• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2013.10a
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• pp.69-70
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• 2013

IPCC (International Panel on Climate Change) reported that the arctic sea-ice extent has been decreased by 2.7% per decades since satellite observations in 1978. The decreased sea-ice extent has gained an international attention due to its economical benefits from the NSR (Northen Sea Route). The NRS - not a clearly defined single route, but a number of alternative routes across the top of Russiahas a 37 % reduction in sailing distance, comparing to the SSR (Southen Sea Route) passing thourgh the Suez Canal. Sailing days are consequently reduced from 30 days to 20 days. Also, it is estimated that the Northen Sea has 20 to 25% of world's oil resources and occupies 40% of the world's fishery production. As Republic of Korea was admitted as an observer to the Arctic Council on May 15, 2013, there has been increasing needs to explore new route in the Northen Sea. In this situation, Korea Institute of Ocean Science & Technology (KIOST) is preparing a plan for the development of Arctic-circle Ocean Environmental Information System to support the ice navigation and resource exploration in the Arctic. We will introduce a conceptual design of a satellite-based ice navigation supporting system for the northern sea route.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2019.08a
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• pp.246-246
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• 2019

• The Journal of Engineering Geology
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• v.31 no.4
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• pp.549-559
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• 2021

The Arctic Circle's huge amounts of fossil fuels and mineral resources are being developed and subjected to active construction projects. Global efforts are continuing to actively respond to climate change, but the dependence on fossil fuels remains high. This study reports a preliminary survey conducted in Alberta, Canada, where oil sand resources are actively developed. A land cover map was prepared using satellite imagery to reduce the cost and time of surveying a wide area. Results likely useful to resource development projects such as ground surface temperature and snow cover distribution were derived by using the obtained image classification results. It is expected that the results of the present research and analysis will be used to establish strategies for the successful promotion and operation of projects to develop resources in the Arctic.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2015.07a
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• pp.41-42
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• 2015

극해 지역은 채굴가능 매장량의 30% 정도의 각종 천연자원이 매장되어 있으며 기후변화로 인해 북극해 항로를 이용한 운항 및 자원의 수송과 저장을 위해 빙해 선박과 극지용 해양구조물의 수요가 증가하고 있다. 이 연구에서는 아이스 클라스 등 방한기술에 근거하여 빙해 선박에 탑재되는 루버의 기술개발 동향에 대해 고찰 하였다.

• The Safety technology
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• no.179
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• pp.15-17
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• 2012

극지(極地), 그곳은 말 그대로 '맨 끝에 있는 땅'이다. 흔히 남 북 양극지방을 통칭하는 말이기도 하다. 극지에 대한 일반 국민들의 관심은 2009년에 진수된 우리나라 최초의 쇄빙선 아라온호의 명성으로 극대화됐다. 거기에 얼마 전 TV 다큐멘터리 '남극의 눈물' 방영도 일반인들에게 극지에 대한 친숙함과 이해를 높이는 데 한몫 했다. 얼음과 눈, 그리고 살을 에는 추위뿐인 동토의 땅에서 대한민국 태극기를 펄럭이며 극지의 모든 것에 대해 연구하는 과학기지가 있다. 바로 남극 세종과학기지와 2014년 완공되는 장보고과학기지, 그리고 북극의 다산과학기지다. 인천광역시 연수구 송도동에 자리 잡은 극지연구소(KOPRI, Korea Polar Research Institute)는 극지와 그 관련지역에서의 기초 및 첨단 응용과학 연구, 남 북극 과학기지 운영 등을 지원하는 극지 전문기관으로, 국토해양부 한국해양과학기술원 부설기관이다. 이곳은 우리나라 유일의 극지연구전문기관으로, 미래의 기후 변화와 무한한 생물종을 연구하는 과학자들의 열의가 대단하다. 그 뜨거운 열기의 중심에는 바로 안전이 자리 잡고 있다. '극지'라는 특수지역을 무대로 삼아 국가적인 연구를 수행하고 있는 만큼 '안전'은 연구 활동을 뒷받침 하는 주춧돌이자 왕성한 연구활동을 이어나갈 수 있게 하는 원동력이 되고 있다. 안전을 위시해 전문적인 극지 연구를 하고 있는 이곳, 극지연구소만의 특별한 안전관리 현장을 찾아가봤다.

