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http://dx.doi.org/10.7780/kjrs.2011.27.4.467

Net Primary Production Changes over Korea and Climate Factors  

Hong, Ji-Youn (Korea Environment Institute)
Shim, Chang-Sub (Korea Environment Institute)
Lee, Moung-Jin (Korea Environment Institute)
Baek, Gyoung-Hye (Korea Environment Institute)
Song, Won-Kyong (Korea Environment Institute)
Jeon, Seong-Woo (Korea Environment Institute)
Park, Yong-Ha (Korea Environment Institute)
Publication Information
Korean Journal of Remote Sensing / v.27, no.4, 2011 , pp. 467-480 More about this Journal
Abstract
Spatial and temporal variabilities of NPP(Net Primary Production) retrieved from two satellite instruments, AVHRR(Advanced Very High Resolution Radiometer, 1981-2000) and MODIS(MODerate-resolution Imaging Spectroradiometer, 2000-2006), were investigated. The range of mean NPP from A VHRR and MODIS were estimated to be 894-1068 $g{\cdot}C/m^2$/yr and 610-694.90 $g{\cdot}C/m^2$/yr, respectively. The discrepancy of NPP between the two instruments is about 325 $g{\cdot}C/m^2$/yr, and MODIS product is generally closer to the ground measurement than AVHRR despite the limitation in direct comparison such as spatial resolution and vegetation classification. The higher NPP values over South Korea are related to the regions with higher biomass (e.g., mountains) and higher annual temperature. The interannual NPP trends from the two satellite products were computed, and both mean annual trends show continuous NPP increase; 2.14 $g{\cdot}C/m^2$/yr from AVHRR(1981-2000) and 6.08 $g{\cdot}C/m^2$/yr from MODIS (2000-2006) over South Korea. Specifically, the higher increasing trends over the Southwestern region are likely due to the increasing productivity of crop fields from sufficient irrigation and fertilizer use. The retrieved NPP shows a closer relationship between monthly temperature and precipitation, which results in maximum correlation during summer monsoons. The difference in the detection wavelength and model schemes during the retrieval can make a significant difference in the satellite products, and a better accuracy in the meterological and land use data and modeling applications will be necessary to improve the satellite-based NPP data.
Keywords
AVHRR; MODIS; satellite; NPP; biomass;
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Times Cited By KSCI : 4  (Citation Analysis)
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1 Zhao, M., F. A. Heinsch, R. R. Nemani, and S. V. Running, 2005, Improvements of the MODIS terrestrial gross and net primary production global data set, Remote sensing of Environment, 95(2): 164-176.   DOI   ScienceOn
2 Zhao, M., S. W. Running, and R. R. Nemani, 2006. Sensitivity of Moderate Resolution Imaging Spectroradiometer (MODIS) terrestrial primary production to the accuracy of meteorological reanalysis, Journal of Geophysical Research, 111, G01002, doi:10.1029/2004JG000004.   DOI
3 Thornton, P. E., B. E. Law, H. L. Gholz, K. L. Clark, E. Falge, D. S. Ellsworth, A. H. Goldstein, R. K. Monson, D. Hollinger, M. Falk, J. Chen, and J. P. Sparks, 2002. Modeling and measuring the effects of disturbance history and climate on carbon and water budgets in evergreen needleleaf forests, Agricultural and Forest Meteorology, 113:185-222.   DOI   ScienceOn
4 Turner, D. P., S. Urbanski, D. Bremer, S. C. Wofsy, T. Meyers, S. T. Gower, and M. Gregory, 2003. A cross-biome comparison of daily light-use efficiency for gross primary production, Global Change Biology, 9: 383-395.   DOI   ScienceOn
5 White, M. A., P. E. Thornton, and S. W. Running, 1997. A continental phenology model for monitoring vegetation responses to interannual climatic variability, Global Biogeochemical Cycles, 11(2): 217-234.   DOI   ScienceOn
6 Zhang, Y., J., M. Xu, H. Chen, and J. Adams, 2009. Global pattern of NPP to GPP ratio derived from MODIS data: effects of ecosystem type, geographical location and climate, Global Ecology and Biogeography, 18(3): 280-290.   DOI   ScienceOn
7 Prince, S. D. and S. N. Goward, 1995. Global Primary Production: a remote sensing approach, Goward Laboratory for global remote sensing studies, Journal of Biogeography, 22: 815-835.   DOI   ScienceOn
8 Monteith, J. L., 1972. Solar radiation and productivity in tropical ecosystems, Journal of Applied Ecology, 9(3): 747-766.   DOI   ScienceOn
9 Prince, S. D., S. J. Goetz, K. Czajkowski, R. Dubayah, and S. N. Goward, 1998. Inference of surface and air temperature, atmospheric precipitable water and vapor pressure deficit using AVHRR satellite observations: Validation of algorithms, Journal of Hydrology, 212-213: 230-250.   DOI
10 Running, S. W. and E. R. Hunt, 1993. Generalization of a forest ecosystem process model for other biomes, Biome-BGC, and an application for global-scale models. In: Scaling Physiological Processes: Leaf to Globe, J. Ehleringer, and C. Field, pp. 141-158, Academic Press, San Diego, 236.
