• Proceedings of the KSRS Conference
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• 2009.03a
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• pp.143-146
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• 2009

다산기지 주변 해역인 스발바드섬은 북반구 해빙 분포지역의 가장자리에 위치해 있으며 해빙의 이동이 비교적 빠른 지역이다. 지구 온난화의 영향을 받는 대표적인 지역으로 이 지역의 해빙변화에 대한 연구는 지구온난화의 지표로서 중요성을 가진다. 스발바드섬 주변의 해빙에서 얻어진 다편파 SAR 데이터를 분석하여 해빙에 대한 후방산란계수의 특성을 분석하고자 한다. 데이터 획득에는 ENVISAT/ASAR (2002 년 발사 C-밴드, 다편파 사용)과 PALSAR (2006 년 발사, L-밴드, 다편파 사용)의 두 가지 SAR 가 이용되었으며 데이터 획득 시기는 해빙의 변화가 활발한 4 월경이다. 기본적으로 L-밴드와 C-밴드의 두 가지 밴드별 차이에 관한 특성을 알아보고 기타 후방산란계수에 영향을 주는 요소들에 대하여 알아보고자 한다.

• Environmental and Resource Economics Review
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• v.18 no.4
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• pp.787-813
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• 2009

Because of global warming, the thawing of the Arctic ice cap is slowly accelerating. That is the hot issue nowadays. According to the each country's climate change policy, it is boom in the world to lessen the consuming of the fossil fuel those are oil, coal and natural gas. But on the contrary the thawing of the Arctic ice cap is the chance to make the natural gas producing unit cost lower. The purpose of this paper is to search the Arctic policy of each country under the contradictory relationship between promoting the climate change policy and exploiting the natural gas on the Arctic. Specially, there are huge natural gas reserves in Russia on the Arctic region, Russia's exploiting the natural gas on the Arctic will affect on the natural gas supply-demand balance of world natural gas market strongly in the future. Therefore it needs to prepare the future energy alternative policy for Korea's energy security. Russia has Yamal Peninsular where is abundant on natural gas reserver, and she can supply natural gas by LNG ship all over the world via the Arctic route. This means that the structure of world natural gas market be changed gradually. It will be possible in 2030~2040. And such a change is very important because new natural gas trading type can do it through not only overcoming the geological restriction but also shifting the main trading type from PNG(Pipeline Natural Gas) to LNG(Liquified Natural Gas). Therefore it is necessary that we should let this be a good lesson to ourselves through the government action of other countries (China, Japan) those also have no sovereignty over the Arctic as Korea.

• Korean Journal of Remote Sensing
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• v.34 no.6_2
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• pp.1251-1260
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• 2018

High-quality sea-ice surface models generated from aerial images can be used effectively as field data for developing satellite-based remote sensing methods but also as analysis data for understanding geometric variations of Arctic sea-ice. However, the lack of texture information on sea-ice surfaces can reduce the accuracy of image matching. In this paper, we analyze the performance of matching cost functions for homogeneous sea-ice surfaces as a part of high-quality sea-ice surface model generation. The matching cost functions include sum of squared differences (SSD), normalized cross-correlation (NCC), and zero-mean normalized cross-correlation (ZNCC) in image domain and phase correlation (PC), orientation correlation (OC), and gradient correlation (GC) in frequency domain. In order to analyze the matching performance for texture changes clearly and objectively, a new evaluation methodology based on the principle of object-space matching technique was introduced. Experimental results showed that it is possible to secure reliability and accuracy of image matching only when optimal search windows are variably applied to each matching point in textureless regions such as sea-ice surfaces. Among the matching cost functions, NCC and ZNCC showed the best performance for texture changes.

• Korean Journal of Remote Sensing
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• v.34 no.6_2
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• pp.1239-1249
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• 2018

Optical remote sensing sensors provide visually more familiar images than radar images. However, it is difficult to discriminate sea ice types in optical images using spectral information based machine learning algorithms. This study addresses two topics. First, we propose a semantic segmentation which is a part of the state-of-the-art deep learning algorithms to identify ice types by learning hierarchical and spatial features of sea ice. Second, we propose a new approach by combining of semi-supervised and active learning to obtain accurate and meaningful labels from unlabeled or unseen images to improve the performance of supervised classification for multiple images. Therefore, we successfully added new labels from unlabeled data to automatically update the semantic segmentation model. This should be noted that an operational system to generate ice type products from optical remote sensing data may be possible in the near future.

• Korean Journal of Remote Sensing
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• v.34 no.6_2
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• pp.1229-1238
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• 2018

We examined if a state of sea-ice in Bering Sea acts as a prelude of variation in that of Chukchi Sea by using satellites-based Arctic sea-ice concentration time series. Datasets consist of monthly values of sea-ice concentration during 36 years (1982-2017). Time series analysis armed with Transfer entropy is performed to describe how sea-ice data in Chukchi Sea is affected by that in Bering Sea, and to explain the relationship. The transfer entropy is a measure which identifies a nonlinear coupling between two random variables or signals and estimates causality using modification of time delay. We verified this measure checked a nonlinear coupling for simulated signals. With sea-ice concentration datasets, we found that sea-ice in Bering Sea is influenced by that in Chukchi Sea 3, 5, 6 months ago through the transfer entropy measure suitable for nonlinear system. Particularly, when a sea-ice concentration of Bering Sea has a local minimum, sea ice concentration around Chukchi Sea tends to decline 5 months later with about 70% chance. This finding is considered to be a process that inflow of Pacific water through Bering strait reduces sea-ice in Chukchi Sea after lowering the concentration of sea-ice in Bering Sea. This approach based on information theory will continue to investigate a timing and time scale of interesting patterns, and thus, a coupling inherent in sea-ice concentration of two remote areas will be verified by studying ocean-atmosphere patterns or events in the period.

