Korean Journal of Remote Sensing (대한원격탐사학회지)

Korean Society of Remote Sensing (대한원격탐사학회)
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The Estimation of Gross Primary Productivity over North Korea Using MODIS FPAR and WRF Meteorological Data

MODIS 광합성유효복사흡수율과 WRF 기상자료를 이용한 북한지역의 총일차생산성 추정

  • Do, Na-Young (Department of Environmental Science, Kangwon National University) ;
  • Kang, Sin-Kyu (Department of Environmental Science, Kangwon National University) ;
  • Myeong, Soo-Jeong (Korea Adaptation Center for Climate Change, Korea Environment Institute) ;
  • Chun, Tae-Hun (Department of Environmental Science, Kangwon National University) ;
  • Lee, Ji-Hye (Department of Environmental Science, Kangwon National University) ;
  • Lee, Chong-Bum (Department of Environmental Science, Kangwon National University)
  • 도나영 (강원대학교 자연과학대학 환경과학과) ;
  • 강신규 (강원대학교 자연과학대학 환경과학과) ;
  • 명수정 (한국환경정책.평가연구원 국가기후변화적응센터) ;
  • 천태훈 (강원대학교 자연과학대학 환경과학과) ;
  • 이지혜 (강원대학교 자연과학대학 환경과학과) ;
  • 이종범 (강원대학교 자연과학대학 환경과학과)
  • Received : 2011.11.11
  • Accepted : 2012.03.06
  • Published : 2012.04.30
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Abstract

NASA MODIS GPP provides a useful tool to monitor global terrestrial vegetation productivity. Two major problems of NASA GPP in regional applications are coarse spatial resolution ($1.25^{\circ}{\times}1^{\circ}$) of DAO meteorological data and cloud contamination of MODIS FPAR product. In this study, we improved the NASA GPP by using enhanced input data of high spatial resolution (3 km${\times}$3 km) WRF meteorological data and cloud-corrected FPAR over the North Korea. The improved GPP was utilized to investigate characteristics of GPP interannual variation and spatial patterns from 2000 to 2008. The GPP varied from 645 to 863 $gC\;m^{-2}\;y^{-1}$ in 2000 and 2008, respectively. Mixed forest showed the highest GPP (1,076 $gC\;m^{-2}\;y^{-1}$). Compared to NASA GPP (790 $gC\;m^{-2}\;y^{-1}$);FPAR enhancement increased GPP (861) but utilization of WRF data decreased GPP (710). Enhancements of both FPAR and meteorological input resulted in GPP increase (809) and the improvement was the greatest for mixed forest regions (+10.2%). The improved GPP showed better spatial heterogeneity reflecting local topography due to high resolution WRF data. It is remarkable that the improved and NASA GPPs showed distinctly different interannual variations with each other. Our study indicates improvement of NASA GPP by enhancing input variables is necessary to monitor region-scale terrestrial vegetation productivity.

미국항공우주국(NASA)의 MODIS GPP 자료는 육상식생의 총일차생산성(GPP) 모니터링에 중요한 수단을 제공한다. 그러나 GPP 추정의 입력자료로 사용하는 DAO기상자료의 거친 공간해상도($1.25^{\circ}{\times}1^{\circ}$)와 FPAR 자료의 구름영향에 의한 신뢰도 저하 등은 지역 수준의 GPP 모니터링에 문제를 야기한다. 이 연구에서는 북한지역을 대상으로 FPAR의 구름영향 제거하고 고해상도(3 km${\times}$3 km) WRF 기상자료를 사용함으로써 입력자료의 문제를 개선한 GPP를 추정한 후, 2000-2008년 간의 GPP 연간 변동특성 및 지역적 분포특성을 분석하였다. 개선한 GPP는 2000년의 645 $gC\;m^{-2}\;y^{-1}$에서 2008년의 863 $gC\;m^{-2}\;y^{-1}$까지 변화하였고, 혼효림지역이 1,076 $gC\;m^{-2}\;y^{-1}$으로 가장 큰 값을 보였다. NASA GPP (790 $gC\;m^{-2}\;y^{-1}$)에 비해 FPAR 개선 후 GPP가 증가하였고(861), WRF 자료 이용 시 감소(710), FPAR와 WRF 자료 이용 시 다소 증가(809)하는 양상을 보였다. 개선효과는 북한에서 제일 큰 면적을 차지한 혼효림에서 가장 뚜렷하였다(+10.2%). 한편 WRF 기상자료가 DAO에 비해 지형적 영향을 보다 잘 반영함으로써, 결과적으로 개선한 GPP의 공간이질성이 증가한 것으로 나타났다. 각 피복유형별 연간변동성을 분석한 결과 개선한 GPP는 NASA GPP와 상이한 연간변화를 보였다. 위 결과들을 종합하면, 북한 등의 지역수준의 GPP 모니터링을 목적으로할 경우, 입력자료의 개선에 의한 MODIS GPP를 재산출할 필요가 있다고 보여진다.

Keywords

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