• Korean Journal of Remote Sensing
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• v.33 no.6_1
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• pp.901-915
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• 2017

Recently, global climate change has caused a catastrophic event in the Arctic Ocean, directly and indirectly. The air-sea interaction has caused the significant sea-ice reduction in the Arctic Ocean, and has been accelerating the Arctic warming. Many scientists are worried about the Arctic environment change, suggesting that many of anomalous events will produce direct or indirect biophysical effects on the Arctic. The aim of this study is to understand the inter-annual variability of the Arctic Ocean in wide-view using multi-satellite-derived measurements. Sea surface temperature (SST) and sea ice concentration (SIC) data were obtained from Optimum Interpolation Sea Surface Temperature (OISST) and ECMWF ERA-Interim, respectively. Chlorophyll-a concentration (CHL) was obtained from Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) and Aqua sensor from MODerate resolution Imaging Spectroradiometer (MODIS-Aqua) sensor which has continuously observed since 1998. From 1998 to 2016 summer in the Arctic Ocean which was defined as regions over $60^{\circ}N$ in this study, there were three consequences that CHL increase ($0.15mg\;m^{-3}\;decade^{-1}$), SST warming ($0.43^{\circ}C\;decade^{-1}$) and SIC decrease ($-5.37%\;decade^{-1}$). While SST and SIC highly correlated each other (r = -0.76), a relationship between CHL and SIC was very low ($r={\pm}0.1$) because of data limitations. And a relationship between CHL and SST shows meaningful results ($r={\pm}0.66$) with regional differences.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.12 no.2
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• pp.61-72
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• 2007

The relationship between North Pacific chum salmon (Oncorhynchus keta) population and climate variability was investigated in the North Pacific ecosystem. Time-series for the Aleutian Low Pressure, Southern Oscillation, Arctic Oscillation, and Pacific Decadal Oscillation (PDO) indices dating back to 1950 are compared with the chum salmon catch using a cross-correlation function (CCF) and cumulative sum (CuSum) of anomalies. The results of CCF and CuSum analyses indicated that there was a major change in climate during the mid 1970s, and that the chum salmon population responded to this climate event with a time-lag. The PDO and chum salmon returns showed a highly significant correlation with a time-lag of 3 years, while the AOI with a time-lag of $6{\sim}7$ years. The favorable environments for fry chum salmon might cause better growth in the coastal areas, but higher growth rate during the early stage does not seem to be related to the improved return rate of spawning adults. Rather, growth in the Okhotsk Sea or the Bering Sea during immature stages has a significant correlation with return rate, which implies the size-related mortality process. The development of a local climate index is necessary to elucidate the effect of climate variability on the marine ecosystem around the Korean Peninsula.

• Journal of the Korean Geographical Society
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• v.43 no.1
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• pp.1-19
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• 2008

This study intends to clarify the characteristics and causes of current changes in wintertime precipitation in Korea and to predict the future directions based on surface observational $(1973/04\sim2006/07)$ and modeled (GFDL 2.1) climate data. Analyses of surface observation data demonstrate that without changes in the total amount of precipitation, snowfall in winter (November-April) has reduced by 4.3cm/decade over the $1973\sim2007$ period. Moreover, the frequency and intensity of snowfall have decreased; the duration of snow season has shortened; and the snow-to-rain day ratio (STDR) has decreased. These patterns indicate that the type of wintertime precipitation has changed from snow to rain in recent decades. The snow-to-rain change in winter is associated with the increases of air temperature (AT) over South Korea. Analyses of synoptic charts reveal that the warming pattern is associated with the formation of a positive pressure anomaly core over northeast Asia by a hemispheric positive winter Arctic Oscillation (AO) mode. Moreover, the differentiated warming of AT versus sea surface temperature (SST) under the high pressure anomaly core reduces the air-sea temperature gradient, and subsequently it increases the atmospheric stability above oceans, which is associated with less formation of snow cloud. Comparisons of modeled data between torrent $(1981\sim2000)$ and future $(2081\sim2100)$ periods suggest that the intensified warming with larger anthropogenic greenhouse gas emission in the $21^{st}$ century will amplify the magnitude of these changes. More reduction of snow impossible days as well as more abbreviation of snow seasons is predicted in the $21^{st}$ century.

• Korean Journal of Remote Sensing
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• v.30 no.6
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• pp.809-816
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• 2014

Ocean Color products have been used to understand marine ecosystem. In high latitude region, ice melting optically influences the ocean color products. In this study, we assessed optical properties in fjord around Svalbard Arctic sea, and estimated distribution of chlorophyll-a and suspended sediment by using high resolution satellite data, Landsat-8 Operational Land Imager (OLI). To estimate chlorophyll-a and suspended sediment concentrations, various regression models were tested with different band ratio. The regression models were not shown high correlation because of temporal difference between satellite data and in-situ data. However, model-derived distribution of ocean color products from OLI showed a possibility that fjord and coastal areas around Arctic Sea can be monitored with high resolution satellite data. To understand climate change pattern around Arctic Sea, we need to understand ice meting influences on marine ecosystem change. Results of this study will be used to high resolution monitoring of ice melting and its influences on the marine ecosystem change at high latitude. KOPRI (Korea Polar Research Institute) has been operated the Dasan station on Svalbard since 2002, and study was conducted using Arctic station.

• 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.