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Chinese Optics Letters

Chinese Optics Letters


  • Vol. 9, Iss. 10 — Oct. 10, 2011
  • pp: 102901–

Modeling visible and near-infrared snow surface reflectance-simulation and validation

Hongyi Wu and Ling Tong  »View Author Affiliations

Chinese Optics Letters, Vol. 9, Issue 10, pp. 102901- (2011)

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Retrieving snow surface reflectance is difficult in optical remote sensing. Hence, this letter evaluates five surface reflectance models, including the Ross-Li, Roujean, Walthall, modified Rahman and Staylor models, in terms of their capacities to capture snow reflectance signatures using ground measurements in Antarctica. The biases of all the models are less than 0.0003 in both visible and near-infrared regions. Moreover, with the exception of the Staylor model, all models have root-mean-square errors of around 0.02, indicating that they can simulate the reflectance magnitude well. The R2 performances of the Ross-Li and Roujean models are higher than those of the others, indicating that these two models can capture the angle distribution of snow surface reflectance better.

© 2011 Chinese Optics Letters

OCIS Codes
(280.0280) Remote sensing and sensors : Remote sensing and sensors
(290.0290) Scattering : Scattering
(300.0300) Spectroscopy : Spectroscopy
(330.0330) Vision, color, and visual optics : Vision, color, and visual optics
(350.0350) Other areas of optics : Other areas of optics

Hongyi Wu and Ling Tong, "Modeling visible and near-infrared snow surface reflectance-simulation and validation," Chin. Opt. Lett. 9, 102901- (2011)

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  1. S. Liang, Quantitative Remote Sensing of Land Surfaces (Hoboken, Wiley-IEEE, 2004).
  2. W. Zhang, H. Wang, and Z. Wang, Chin. Opt. Lett. 7, 88 (2009).
  3. F. Maignan, F.-M. Breon, and R. Lacaze, Remote Sens. Environ. 90, 210 (2004).
  4. P. Bicheron and M. Leroy, J. Geophys. Res. 105, 26669 (2000).
  5. Y.-M. Chen, S. Liang, J. Wang, H.-Y. Kim, and J. V. Martonchik, Int. J. Remote Sens. 29, 6971 (2008).
  6. M. I. Mishchenko, J. M. Dlugach, E. G Yanovitskij, and N. T. Zakharova, J. Quant. Spectrosc. Ra. 63, 409 (1999).
  7. Y. Jin, F. Gao, C. B. Schaaf, X. Li, A. H. Strahler, C. J. Bruegge, and J. V. Martonchik, IEEE Trans. Geosci. Remote Sens. 40, 1593 (2002).
  8. W. Lucht, C. B. Schaaf, and A. H. Strahler, IEEE Trans. Geosci. Remote Sens. 38, 977 (2000).
  9. X. Li and A. H. Strahler, IEEE Trans. Geosci. Remote Sens. 30, 276 (1992).
  10. W. Wanner, X. Li, and A. H. Strahler, J. Geophys. Res. 100, 21077 (1995).
  11. C. L. Walthall, J. M. Norman, J. M. Welles, G. Campbell, and B. L. Blad, Appl. Opt. 24, 383 (1985).
  12. J. L. Roujean, M. Leroy, and P. Y. Deschamps, J. Geophys. Res. 97, 20455 (1992).
  13. H. Rahman, M. M. Verstraete, and B. Pinty, J. Geophys. Res. 98, 20779 (1993).
  14. W. F. Staylor and J. T. Suttles, J. Climate Appl. Meteorol. 25, 196 (1985).
  15. Z. Zhao, C. Qi, and J. Dai, Chin. Opt. Lett. 5, 168 (2007).
  16. S. R. Hudson, S. G.Warren, R. E. Brandt, T. C. Grenfell, and D. Six, J. Geophys. Res. 111, D18106 (2006).
  17. B. C. Kindel, Z. Qu, and A. F. H. Goetz, Appl. Opt. 40, 3483 (2001).
  18. Q. Duan, S. Sorooshian, and V. Gupta, Water Resour. Res. 28, 1015 (1992).

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