자원환경지질 (Economic and Environmental Geology)

  • 제57권5호
  • /
  • Pages.513-527
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  • 2024
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  • 1225-7281(pISSN)
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  • 2288-7962(eISSN)
대한자원환경지질학회 (The Korean Society of Economic and Environmental Geology)
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인공위성 원격탐사 기반 메탄 배출 모니터링 기술 현황

Current Status of Satellite Remote Sensing-Based Methane Emission Monitoring Technologies

  • 김민주 (동아대학교 에너지자원공학과) ;
  • 박정우 (동아대학교 에너지자원공학과) ;
  • 현창욱 (동아대학교 에너지자원공학과)
  • Minju Kim (Department of Energy and Mineral Resources Engineering, Dong-A University) ;
  • Jeongwoo Park (Department of Energy and Mineral Resources Engineering, Dong-A University) ;
  • Chang-Uk Hyun (Department of Energy and Mineral Resources Engineering, Dong-A University)
  • 투고 : 2024.08.29
  • 심사 : 2024.09.24
  • 발행 : 2024.10.29
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초록

메탄은 이산화탄소에 이어 두 번째로 지구온난화에 미치는 영향이 큰 온실가스로, 기후변화에 상당한 영향을 미친다. 본 논문에서는 메탄 배출을 효율적으로 탐지하고 정량화하기 위해 사용되는 인공위성 원격탐사 기반 메탄 탐지 기술을 종합적으로 검토하고자 한다. 메탄 배출원은 크게 자연적 배출원(영구동토, 습지)과 인위적 배출원(농축산업, 석탄광, 석유 및 가스전, 폐기물 처리)으로 구분된다. 이 중 인위적 배출원에 대해 단파장적외선을 포함한 다양한 파장영역의 정보를 활용한 메탄 탐지의 원리와 이를 지원하는 주요 위성자료의 활용성에 대해 고찰하였다. 최근에는 위성자료를 활용한 메탄 탐지에서 딥러닝 기법을 적용한 연구들이 진행되고 있으며 이는 메탄 배출을 보다 정확하게 분석하는 데 기여하고 있다. 또한, 딥러닝 기법 적용 사례를 포함하여 전 지구, 지역 및 대형 사고 규모에서의 메탄 배출 탐지 사례를 종합적으로 검토하고 위성 기반 메탄 모니터링의 실용성을 평가하였다. 전 지구 규모에서는 Sentinel-5P TROPOspheric Monitoring Instrument (TROPOMI)와 같은 위성 센서를 사용한 연구들이 검토되었고 지역 규모에서는 주로 TROPOMI 자료와 상대적으로 고해상도의 위성자료(Sentinel-2 MultiSpectral Instrument (MSI), GHGSat Wide-Angle Fabry-Perot (WAF-P) Imaging Spectrometer 등)를 결합하여 메탄 배출 및 배출량을 탐지한 연구 사례를 소개하였다. 이러한 종합적 검토를 통해 위성 기반 메탄 탐지 기술의 현황과 활용성을 평가하였다.

Methane is the second most significant greenhouse gas contributing to global warming after carbon dioxide, exerting a substantial impact on climate change. This paper provides a comprehensive review of satellite remote sensing-based methane detection technologies used to efficiently detect and quantify methane emissions. Methane emission sources are broadly categorized into natural sources (such as permafrost and wetlands) and anthropogenic sources (such as agriculture, coal mines, oil and gas fields, and landfills). This study focuses on anthropogenic sources and examines the principles of methane detection using information from various spectral bands, including the shortwave infrared (SWIR) band, and the utilization of key satellite data supporting these technologies. Recently, deep learning techniques have been applied in methane detection research using satellite data, contributing to more accurate analyses of methane emissions. Furthermore, this paper assesses the practicality of satellite-based methane monitoring by synthesizing case studies of methane emission detection at global, regional, and major incident scales, including examples of applying deep learning techniques. At the global scale, research utilizing satellite sensors like the Sentinel-5P TROPOspheric Monitoring Instrument (TROPOMI) was reviewed. At the regional scale, studies were highlighted where TROPOMI data was combined with relatively high-resolution satellite data, such as the Sentinel-2 MultiSpectral Instrument (MSI) and GHGSat Wide-Angle Fabry-Perot (WAF-P) Imaging Spectrometer, to detect methane emissions and sources. Through this comprehensive review, the current state and applicability of satellite-based methane detection technologies are evaluated.

키워드

과제정보

이 논문은 동아대학교 교내연구비 지원에 의하여 연구되었습니다.

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