• Korean Journal of Remote Sensing
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• v.34 no.6_2
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• pp.1165-1178
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• 2018

Collapse of an Antarctic ice shelf and its flow velocity changes has the potential to reduce the restraining stress to the seaward flow of the Antarctic Ice Sheet, which can cause sea level rising. In this study, variations in ice velocity from 2000 to 2017 for the Nansen Ice Shelf in East Antarctica that experienced a large-scale collapse in April 2016 were analyzed using Landsat-7 Enhanced Thematic Mapper Plus (ETM+) and Landsat-8 Operational Land Imager (OLI) images. To extract ice velocity, image matching based on orientation correlation was applied to the image pairs of blue, green, red, near-infrared, panchromatic, and the first principal component image of the Landsat multispectral data, from which the results were combined. The Landsat multispectral image matching produced reliable ice velocities for at least 14% wider area on the Nansen Ice Shelf than for the case of using single band (i.e., panchromatic) image matching. The ice velocities derived from the Landsat multispectral image matching have the error of $2.1m\;a^{-1}$ compared to the in situ Global Positioning System (GPS) observation data. The region adjacent to the Drygalski Ice Tongue showed the fastest increase in ice velocity between 2000 and 2017. The ice velocity along the central flow line of the Nansen Ice Shelf was stable before 2010 (${\sim}228m\;a^{-1}$). In 2011-2012, when a rift began to develop near the ice front, the ice flow was accelerated (${\sim}255m\;a^{-1}$) but the velocity was only about 11% faster than 2010. Since 2014, the massive rift had been fully developed, and the ice velocity of the upper region of the rift slightly decreased (${\sim}225m\;a^{-1}$) and stabilized. This means that the development of the rift and the resulting collapse of the ice front had little effect on the ice velocity of the Nansen Ice Shelf.

• Korean Journal of Remote Sensing
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• v.34 no.2_1
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• pp.203-211
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• 2018

Dam discharge is carried out for the management of rivers and area around rivers due to rainy season or drought. Dam discharge should be based on an accurate understanding of the flow rate that can be accommodated in the river. Therefore, understanding the allowable storage capacity of river is an important factor in the management of the environment around the river. However, the methods using water level meters and images, which are currently used to determine the allowable flow rate of rivers, show limitations in terms of accuracy and efficiency. In order to solve these problems, this paper proposes a method to automatically calculate the allowable storage capacity of river based on the images taken by drone. In the first step, we create a 3D model of the river by using the drone images. This generation process consists of tiepoint extraction, image orientation, and image matching. In the second step, the allowable storage capacity is calculated by cross section analysis of the river using the generated river 3D model and the road and river layers in the target area. In this step, we determine the maximum water level of the river, extract the cross-sectional profile along the river, and use the 3D model to calculate the allowable storage capacity for the area. To prove our method, we used Bukhan river's data and as a result, the allowable storage volume was automatically extracted. It is expected that the proposed method will be useful for real - time management of rivers and surrounding areas and 3D models using drone.

• Journal of the Korean Geographical Society
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• v.50 no.1
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• pp.1-21
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• 2015

The present study aims to characterize the synoptic climatic patterns of winter extreme low temperature events occurred in different regions of Korea based on daily temperature data observed at 61 weather stations under the supervision of the Korea Meteorological Administation and NCEP/NCAR reanalysis I data for the recent 40 years (1973~2012) period. Analyses of daily maximum and minimum temperatures below 10th percentile thresholds show that high frequencies of winter extreme low temperature events appear across the entire regions of Korea or in either the western or eastern half region divided by major mountain ridges at the 2~7 dayintervals particularly in the first half of the winter period (before mid-January). Composite analyses of surface synoptic climatic data including sea level pressure and wind vector reveal that 13 regional types of winter extreme low temperature events in Korea are closely associated with the relative location and intensity of both the Siberian high pressure and the Aleutian low pressure systems as well as major mountain ridges. Investigations of mid-troposphere (500 hPa) synoptic climatic charts demonstrate that the blocking-like upper troposphere low pressure system advecting the cold air from the Arctic toward the Korean Peninsula may provide favorable synoptic conditions for the outbreaks of winter extreme low temperature events in Korea. These results indicate that the monitoring of synoptic scale climatic systems in East Asia including the Siberian high pressure system, the Aleutian low pressure system and upper level blocking system is critical to the improvement of the predictability of winter extreme low temperature events in Korea.

• Journal of the Korean earth science society
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• v.41 no.1
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• pp.31-39
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• 2020

Cheonji, the largest caldera lake in Asia, is located at the summit of Baekdu Mountain. Cheonji is covered with snow and ice for about six months of the year due to its high altitude and its surrounding environment. Since most of the sources of water are from groundwater, the water temperature is closely related to the volcanic activity. However, in the 2000s, many volcanic activities have been monitored on the mountain. In this study, we analyzed the dimension of ice produced during winter in Baekdu Mountain using Sentinel-1 satellite image data provided by the European Space Agency (ESA). In order to calculate the dimension of ice from the backscatter image of the Sentinel-1 satellite, 20 Gray-Level Co-occurrence Matrix (GLCM) layers were generated from two polarization images using texture analysis. The method used in calculating the area was utilized with the Support Vector Machine (SVM) algorithm to classify the GLCM layer which is to calculate the dimension of ice in the image. Also, the calculated area was correlated with temperature data obtained from Samjiyeon weather station. This study could be used as a basis for suggesting an alternative to the new method of calculating the area of ice before using a long-term time series analysis on a full scale.

