<?xml version="1.0" encoding="UTF-8"?>
<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns="http://purl.org/rss/1.0/" xmlns:dc="http://purl.org/dc/elements/1.1/">
  <channel rdf:about="https://repository.kopri.re.kr/handle/201206/15841">
    <title>DSpace Collection:</title>
    <link>https://repository.kopri.re.kr/handle/201206/15841</link>
    <description />
    <items>
      <rdf:Seq>
        <rdf:li rdf:resource="https://repository.kopri.re.kr/handle/201206/16207" />
        <rdf:li rdf:resource="https://repository.kopri.re.kr/handle/201206/16305" />
        <rdf:li rdf:resource="https://repository.kopri.re.kr/handle/201206/16378" />
        <rdf:li rdf:resource="https://repository.kopri.re.kr/handle/201206/16433" />
      </rdf:Seq>
    </items>
    <dc:date>2026-04-21T05:21:55Z</dc:date>
  </channel>
  <item rdf:about="https://repository.kopri.re.kr/handle/201206/16207">
    <title>Arctic Greening Trends: Change Points in Satellite-Derived Normalized Difference Vegetation Indexes and Their Correlation with Climate Variables over the Last Two Decades</title>
    <link>https://repository.kopri.re.kr/handle/201206/16207</link>
    <description>Title: Arctic Greening Trends: Change Points in Satellite-Derived Normalized Difference Vegetation Indexes and Their Correlation with Climate Variables over the Last Two Decades
Authors: Seo, Minji; Kim, Hyun-cheol
Abstract: In this study, we utilized NDVI data from the moderate resolution imaging spectroradiometer (MODIS) alongside climatic variables obtained from a reanalyzed dataset to analyze Arctic greening during the summer months (June-September) of the last two decades. This investigation entailed a detailed analysis of these changes across various temporal scales. The data indicated a continuous trend of Arctic greening, evidenced by a 1.8% per decade increment in the NDVI. Notably, significant change points were identified in June 2012 and September 2013. A comparative assessment of NDVI pre- and post-these inflection points revealed an elongation of the Arctic greening trend. Furthermore, an anomalous increase in NDVI of 2% per decade was observed, suggesting an acceleration in greening. A comprehensive analysis was conducted to decipher the correlation between NDVI, temperature, and energy budget parameters to elucidate the underlying causes of these change points. Although the correlation between these variables was relatively low throughout the summer months, a distinct pattern emerged when these periods were dissected and examined in the context of the identified change points. Preceding the change point, a strong correlation (approximately 0.6) was observed between all variables; however, this correlation significantly diminished after the change point, dropping to less than half. This shift implies an introduction of additional external factors influencing the Arctic greening trend after the change point. Our findings provide foundational data for estimating the tipping point in Arctic terrestrial ecosystems. This is achieved by integrating the observed NDVI change points with their relationship with climatic variables, which are essential in comprehensively understanding the dynamics of Arctic climate change, particularly with alterations in tundra vegetation.</description>
    <dc:date>2024-01-01T00:00:00Z</dc:date>
  </item>
  <item rdf:about="https://repository.kopri.re.kr/handle/201206/16305">
    <title>Assessment of Antarctic Ice Tongue Areas Using Sentinel-1 SAR on Google Earth Engine</title>
    <link>https://repository.kopri.re.kr/handle/201206/16305</link>
    <description>Title: Assessment of Antarctic Ice Tongue Areas Using Sentinel-1 SAR on Google Earth Engine
Authors: Lee, Na-Mi; Kim, Seung Hee; Kim, Hyun-cheol
Abstract: This study explores the use of Sentinel-1 Synthetic Aperture Radar (SAR), processed through&#xD;
Google Earth Engine (GEE), to monitor changes in the areas of Antarctic ice shelves. Focusing on the&#xD;
Campbell Glacier Tongue (CGT) and Drygalski Ice Tongue (DIT), the research utilizes GEE’s cloud computing&#xD;
capabilities to handle and analyze large datasets. The study employs Otsu’s method for image binarization to&#xD;
distinguish ice shelves from the ocean and mitigates detection errors by averaging monthly images and&#xD;
extracting main regions. Results indicate that the CGT area decreased by approximately 26% from January&#xD;
2016 to January 2024, primarily due to calving events, while DIT showed a slight increase overall, with notable&#xD;
reduction in recent years. Validation against Sentinel-2 optical images demonstrates high accuracy, underscoring&#xD;
