https://repository.kopri.re.kr/handle/201206/15763 2026-04-05T22:06:49Z 2026-04-05T22:06:49Z Lee, Bomi Lee, sungjae Kim, Hyun-cheol lee https://repository.kopri.re.kr/handle/201206/16544 2026-02-04T05:58:25Z 2025-12-01T00:00:00Z

Title: The Integrated System Development Direction for Expanding the Application of Polar Spatial Information Authors: Lee, Bomi; Lee, sungjae; Kim, Hyun-cheol; lee Abstract: As global warming causes rising ocean temperatures, the decline of glaciers in the polar regions is accelerating. Because the Antarctic and Arctic are vast in scale and difficult to access, there were limitations in immediately detecting changes. However, as accessibiliy to the polar regions improves each year, data acquisition through exploration of the polar regions is becoming easier, accordingly, research to develop a new Arctic shipping route is emerging as a new national agenda. Since 2010, In korea, Korea Polar Research Institute(KOPRI) has been conducting polar ocean research by obtaining various types of polar ocean observation data using the icebreaker research vessel “Araon”. This “Araon” operates during the summer season in polar regions(the Arctic : July to October, the Antarctic : November to March), but as the number of days of operation on the Northern Sea Route increases every year, it is considered a green light for developing the Northern Sea Route. With the advancement of IT and computing technology, spatial information has rapidly permeated every aspect of our lives. With the evolution of various spatial information platforms and the recent integration of technologies like IoT and AI, it is being widely utilized in diverse fields such as autonomous driving, smart cities, fire prevention, environmental protection, resource management, and climate change. Therefore, the purpose of this study is to suggest a direction for the construction of an integrated polar spatial information system to promote the utilization of polar data, which is currently operated according to the individual tasks of each ministry, and to manage it continuously. This study is significant in that it expands the openness of polar spatial information and activates data sharing and utilization by suggesting directions through analysis of existing polar systems(Star, Kaos); 지구 온난화로 인해 해수 온도가 상승함에 따라 극지방 빙하의 감소가 가속화되고 있다. 남극과 북극은 스케일이 방대하고 접근이 어렵기 때문에 변화를 즉각 감지하는데 한계가 있었다. 그러나 극지에 대한 접근성이 매년 개선됨에 따라 극지역 탐지를 통한 자료 취득이 용이해 지고 있으며, 이에 따라 북극 신항로를 개척하기 위한 연구가 새로운 국가 아젠다로 부상하고 있다. 우리나라는 극지연구소가 2010년부터 쇄빙연구선 “아라온호”를 이용하여 다양한 종류의 극지 해양 관측 자료를 획득하여 연구를 수행하고 있다. 아라온호는 극지역의 여름철(북극: 7월 ~ 10월, 남극: 11월 ~ 3월)에 운항하고 있으나, 북극항로의 경우 매년 운행 일수가 증가하면서 항로 개척에 청신호로 판단되고 있다. IT와 더불어 컴퓨팅 기술이 발전하면서 공간정보는 빠르게 우리 생활 전반에 스며들었으며, 다양한 공간정보 플랫폼의 진화와 더불어 최근 IoT, AI 등의 기술이 결합되면서 자율주행, 스마트 시티, 소방 방재, 환경 보호, 자원 관리, 기후 변화 등 다양한 분야에 폭넓게 활용되고 있다. 따라서, 본 연구는 기존 부처별 개별 사무에 따라 각각 운영되는 극지 데이터의 이？활용을 촉진하고, 이를 지속적으로 관리하기 위한 극지 공간정보 통합시스템의 구축 방향을 제시하는 것을 목적으로 한다. 본 연구는 기존 극지 시스템(Star, Kaos)에 대한 분석을 통해 방향성을 제시함으로써 극지 공간정보의 개방성을 확대하고 데이터의 공유 및 활용을 활성화하는데 의의가 있다고 하겠다.

2025-12-01T00:00:00Z Guha Supratim Kim, Hyun-cheol https://repository.kopri.re.kr/handle/201206/16606 2026-02-10T04:23:25Z 2025-12-01T00:00:00Z

