Temporal Variation Analysis for Spectral Reflectance of Maize Leaves Using a Fitting Method
QU Ying1, 2, 3, LIU Su-hong1, 2, 3*, LI Xiao-wen1, 2, 3
1. School of Geography, Beijing Normal University, Beijing 100875, China 2. State Key Laboratory of Remote Sensing Science, Beijing Normal University, Beijing 100875, China 3. Beijing Key Laboratory for Remote Sensing of Environment and Digital Cities, Beijing Normal University, Beijing 100875, China
Abstract：The present study is to investigate the temporal variation patterns through the dataset of spectral reflectance of maize leaf using a fitting method. In the field experiment, 1 261 pieces of spectral reflectance of maize leaves at different leaf positions were measured every day during its life cycle. After signal/noise analysis, the visible and near infrared (VNIR) band (400～960 nm) was selected in this study. The spectral reflectance was fitted using a spectral scatter diagram (SSD) method. Seven fitting coefficients were employed to denote the temporal variation patterns of maize leaf, which can also be fitted by bi-variate quadratic functions. The comparison of the fitted results with the original measurement data shows that the fitting results are reasonably good, where for 98.7% leaves r is larger than 0.99, and for 80.9% leaves RMSE is less than 0.001 5. All the fitted spectral reflectance is compared with the original measurement data, where r is 0.997 8, and RMSE is 0.0105. The results show that this method is particularly suitable for presenting the temporal variation patterns of the spectral reflectance of maize leaves.
[1] Blackburn G A. J. Experimental Botany, 2007, 58(4): 855. [2] Blackburn G A. Remote Sens. Environ., 1998, 66(3): 273. [3] Jacquemoud S, Verhoef W, Baret F, et al. Remote Sens. Environ., 2009, 113: S56. [4] Gitelson A A, Merzlyak M N. J. Plant Physiol., 1996, 148(3): 494. [5] Baker N R. Annu. Rev. Plant Biol., 2008, 59: 89. [6] Wu C, Niu Z, Tang Q, et al. Agr. Forest Meteorol., 2009, 149(6-7): 1015. [7] Hatfield J, Gitelson A A, Schepers J S, et al. Agron. J., 2008, 100(3): 117. [8] Feret J B, Franois C, Asner G P, et al. Remote Sens. Environ., 2008, 112(6): 3030. [9] Jacquemoud S, Baret F. Remote Sens. Environ., 1990, 34(2): 75. [10] Blackburn G A. Int. J. Remote Sens., 1998, 19(4): 657. [11] Gitelson A A. J. Plant Physiol., 2003, 160(3): 271. [12] Gitelson A A, Chivkunova O B, Merzlyak M N. Am. J. Bot., 2009, 96(10): 1861. [13] Gitelson A A, Keydan G P, Merzlyak M N. Geophys. Res. Lett., 2006, 33(11): L11402. [14] Nichol C, Grace J. Int. J. Remote Sens., 2010, 31(20): 5409. [15] Kimes D, Markham B, Tucker C, et al. Remote Sens. Environ., 1981, 11: 401. [16] Letts M G, Phelan C A, Johnson D R E, et al. Tree Physiol., 2008, 28(7): 1037. [17] Zhang X, Goldberg M D. Remote Sens. Environ., 2011, 115(2): 382. [18] Wright D L, Rasmussen V P, Ramsey R D. Geocarto. Int., 2005, 20(1): 63. [19] Ciganda V, Gitelson A, Schepers J. Agron. J., 2008, 100(5): 1409. [20] Ciganda V, Gitelson A, Schepers J. J. Plant Physiol., 2009, 166(2): 157. [21] SU Li-hong, LI Xiao-wen, LIANG Shun-lin, et al(苏理宏，李小文，梁顺林，等). Geog. Info. Sci.(地理信息科学), 2002, 4(4): 7. [22] Zhao Y, Tong Q, Zheng L, et al. Info-Tech & Info-Net. Beijing: IEEE, 2001. 115.