• Atmosphere
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• v.29 no.1
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• pp.87-103
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• 2019

This study introduces the overall characteristics of LOVECLIM version 1.3, the earth system model of intermediate complexity (EMIC), including the installation and operation processes by conducting two kinds of past climate simulation. First climate simulation is the equilibrium experiment during the mid-Holocene (6,000 BP), when orbital parameters were different compared to those at present. The overall accuracy of simulated global atmospheric fields by LOVECLIM is relatively lower than that in Coupled Model Intercomparison Project phase 5 (CMIP5) and Paleoclimate modelling Intercomparison Project phase 3 (PMIP3) simulations. However, surface temperature over the globe, the 800 hPa meridional wind over the mid-latitude coastal region, and the 200 hPa zonal wind from LOVECLIM show similar spatial distribution to those multi-model mean of CMIP5/PMIP3 climate models. Second one is the transient climate experiment from mid-Holocene to present. LOVECLIM well captures the major differences in surface temperature between preindustrial and mid-Holocene simulations by CMIP5/PMIP3 multi-model mean, even though it was performed with short integration time (i.e., about four days in a single CPU environment). In this way, although the earth system model of intermediate complexity has a limit due to its relatively low accuracy, it can be a very useful tool in the specific research area such as paleoclimate.

• Korean Journal of Microbiology
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• v.52 no.2
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• pp.192-201
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• 2016

Recently, Psychrobacter sp. ArcL13 strain showing the extracellular lipase activity was isolated from the Chuckchi Sea of the Arctic Ocean. However, due to the low expression levels of the enzyme in the natural strain, the production of recombinant lipase is crucial for various applications. Identification of the gene for the enzyme is prerequisite for the production of the recombinant protein. Therefore, in the present study, a novel lipase gene (ArcL13-Lip) was isolated from Psychrobacter sp. ArcL13 strain by gene prospecting using PCR, and its complete nucleotide sequence was determined. Sequence analysis showed that ArcL13-Lip has high amino acid sequence similarity to lipases from bacteria of some Psychrobacter genus (84-90%) despite low nucleotide sequence similarity. The lipase gene was cloned into the bacterial expression plasmid and expressed in E. coli. SDS-PAGE analysis of the cells showed that ArcL13-Lip was expressed as inclusion bodies with a molecular mass of about 35 kDa. Refolding was achieved by diluting the unfolded protein into refolding buffers containing various additives, and the highest refolding efficiency was seen in the glucose-containing buffer. Refolded ArcL13-Lip showed high hydrolytic activity toward p-nitrophenyl caprylate and p-nitrophenyl decanoate among different p-nitrophenyl esters. Recombinant ArcL13-Lip displayed maximal activity at $40^{\circ}C$ and pH 8.0 with p-nitrophenyl caprylate as a substrate. Activity assays performed at various temperatures showed that ArcL13-Lip is a cold-active lipase with about 40% and 73% of enzymatic activity at $10^{\circ}C$ and $20^{\circ}C$, respectively, compared to its maximal activity at $40^{\circ}C$.

• Korean Journal of Mineralogy and Petrology
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• v.36 no.4
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• pp.303-312
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• 2023

The determination of the oxidation states of metal elements in manganese nodules sheds light on the understanding of the formation mechanism of nodules, providing insights into the paleo-environmental conditions such as the redox potential of the aqueous system. This study aims to reveal the oxidation states and chemical bonding of manganese in the natural polymetallic nodules, utilizing conventional X-ray photoelectron spectroscopy (XPS). Specifically, shallow manganese nodules from the Siberian Arctic Sea, effectively recording mineralogical variations, were used in this study. Detailed analysis of XPS Mn 2p spectra showed changes in the manganese oxidation state from the center to the outer parts of the nodules. The central part of the nodules showed a higher Mn⁴⁺ content, approximately 67.9%, while the outermost part showed about 63% of Mn⁴⁺ due to an increase in the Mn³⁺+Mn²⁺. The decrease in the Mn oxidation state with the growth is consistent with the previously reported mineralogical variations from todorokite to birnessite with growth. Additionally, the O 1s spectra presented a predominance of Mn-O-H bonds in the outer layers compared to the center, suggesting hydration by water in the layered manganates of outer layers. The results of this study demonstrate that XPS can be directly applied to understand changes in paleo-environmental conditions such as the redox states during the growth of manganese nodules. Finally, future studies using high-resolution synchrotron-based XPS experiments could achieve details in oxidation states of manganese and trace metal elements.