• Korean Journal of Remote Sensing
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• v.33 no.3
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• pp.333-338
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• 2017

We compared sea ice concentration(SIC) and sea ice extent(SIE) using EUMETSAT Ocean and Sea Ice Satellite Application Facilities(OSI SAF) and NASA Team(NT) sea ice algorithm in the Arctic during 1980-2010 to investigate the difference between sea ice data applied different algorithms. SIC and SIE of the two data showed different consistency by season and by sea area. Seasonally, SIC of OSI SAF was 0.85 % overall, 0.48 % in spring, 0.97 % in summer, 1.38 % in autumn and 0.66 % in winter higher than NT SIC. By sea area, OSI SAF SIC was 2.7 %, SIE was $198,000km^2$ higher than NT in Arctic Ocean, but in Lincoln Sea, OSI SAF SIC was 2.3 %, SIE was $20,000km^2$ lower than NT.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2018.11a
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• pp.173-174
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• 2018

온난화 현상으로 북극 해빙 속도가 가속화되면서 북극 운항 선박이 증가하고 있어 선박의 안전 항해를 위한 기술개발이 요구되고 있다. 본 연구에서는 선박해양플랜트연구소에서 개발 중인 KRISO Arctic Safe Routing System(KARS)의 안전 최적항로 계획 방법의 선박실 운항 추진성능 모델 과 선박 고유의 빙 저항 추진 성능 데이터베이스 구성 내용을 소개하였다. 추진성능 모델은 예인 수조시험의 속도-마력 -RPM 성능 데이터와 실 운항에서 조우할 수 있는 바람, 파도 등의 외란에 기인하는 부가저항 및 빙해수조 결과를 바탕으로 다양한 빙상환경에 따른 빙 성능 추정결과를 활용하여 ISO15016: 2002 기반으로 Calm sea 및 빙 해역에서의 선박 속도-마력 성능에서 외란에 의한 부가저항에 따른 소요마력 및 속도변화를 추정하도록 하였다. 제안된 성능모델은 최적 북극항로 탐색 모듈과 결합되어 안전한 북극항로를 도출할 수 있음을 확인하였다.

• 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.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1491-1495
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• 2023

This study utilized automated machine learning (AutoML) to calculate Arctic ice surface temperature (IST). AutoML-derived IST exhibited a strong correlation coefficient (R) of 0.97 and a root mean squared error (RMSE) of 2.51K. Comparative analysis with deep neural network (DNN) models revealed that AutoML IST demonstrated good accuracy, particularly when compared to Moderate Resolution Imaging Spectroradiometer (MODIS) IST and ice mass balance (IMB) buoy IST. These findings underscore the effectiveness of AutoML in enhancing IST estimation accuracy under challenging polar conditions.

• The Korean Journal of Quaternary Research
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• v.33 no.1_2
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• pp.1-23
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• 2021

In response to the increase in atmospheric carbon dioxide and greenhouse gases, the global mean temperature is rising rapidly. In particular, the warming of the Arctic is two to three times faster than the rest. Associated with the rapid Arctic warming, the sea ice shows decreasing trends in all seasons. The faster Arctic warming is due to ice-albedo feedback by the presence of snow and ice in polar regions, which have higher reflectivity than the ocean, the bare land, or vegetation, higher long-wave heat loss to space than lower latitudes by lower surface temperature in the Arctic than lower latitudes, different stability of atmosphere between the Arctic and lower latitudes, where low stability leads to larger heat losses to atmosphere from surface by larger latent heat fluxes than the Arctic, where high stability, especially in winter, prohibits losing heat to atmosphere, increase in clouds and water vapor in the Arctic atmosphere that subsequently act as green house gases, and finally due to the increase in sensible heat fluxes from low latitudes to the Arctic via lower troposphere. In contrast to the rapid Arctic warming, in midlatitudes, especially in eastern Asia and eastern North America, cold air outbreaks occur more frequently and last longer in recent decades. Two pathways have been suggested to link the Arctic warming to cold air outbreaks over midlatitudes. The first is through troposphere in synoptic-scales by enhancing the Siberian high via a development of Rossby wave trains initiated from the Arctic, especially the Barents-Kara Seas. The second is via stratosphere by activating planetary waves to stratosphere and beyond, that leads to warming in the Arctic stratosphere and increase in geopotential height that subsequently weakens the polar vortex and results in cold air outbreaks in midlatitudes for several months. There exists lags between the Arctic warming and cold events in midlatitudes. Thus, understanding chain reactions from the Arctic warming to midlatitude cooling could help improve a predictability of seasonal winter weather in midlatitudes. This study reviews the results on the Arctic warming and its connection to midlatitudes and examines the trends in surface temperature and the Arctic sea ice.