Northeast Passage could become open year-round in near future.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1245-1255
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• 2022

Terra Nova Bay polynya (TNBP) is a representative coastal polynya in East Antarctica, which is formed by strong katabatic winds. As the TNBP is one of the major sea ice factory in East Antarctica and has a great impact on regional ocean circulation and surrounding marine ecosystem, it is very important to analyze its area change and development characteristics. In this study, we detected the TNBP from synthetic aperture radar (SAR) and optical images obtained from April 2007 to April 2022 by visually analyzing the stripes caused by the Langmuir circulation effect and the boundary between the polynya and surrounding sea ice. Then, we analyzed the area change and development characteristics of the TNBP. The TNBP occurred frequently but in a small size during the Antarctic winter (April-July) when strong katabatic winds blow, whereas it developed in a large size in March and November when sea ice thickness is thin. The 12-hour mean wind speed before the satellite observations showed a correlation coefficient of 0.577 with the TNBP area. This represents that wind has a significant effect on the formation of TNBP, and that other environmental factors might also affect its development process. The direction of TNBP expansion was predominantly determined by the wind direction and was partially influenced by the local ocean current. The results of this study suggest that the influences of environmental factors related to wind, sea ice, ocean, and atmosphere should be analyzed in combination to identify the development characteristics of TNBP.

• Journal of Ocean Engineering and Technology
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• v.25 no.2
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• pp.55-61
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• 2011

A field trial in an ice-covered sea is one of the most important tasks in the design of icebreaking ships and offshore structures. To correctly estimate the ice load and ice resistance of a ship's hull, it is essential to understand the material properties of sea ice during ice field trials and to use the proper experimental procedure for gathering effective ice data. The first Korean-made icebreaking research vessel, "ARAON," had her second sea ice trial in the Arctic Ocean during the summer season of 2010. This paper describes the test procedures used to obtain proper sea ice data, which provides the basic information for the ship's performance in an ice-covered sea and is used to estimate the correct ice load and ice resistance of the IBRV ARAON. The data gathered from the sea ice in the Chukchi Sea and Beaufort Sea during the Arctic voyage of the ARAON includes the temperature, density, and salinity of the sea ice, which was believed to be from two-year old ice floes. This paper analyses the gathered sea ice data in comparison with data from the first voyage of the ARAON during her Antarctic Sea ice trial.

• Journal of the Society of Naval Architects of Korea
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• v.49 no.1
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• pp.45-51
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• 2012

Sea ice properties have been considered a key indicator in the structural design criteria of icebreaking vessels and arctic offshore platforms to estimate design ice load and resistance for their safety management in Arctic Ocean. A measurement study of sea ice properties was conducted during July to August of 2011 with the Korean icebreaking research vessel "Araon" around Chukchi Borderland. The sea ice concentration appears to be rapidly decreasing during this cruise. Ice condition seems to be thick second-year ice and multi-year ice and then, a lot of melt ponds were observed in the surface of ice floe. Calculated flexural strength of sea ice was about 250~550kPa, ice thickness was roughly 1.3~3.0m. In this research we performed field experiment to measure ice temperature along the depth, thickness, density, salinity, brine volume ratio and crystal structure. Apparent conductivities derived with the electromagnetic induction instrument were compared to drill hole measurement results and accuracy of sea ice thickness estimation formula was discussed.

• Journal of the Society of Naval Architects of Korea
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• v.48 no.3
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• pp.254-259
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• 2011

The first Korean-made icebreaking research vessel "ARAON" had her second sea ice trial in the Arctic Ocean in Aug. 2010 after her first voyage to Antarctic Ocean in Jan. 2010 to gather various material and strength characteristics of sea ice. This is a detail report of ARAON 2010 summer Arctic voyage and this paper describes a standard test procedure to obtain proper sea ice data which provide basic information to estimate ice loads and icebreaking performance of the ship. The data gathered from sea ice in the Chukchi Sea and Beaufort Sea during the Arctic voyage of the ARAON includes ice temperature/salinity and the compressive/flexural strength of sea ice. This paper analyses the gathered sea ice data in comparison with data from the first voyage of the ARAON during her Antarctic Sea ice trial.