the effectiveness of SAR and GEE for continuous, long-term monitoring of Antarctic ice shelves.; 본 연구는 Google Earth Engine을 활용하여 Sentinel-1 Synthetic Aperture Radar 영상을 통해 남극Campbell Glacier Tongue (CGT)와 Drygalski Ice Tongue (DIT)의 면적 변화를 2016년부터 2024년까지 모니터링하였다. Otsu 기법과 Simple Non-Iterative Clustering (SNIC) 클러스터링 기법을 사용하여 빙설과 해양을 구분하고 월평균 영상을 통해 빙설 탐지 오류를 줄였다. 분석 결과 CGT는 주기적인 붕괴로 인하여 약26% 감소하였고 DIT는 전반적으로 증가하다가 최근 급격한 감소를 보였다. Sentinel-2 광학 영상과 비교한결과 높은 탐지 정확성을 보여 제안된 방법의 신뢰성을 입증하였으며, 본 연구는 남극 빙설과 빙붕의 장기모니터링에 기여할 것으로 기대된다.</description>
    <dc:date>2024-01-01T00:00:00Z</dc:date>
  </item>
  <item rdf:about="https://repository.kopri.re.kr/handle/201206/16378">
    <title>Four Decades of Polar Research in Remote Sensing: A Comprehensive Review</title>
    <link>https://repository.kopri.re.kr/handle/201206/16378</link>
    <description>Title: Four Decades of Polar Research in Remote Sensing: A Comprehensive Review
Authors: Kim, Hyun-cheol
Abstract: Four Decades of Polar Research in Remote Sensing: A ComprehensiveReview</description>
    <dc:date>2024-01-01T00:00:00Z</dc:date>
  </item>
  <item rdf:about="https://repository.kopri.re.kr/handle/201206/16433">
    <title>Directional Wave Scattering Distribution Modes Analysis and Synthesis of Random Ocean Media Roughness for SAR Electromagnetic Interactions Using Feature Fusion in Dynamic Sea States: A Survey</title>
    <link>https://repository.kopri.re.kr/handle/201206/16433</link>
    <description>Title: Directional Wave Scattering Distribution Modes Analysis and Synthesis of Random Ocean Media Roughness for SAR Electromagnetic Interactions Using Feature Fusion in Dynamic Sea States: A Survey
Authors: Shahrezaei, Iman Heidarpour; Kim, Hyun-cheol
Abstract: Ocean waves have long been a research topic, and numerous formulas of the ocean wave spectrum have been widely developed to provide new prospects for ocean experiments and the advancement of radar probing. Nonetheless, the wave spectra developed by researchers fall short of the standards set by remote sensing specialists, mainly due to the limitation of capturing the surface roughness influenced by both short and long waves, prompting ongoing efforts to develop a model covering a diverse scale of wavenumbers in the absence of a generally recognized reference formula. In response, a standard two-scale formulation of wave frequency spectra (WFS) was introduced, where wave height and spectral peak period are determined by sea state. The proposed composite WFS holds the potential to incorporate directional spreading, contributing to the angular distribution of ocean wave energy in the form of directional WFS, making it applicable for ocean modeling. In an effort to investigate directionality effects, an array of well-established spreading functions, including cosine-squared, half-cosine 2s, parameterized half-cosine 2s, hyperbolic secant-squared, and composite structured functions, has been developed here for numerical modeling of random ocean media (ROM) surface roughness and synthesized for their spectral scattering distribution mode, encompassing scattering pattern, scattering orientation, and fractal roughness properties. Nonetheless, the generated ROM models, each varying due to inherent limitations in directional WFS formulation and numerical approximations, demonstrate indeterminacy and unpredictability in surface features, posing challenges for accurately synthesizing ROM roughness patterns. These challenges intensify under varying sea states and different directional WFS formulas, leading to a situation where no single synthesized composite ROM model consistently outperforms the others, rendering them imprecise frameworks for analyzing roughness patterns and investigating texture electromagnetic interactions within the realm of remote sensing. As an approach, a pattern-sensitive fusion method is proposed, employing a multi-scale transform domain (MTD) fusion scheme that leverages the learning potential of a deep super resolution network. The objective is to fuse the reconstructed ROM roughness models, generating an optimal roughness while maintaining their scattering pattern, scattering orientation, and dominant directionality, pivotal for texture consistency and, consequently, the backscattering properties from the synthetic aperture radar (SAR) viewpoint. To validate the reliability of ROM modeling and its roughness synthesis, including the texture fusion and raw data generation, a comprehensive objective quality assessment technique is utilized. These assessments demonstrate the complete consistency of the simulation results with the underlying spectral theory, highlighting their potential contribution to projects related to ocean radar probing and remote sensing.</description>
    <dc:date>2024-01-01T00:00:00Z</dc:date>
  </item>
</rdf:RDF>