11 Goward, S. N., R. H. Waring, and D. G. Dye, 1994. Ecological remote sensing at OTTER: Macroscale satellite observations, Ecological Society of America, 4(2): 322-343.
12 Heinsch, F. A., M. Reeves, C. F. Bowker, P. Votava, S. Kang, C. Milesi, M. Zhao, J. Glassy, W. M. Jolly, J. S. Kimball, R. R. Nemani, and S. W. Running, 2003. User's Guide GPP and NPP(MOD17A2/A3) Products NASA MODIS Land Algorithm.
13 Goetz, S. J., S. D. Prince, S. N. Goward, M. M. Thawley, J. Small, and A. Johnston, 1999. Mapping net primary production and related biophysical variables with remote sensing: Application to the BOREAS region, Journal of Geophysical Research-Atmospheres, 104(22): 27719-27733.   DOI
14 Heinsch, F. A., M. Zhao, S. Running, J. Kimball, R. Nemani, K. Davis, P. Bolstad, B. Cook, A. Desai, D. Ricciuto, B. Law, W. Oechel, H. Kwon, H. Luo, S. Wofsy, A. L. Dunn, J. Munger, D. Baldocchi, L. Xu, D. Hollinger, A. Richardson, P. Stoy, M. Siqueira, R. Monson, S. Burns, and L. Flanagan, 2006. Evaluation of remote sensing based terrestrial productivity from MODIS using regional tower eddy flux network observations, IEEE Transactions on Geoscience and Remote Sensing, 44(7): 1908-1925.   DOI
15 Hunt, E. R. and Jr. Raymond, 1994. Relationship between woody biomass and PAR conversion efficiency for estimating net primary production from NDVI, International Journal of Remote Sensing, 15(8): 1725-1729.   DOI   ScienceOn
16 Atlas, R. M. and R. Lucchesi, 2000. File specification for GEOS-DAS celled output. Data Assimilation Office, Goddard Space Flight Center, Greenbelt, Maryland, Document No. DAO-1001v4.3.
17 조덕기, 강용혁, 2010. 국내 태양광시스템 설치를 위한 수평면 전일사량과 운량 정밀조사, 한국태양에너지학회, 30(3): 1-9.
18 Goetz, S. J., S. D. Prince, J. Small, A. Gleason, and M. M. Thawley, 2000. Interannual variability of global terrestrial primary production: Results of a model driven with satellite observations, Journal of Geophysical Research, 105: 20077-20091.   DOI
19 윤정숙, 강성진, 이규성, 2009. 시계열 MODIS를 이용한 토지피복의 반사율 패턴: 2004년-2008년, 대한원격탐사학회지, 25(2): 113-126.   DOI
20 정영상, 방정호, 임양생, 1999. 우리 나라의 순1차생산력 및 벼 수량의 지역성과 변이성, 한국농림기상학회, 1(1): 1-12.
21 환경부, 2010. 국가 장기 생태연구, 국립산림과학원.
22 황태희, 이도현, 2003. 경기도 광릉숲의 이산화탄소 흡수 효과 추정: 인공위성 영상과 현장 측정 자료를 이용한 생태계 모형 분석, 기후변화 포럼 및 학술대회, 1(15): 169-180.
23 Baldocchi, D., E. Falge, L. Gu, R. Olson, D. Hollinger, S. Running, P. Anthoni, C. Bernhofer, K. Davis, R. Evans, J. Fuentes, A. Goldstein, G. Katul, B. Law, X. Lee, Y. Malhi, T. Meyers, W. Munger, W. Oechel, U. K. T. Paw, K. Pilegaard, H. P. Schmid, R. Valentini, S. Verma, T. Vesala, K. Wilson, and S. Wofsy, 2001. FLUXNET: A New Tool to Study the Temporal and Spatial Variability of Ecosystem-Scale Carbon Dioxide, Water Vapor and Energy Flux Densities, Bulletin of the American Meteorological Society, 82(11): 2415-2434.   DOI   ScienceOn
24 Angert, A., S. Biraud, C. Bonfils, C. C. Henning, W. Buermann, J. Pinzon, C. J. Tucker, and I. Fung, 2005. Drier summers cancel out the CO2 uptake enhancement induced by warmer springs, Proceedings of the National Academy of Sciences of the United States of America, 102 (31): 10823-10827.   DOI   ScienceOn
25 강신규, 2005. MODIS 엽면적지수 및 일차생산성 영상의 구름 영향 오차 분석: 우리나라 몬순기후의 영향, 한국생태학회지 28(4): 215-222.
26 강신규, 김영일, 김영진, 2005. MODIS 총일차생산성 산출물의 오차요인 분석: 입력기상자료의 영향, 한국농림기상학회지, 7(2): 171-183.
27 국립기상연구소, 2005. 기후변화협약대응 지역기후시나리오 활용기술 개발(I), 국립기상연구소.
28 신사철, 백승철, 2008. 정규화식생지수를 이용한 금강유역의 순일차생산량 추정방법의 제안, 한국지반환경공학회지, 9(6): 43-51.