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Abstract AI-Helper 아이콘AI-Helper

Albedo is one of the critical parameters for understanding global climate change and energy/water balance. In this study, we used red and NIR reflectance from Satellite Pour I'Obervation de la Terre (SPOT)/Vegetation (VGT) S1 product. The product is preprocessed for users that they are atmospherical...

주제어

AI 본문요약
AI-Helper 아이콘 AI-Helper

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제안 방법

  • The spectral albedo is essential intermediate product to retrieval broad band albedo, but SPOT/VGT does not provide the product. So we estimated surface spectral albedo of red and NIR using SPOT/VGT with theBRDF modeling and conversion procedures.Refer to a previously study (Lee and Han, 2013), integral kernel and inversion coefficients of Roujean’s model for retrieving spectral albedos of red and NIR.

대상 데이터

  • As reference broad band albedo data, Moderate Resolution Imaging Spectroradiometer (MODIS) official albedo products (MCD43B3) were collected. Liang et al.

이론/모형

  • Therefore, we used Roujean’s BRDF model to retrieve surface albedo.
본문요약 정보가 도움이 되었나요?

참고문헌 (20)

  1. Avissar, R., and M.M. Verstraete, 1990. The representation of continental surface processes in atmospheric models, Reviews of Geophysics, 28(1): 35-52. 

  2. Dickinson, R.E., 1995. Land processes in climate models, Remote Sensing of Environment, 51(1): 27-38. 

  3. GCOS, 2003. Second report on the adequacy of the global observing systems for climate, Technical Report GCOS-82, WMO/TD No. 1143, World Meteorological Organization. 

  4. GCOS, 2006. Systematic observation requirements for satellite-based products for climate: Supplemental details to the satellite-based component of the implementation plan for the global observing system for climate in support of the UNFCCC, Technical Report GCOS-107, WMO/TD No 1338, World Meteorological Organization. 

  5. Govaers Y.M., A. Lattanzio, M. Taberner, and B. Pinty, Generating global surface albedo products from multiple geostationary satellites, Remote Sensing of Environment, 112: 2804-2816. 

  6. Henderson-Sellers, A. and M.F. Wilson, 1983. Surface albedo data for climatic modelling, Reviews of Geophysics, 21(8): 1743-1778. 

  7. Kim, S.I., K.-S. Han, and K.-J. Pi, 2011. The Trend Analysis of Vegetation Change Applied to Unsupervised Classification Over East Asia: Using the NDVI 10-day data in 1999-2010, Journal of Korean Society for Geospatial Information System, 19(4): 153-159 (in Korean with English abstract). 

  8. Lee, C.S., and K.S. Han, 2013. Comparison of Two Semi-Empirical BRDF algorithms using SPOT/VGT, Korean Journal of Remote Sensing, 29(3): 307-314. 

  9. Liang, S., H. Fang, M. Chen, C.J. Shuey, C. Walthall, C. Daughtry, J. Morisette, C. Schaaf, and A. Strahler, 2002. Validating MODIS land surface reflectance and albedo products: Methods and preliminary results, Remote Sensing of Environment, 83(1): 149-162. 

  10. Lucht, W., C.B. Schaaf, and A.H. Strahler, 2000. An algorithm for the retrieval of albedo from space using semiempirical BRDF models, IEEE Transactions on Geoscience and Remote Sensing, 38(2): 977-998. 

  11. Rahman, H. and G. Dedieu, 1994. SMAC: a simplified method for the atmospheric correction of satellite measurements in the solar spectrum. International Journal of Remote Sensing, 15(1): 123-143. 

  12. Roujean, J.L., M. Leroy, and P.Y. Deschamps, 1992. A bidirectional reflectance model of the Earth's surface for the correction of remote sensing data, Journal of Geophysical Research, 97(D18): 20455-20468. 

  13. Park, E.-B., K.-S. Han, C.-S. Lee, and K.-J. Pi, 2012. The Tendency Analysis of Albedo by Land Cover Over Northeast Asia Using MODIS 16-Day Composited Albedo data, Korean Journal of Remote Sensing, 28(5): 501-508 (in Korean with English abstract). 

  14. Pi, K.-J., K.-S. Han, and S.-J. Park, 2009. A Comparative Analysis of Land Cover Changes Among Different Source Regions of Dust Emission in East Asia: Gobi Desert and Manchuria, Korean Journal of Remote Sensing, 25(2): 175-184 (in Korean with English abstract). 

  15. Schaaf, C.B., 2009. ALBEDO albedo and reflectance anisotropy, Global Terrestrial Observing System, Rome. 

  16. Strahler, A.H., J.P. Muller, W. Lucht, C.B. Schaaf, T. Tsang, F. Gao, L. Xiaowen, J.P. Muller, and M.J. Barnsley, 1999. MODIS BRDF/albedo product: algorithm theoretical basis document version 5.0., MODIS documentation. 

  17. Valiente, J.A., M. Nunez, E. Lopez-Baeza, and J.F. Moreno, 1995. Narrow-band to broad-band conversion for Meteosat-visiible channel and broad-band albedo using both AVHRR-1 and-2 channels, International Journal of Remote Sensing, 16(6): 1147-1166. 

  18. van Leeuwen, W.J., and J.L. Roujean, 2002. Land surface albedo from the synergistic use of polar (EPS) and geo-stationary (MSG) observing systems: An assessment of physical uncertainties, Remote Sensing of Environment, 81(2): 273-289. 

  19. Verbeiren, S., 2009. GMES Space Component Data Access(GSC-DA) Instrument/Product specifications, VITO, p42. 

  20. Wanner, W., X. Li, and A.H. Strahler, 1995. On the derivation of kernels for kernel driven models of bidirectional reflectance. Journal of Geophysical Research: Atmospheres (1984-2012), 100(D10): 21077-21089. 

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