Journal of the Korean Association of Geographic Information Studies (한국지리정보학회지)

The Korean Association of Geographic Information Studies (한국지리정보학회)
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Overview of Research Trends in Estimation of Forest Carbon Stocks Based on Remote Sensing and GIS

원격탐사와 GIS 기반의 산림탄소저장량 추정에 관한 주요국 연구동향 개관

  • Kim, Kyoung-Min (Division Forest Resources Information, Korea Forest Research Institute) ;
  • Lee, Jung-Bin (Division Forest Resources Information, Korea Forest Research Institute) ;
  • Kim, Eun-Sook (Division Forest Resources Information, Korea Forest Research Institute) ;
  • Park, Hyun-Ju (Environmental Strategy Research Group, Korea Environment Institute) ;
  • Roh, Young-Hee (Dept. Geography, Seoul National University) ;
  • Lee, Seung-Ho (Division Forest Resources Information, Korea Forest Research Institute) ;
  • Park, Key-Ho (Dept. Geography, Seoul National University) ;
  • Shin, Hyu-Seok (Institute for Korean Regional Studies, Seoul National University)
  • 김경민 (국립산림과학원 산림자원정보과) ;
  • 이정빈 (국립산림과학원 산림자원정보과) ;
  • 김은숙 (국립산림과학원 산림자원정보과) ;
  • 박현주 (한국환경정책.평가연구원 환경전략연구본부) ;
  • 노영희 (서울대학교 지리학과) ;
  • 이승호 (국립산림과학원 산림자원정보과) ;
  • 박기호 (서울대학교 지리학과) ;
  • 신휴석 (서울대학교 국토문제 연구소)
  • Received : 2011.05.16
  • Accepted : 2011.08.16
  • Published : 2011.09.30
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Abstract

Forest carbon stocks change due to land use change is an important data required by UNFCCC(United Nations framework convention on climate change). Spatially explicit estimation of forest carbon stocks based on IPCC GPG(intergovernmental panel on climate change good practice guidance) tier 3 gives high reliability. But a current estimation which was aggregated from NFI data doesn't have detail forest carbon stocks by polygon or cell. In order to improve an estimation remote sensing and GIS have been used especially in Europe and North America. We divided research trends in main countries into 4 categories such as remote sensing, GIS, geostatistics and environmental modeling considering spatial heterogeneity. The easiest way to apply is combination NFI data with forest type map based on GIS. Considering especially complicated forest structure of Korea, geostatistics is useful to estimate local variation of forest carbon. In addition, fine scale image is good for verification of forest carbon stocks and determination of CDM site. Related domestic researches are still on initial status and forest carbon stocks are mainly estimated using k-nearest neighbor(k-NN). In order to select suitable method for forest in Korea, an applicability of diverse spatial data and algorithm must be considered. Also the comparison between methods is required.

토지이용변화에 따른 산림탄소저장량 변화는 기후변화협약에서 요구하는 주요 자료 중 하나이다. IPCC 우수실행지침(intergovernmental panel on climate change good practice guidance, IPCC GPG) 수준 3에 근거하여 공간적으로 명확한 산림탄소저장량을 추정하게 되면 높은 신뢰도를 확보할 수 있다. 그러나 기존의 추정 방법은 표본점(sample plot) 단위의 국가산림자원조사 (national forest inventory, NFI) 자료만을 이용하여 행정구역별 평균을 집계하는 것으로 폴리곤 혹은 셀 단위의 상세한 탄소저장량을 파악할 수 없었다. 이를 보완하기 위해 유럽, 북미 등에서는 NFI 자료, 원격탐사 및 GIS 기술을 결합하여 산림탄소저장량을 추정하기 위한 노력이 활발히 이루어져왔다. 주요국의 연구 동향을 활용 기법에 따라 분류해보면 원격탐사, GIS, 지구통계 및 환경변수 모델링 등 크게 4가지 범주로 나눌 수 있다. 이 중 가장 손쉽게 국내 적용을 고려해 볼 수 있는 방법은 NFI 자료와 임상도를 결합하는 GIS 기반의 방법이다. 특히, 복잡한 수종 구성을 가지고 있는 국내 산림 환경 특성을 고려할 때 국지적 변이 추정에 유용한 지구통계 기법의 활용성이 기대된다. 아울러, 고해상도 영상의 활용은 산림탄소저장량 추정의 검증 및 탄소배출권 확보를 위한 CDM(clean development mechanism, 청정개발체제) 사업 적지 선정 등에 유용할 것으로 판단된다. 국내 관련 연구는 아직 초기 단계로 최근린 기법(k-nearest neighbor, k-NN)의 적용성을 검토하는 연구가 주를 이루고 있으나 국내 산림 환경에 적합한 방법론의 선정을 위해서는 보다 다양한 공간 자료와 알고리즘의 적용성이 검토되고 방법론 간의 비교 연구가 필요하다.

Keywords

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