DOI QR코드

DOI QR Code

설마천 유역 CO2 Flux 실측 자료에 의한 총일차생산성 (GPP)과 MODIS GPP간의 비교 평가

Evaluation of MODIS Gross Primary Production (GPP) by Comparing with GPP from CO2 Flux Data Measured in a Mixed Forest Area

  • 정충길 (건국대학교 대학원 사회환경시스템공학과) ;
  • 신형진 (건국대학교 대학원 사회환경시스템공학과) ;
  • 박민지 (건국대학교 대학원 사회환경시스템공학과) ;
  • 조형경 (건국대학교 대학원 사회환경시스템공학과) ;
  • 김성준 (건국대학교 사회환경시스템공학과)
  • 투고 : 2010.11.29
  • 심사 : 2011.02.05
  • 발행 : 2011.03.31

초록

In this study, In order to evaluate reliable of MODIS GPP, the MODIS GPP and Flux tower measured GPP were compared to evaluate the use of method on 8 days composite MODIS GPP. The 2008 Flux data ($CO_2$ Flux and air temperature) measured in Seolmacheon watershed ($8.48\;km^2$) were used. The Flux tower GPP was estimated as the sum of $CO_2$ Flux and $R_{ec}$ (ecosystem respiration) by Lloyd and Taylor method (1994). The summer Monsoon period from June to August mostly contributed the underestimation of MODIS GPP by cloud contamination on MODIS pixels. The 2008 MODIS GPP and Flux tower GPP of the watershed were $1133.2\;g/m^2/year$ and $1464.3\;g/m^2/year$ respectively and the determination coefficient ($R^2$) after correction of cloud-originated errors was 0.74 (0.63 before correction). Even though effect of Cloud-Originated Errors was eliminated, Solar radiation and Temperature are affected at GPP. Measurement of correct GPP is difficult. But, If errors of MODIS GPP analyze on Cloud Moonsoon Climate in korea and eliminated effect of Cloud-Originated Errors, MODIS GPP will be considered GPP increasing of 9 %. There, Our results indicate that MODIS GPP show reliable and useful data except for summer period in Moonsoon Climate.

키워드

참고문헌

  1. Cohen, W. B., and C. O. Justice, 1999. Validating MODIS terrestrial ecology products: linking in situ and satellite measurements. Remote Sensing of Environment 70: 1-4. https://doi.org/10.1016/S0034-4257(99)00053-X
  2. 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. http://www.forestry.umt.edu/ntsg/.
  3. Hong, W. Y., H. J. Shin, and S. J. Kim, 2007. Extraction of Snow Cover Area and Depth using MODIS Image for 5 River Basins in South Korea. KCID J. 14(2): 65-75 (in Korean).
  4. Hong, J. K., H. J. Kwon, and J. Kim, 2009. Measurement of Evapotranspiration by Eddy-Covariance Technique. 2-4. TR 2009-13. Sustainable Water Resources Research Center (in Korean).
  5. Houghton, R. A., and J. L. Hackler, 2001. Carbon Flux to the Atmosphere From Land-use Changes: 1850 to 1990. NDP-050/R1, Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee.
  6. Kang, S., S. W. Running, J. Lim, M. Zhao, C. Park, and R. Loehman, 2003. A MODIS-based climatological phenology model for detecting onset of growing seasons in temperate mixed forests in Korea. Remote Sensing of Environment 86: 232-242. https://doi.org/10.1016/S0034-4257(03)00103-2
  7. Kang, S, K., 2005. Analysis on Cloud-Originated Errors of MODIS leaf Area Index and Primary Production Images: Effect of Monsoon Climate in Korea. Journal of Ecology and Field Biology 29(6): 215-222.
  8. Kang, S. K., Y. I. Kim, and Y. J. Kim, 2005. Errors of MODIS product of Gross Primary Productivity by using Data Assimilation Office Meteorological Data. Korean Journal of Agricultural and Forest meteorology 7(2): 171-183 (in Korean).
  9. Kang, S. K., K. C. Jang, B. R. Lee, and S. H. Kim, 2008. User's manual for MODIS data processing and mapping evapotranspiration. 3-6. TR 2008-13. Sustainable Water Resources Research Center.
  10. Kim, N. W., J. E. Lee, I. M. Jung, and D.P. Kim, 2008. Hydrologic Component Analysis of the Seolma-Cheon Watershed by Using SWAT-K Model. Journal of the Environmental Sciences 17(12): 1363-1372 (in Korean). https://doi.org/10.5322/JES.2008.17.12.1363
  11. Kim, Y. I., S. K. Kang, and J. Kim, 2007. Enhancing the Reliability of MODIS Gross Primary Productivity (GPP) by Improving Input Data. Korean Journal of Agricultural and Forest meteorology 9(2): 132-139 (in Korean). https://doi.org/10.5532/KJAFM.2007.9.2.132
  12. Morisette, J. T., J. L. Privette, and C.O. Justice. 2002. A framework for the validation of MODIS Land products. Remote Sensing of Environment 83: 77-96. https://doi.org/10.1016/S0034-4257(02)00088-3
  13. Myneni, R. B., S. Hoffman, Y. Knyazikhin, J. L. Privette, J. Glassy, Y. Tian, Y. Wang, X. Song, Y. Zhang, G. R. Smith, A. Lotsch, M. Friedl, J. T. Morisette, P. Votava, R. R. Nemani, and S. W. Running, 2002. Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data. Remote Sensing of Environment 83: 214-231. https://doi.org/10.1016/S0034-4257(02)00074-3
  14. Running, S. W., P. E. Thornton, R. R. Nemani, and J. M. Glassy, 2000. Global terrestrial gross and net primary productivity from the earth observing system. Methods in Ecosystem Science, O. E. Sala, R. B. Jackson, R. B., H. A. Mooney, and R. W. Howarth (Eds.), Springer-Verlag. New York.
  15. Sellers, P. J., C. J. Tucker, G. J. Collatz, S. O. Los, C. O. Justice, D. A. Dazlich, and D. A. Randall, 1994. A global 1o by 1o NDVI data set for climate studies: 2. The generation of global fields of terrestrial biophysical parameters from the NDVI. International Journal of Remote Sensing 15: 3519-3545. https://doi.org/10.1080/01431169408954343
  16. Turner, D. P., W. Ritts, W. B. Cohen, S. T. Gower, M. Zhao, and S. W. Running, 2003. Scaling gross primary production (GPP) over boreal and deciduous forest landscapes in support of MODIS GPP product validation. Remote Sensing of Environment 88: 256-270. https://doi.org/10.1016/j.rse.2003.06.005
  17. Vogt, R., A. Christen, M. W. Rotach, and A. N. V. Satyanarayana, 2006. Temporal dynamics of $CO_2$ fluxes and profiles over a Central European city. Theor. App;. Climatol. 84: 117-126. https://doi.org/10.1007/s00704-005-0149-9

피인용 문헌

  1. Estimation of Net Primary Production for Nakdong River Basin using Vegetation Index vol.15, pp.10, 2014, https://doi.org/10.14481/jkges.2014.15.10.35