• Korean Journal of Remote Sensing
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• v.33 no.2
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• pp.243-248
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• 2017

Sea ice which is an important component of the global climate system is being actively detected by satellite because it have been distributed to polar and high-latitude region. and the sea ice detection method using satellite uses reflectance and temperature data. the sea ice detection method of Moderate-Resolution Imaging Spectroradiometer (MODIS), which is a technique utilizing Ice Surface Temperature (IST) have been utilized by many studies. In this study, we propose a simple and effective method of sea ice detection using the dynamic threshold technique with no IST calculation process. In order to specify the dynamic threshold, pixels with freezing point of MODIS IST of 273.0 K or less were extracted. For the extracted pixels, we analyzed the relationship between MODIS IST, MODIS $11{\mu}m$ channel brightness temperature($T_{11{\mu}m}$) and Brightness Temperature Difference ($BTD:T_{11{\mu}m}-T_{12{\mu}m}$). As a result of the analysis, the relationship between the three values showed a linear characteristic and the threshold value was designated by using this. In the case ofsea ice detection, if $T_{11{\mu}m}$ is below the specified threshold value, it is detected as sea ice on clear sky. And in order to estimate the performance of the proposed sea ice detection method, the accuracy was analyzed using MODIS Sea ice extent and then validation accuracy was higher than 99% in Producer Accuracy (PA).

• Journal of Ocean Engineering and Technology
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• v.26 no.1
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• pp.1-8
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• 2012

To correctly estimate ice load and ice resistance for a ship's hull, it is essential to understand the material properties of sea ice during ice field trials and to use the proper experimental procedure for gathering ice strength data. The first Korean-made icebreaking research vessel (IBRV), ARAON, had her second sea ice trial in the Arctic Ocean during July and August of 2010. This paper describes the test procedures used to properly obtain sea ice strength data, which provides the basic information on the ship's performance in an ice-covered sea and can be used to estimate the correct ice load and ice resistance on the IBRV ARAON. The data gathered from three sea ice field trials during the Arctic voyage of the ARAON includes the ice compressive strength, flexural strength, and failure strain of sea ice. This paper analyzes the gathered sea ice data in comparison with data from the first voyage of the ARAON during her Antarctic Sea ice trial in January 2010.

• Journal of the Society of Naval Architects of Korea
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• v.51 no.3
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• pp.254-258
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• 2014

Field trial in ice-covered sea is one of the most important tasks in the design of icebreaking ships. To correctly estimate ice load and ice resistance on ship's hull, It is essential to understand the material properties of sea ice during ice field trials and to perform the proper experimental procedure by gathering sea ice data. A measurement of sea ice properties was conducted during February and March of 2012 with the Korean Icebreaking research vessel "ARAON" in the Amundsen Sea, Antarctica. This paper describes a test procedure to obtain sea ice data which provide basic information to estimate ice loads and icebreaking performance of the ship. The data gathered from sea ice field trials during the 2012 Antarctic voyage of the ARAON includes ice temperature/salinity/density and the compressive/flexural strength of sea ice. This paper analyses the gathered Antarctic sea ice material properties comparing with the previous data obtained during ARAON's Arctic and Antarctic voyages in 2010.

• Korean Journal of Mineralogy and Petrology
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• v.34 no.1
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• pp.15-29
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• 2021

In the Arctic Ocean, the distribution of sea ice and ice sheets changes as climate changes. Because the distribution of ice cover influences the mineral composition of marine sediments, studying marine sediments transported by sea ice or iceberg is very important to understand the global climate change. This study analyzes marine sediment samples collected from the Arctic Ocean and infers the provenance of the sediments to reconstruct the paleoenvironment changes of the western Arctic. The analyzed samples include four gravity cores collected from the Araon mound in the Chukchi Plateau and one gravity core collected from the slope between the Araon mounds. The core sediments were brown, gray, and greenish gray, each of which corresponds to the characteristic color of sediments deposited during the interglacial/glacial cycle in the western Arctic Ocean. We divide the core sediments into three units based on the analysis of bulk mineral composition, clay mineral composition, and Ice Rafted Debris (IRD) as well as comparison with previous study results. Unit 3 sediments, deposited during the last glacial maximum, were transported by sea ice and currents after the sediments of the Kolyma and Indigirka Rivers were deposited on the continental shelf of the East Siberian Sea. Unit 2 sediments, deposited during the deglacial period, were from the Kolyma and Indigirka Rivers flowing into the East Siberian Sea as well as from the Mackenzie River and the Canadian Archipelago flowing into the Beaufort Sea. Unit 2 sediments also contained an extensive amount of IRD, which originated from the melted Laurentide Ice Sheet. During the interglacial stage, fine-grained sediments of Unit 1 were transported by sea ice and currents from Northern Canada and the East Siberian Sea, but coarse-grained sediments were derived by sea ice from the Canadian Archipelago.