Title: Temporal glacier velocity variations and their controlling factors in the Nathorstbreen glacier system, Svalbard Authors: Guha Supratim; Kim, Hyun-cheol Abstract: Temporal variations in glacier velocity are not only essential to understand glacier dynamics but also to predict glacier hazards. Therefore, in the current study, the continuous glacier velocities were estimated from 2014 to 2023 in the Nathorstbreen Glacier System (NGS), Svalbard, where a recent surge event has been observed. Also, the study identified and quantified the factors controlling variations of annual glacier velocity. Using Landsat 8 OLI images, Cossi-corr (Co-registration of Optically Sensed Images and Correlation), an advanced Fourier-based image-matching tool, was utilized to estimate the velocity of the NGS. A multivariate regression analysis was performed to evaluate the influence of temperature, precipitation, snowfall, and terminus fluctuations on annual velocity changes. The results indicate that the NGS exhibited the highest and lowest average annual velocities in 2021 and 2018, with magnitudes of 0.86 ± 0.11 m/day and 0.34 ± 0.18 m/day, respectively. The lower velocity in 2018 represents a quiescent phase following the previous surge, whereas the acceleration in 2021 reflects renewed dynamic activity linked to terminus retreat. Overall, glacier velocity declined from 2014 to 2018, increased between 2020 and 2022, and slightly decreased again in 2023. During this period, the glacier terminus experienced alternating annual retreat and advance, resulting in a net retreat of approximately 2.9 km. Terminus fluctuations were identified as important factors influencing annual glacier velocity, showing a lagged response between terminus movement and velocity. Including parameters such as ice thickness and subglacial hydrology in future analyses would further improve understanding of glacier velocity controls.

2025-12-01T00:00:00Z Jeong, Yongsik Kim, Hyun-cheol https://repository.kopri.re.kr/handle/201206/16589 2026-02-10T03:56:22Z 2025-12-01T00:00:00Z

Title: High-Precision Multi-Sensor Digital Surface Model Dataset Based on UAV and Satellite Data for Greenland Glacier Monitoring Authors: Jeong, Yongsik; Kim, Hyun-cheol Abstract: This study presents a methodological framework for developing a high-precisiondigitalsurface model (DSM) dataset based on complementary unmanned aerialvehicle (UAV) light detection and ranging (LiDAR) and satellite-derived data for RussellGlacier terminus, Greenland. Field surveys were conducted across four annualcampaigns (2022-2025), acquiring UAV LiDAR data that were subsequently cross-referencedwith three satellite-derived DSMs, ASTER GDEM V3, WorldDEM, and Arctic-DEM Mosaic v4.1. Vertical rectification using inverse distance weighting interpolationwith six ground control points was applied to all datasets, achieving a remarkable94.1% improvement in accuracy, reducing mean root mean square error (RMSE) from19.05 to 1.12 m. WorldDEM demonstrated the most substantial improvement (98.6%reduction), while post-correction ArcticDEM achieved the highest accuracy (0.20 mRMSE). UAV LiDAR maintained centimeter-level precision (0.51 m RMSE). Spatiotemporalanalysis revealed significant morpho-dynamic changes, including proglaciallake expansion, moraine evolution, and surface elevation variations. Over 20 years(2000-2025), terminus-region elevation differences reached to 20 m. The verticalrectification methodology demonstrates the effectiveness of employing multi-sensordatasets derived from complementary platforms to overcome individual sensor limitations. This dataset supports glacier mass balance research, dynamics investigations,and climate change impact assessments. The dataset is publicly available through theKorea Polar Data Center (KPDC).

2025-12-01T00:00:00Z Shahrezaei, Iman Heidarpour Kim, Hyun-cheol https://repository.kopri.re.kr/handle/201206/16464 2026-01-14T07:15:17Z 2025-05-01T00:00:00Z

Title: Sea-Ice Surface Types Characterization and SAR Volume Backscattering Properties in Response to Sea States Interactions Using Structural Feature Fusion Authors: Shahrezaei, Iman Heidarpour; Kim, Hyun-cheol Abstract: Despite extensive research in polar remote sensing, there is still no consensus on how sea-ice evolves in response to interactions with ocean waves, nor is there agreement on the most effective way to characterize it based on fluctuations in height profile, both of which compromise interpretations of its texture properties when observed by synthetic aperture radar (SAR). This study aims to address these knowledge gaps by investigating the sea-ice modeling, marginal ice zone (MIZ) categorization and identifying an optimal approach to extract its freeboard profile and relevant backscattering properties under varying sea state conditions. To accomplish this, a numerical approach for modeling random polar media (RPM) is proposed, benefiting from transform-domain fusion method decompositions in conjunction with a convolutional neural network to jointly reconstruct a reference MIZ model in response to wind waves. To ensure consistency in surface structure, the fusion scheme incorporates a point-wise processing principle technique. The reconstructed reference sea-ice model is then subjected to an inverse problem solution analysis to generate the SAR volume backscattering dataset. The simulation results show that the entire routine, encompassing RPM modeling, MIZ characterization, structural fusion, and SAR raw data generation, yields promising results in the realm of sea-ice remote sensing. It reduces dependence on empirical methods, which typically necessitate polar field experiments that are limited by access constraints, or incorporate nonuniform and time-varying media characteristics into large-scale theoretical observation.

2025-05-01T00:00:00Z