Analysis Of Spectral Characteristics Of Rice Canopy Under Water Deficiency

@ Reflectance ratio of the spectrum from stressed canopy to that from well-watered canopy.

From the apparent peaks and valleys of reflectance spectra measured in the well-watered plants during the experimental period, 12 characteristics wavelengths were identified (Table 2). Among these characteristics wavelengths selected to examine their correlation to water deficits, the reflectance of 8 wavelengths had significant linear relationships with stress levels; the coefficients all greater than 0.61. The reflectance at 2245 nm had the highest r value (0.80), but not as good as at 2113.5 nm. Based on such results, it suggests that soil water stress did not change dramatically the overall pattern of reflectance spectrum of rice canopy.

Table 2. The correlation coefficients for the 13 characteristics wavelengths selected from reflectance spectra of rice

canopy in response to soil water deficits @ .


It has been reported that the absorption maximum of chlorophyll in the visible band and the near-infrared shoulder of the red-edge will be changed upon environmental stress (Horler et al., 1983). It is therefore a reasonable prediction that both position and slope of the red-edge may be altered by the impact of water stress. With hyperspectra at intervals less than 10 nm in this study, position and slope of the red-edge acquired were quite reliable and accurate (Figure 3). However, results show that changes in red-edge position and slope did not correlate to soil water potential. Thus, the red-edge is not a good spectral parameter to distinguish levels of water deficit. On the other hand, the relationship between NDVI and soil water potential was significant (figure 3), the increasing of soil water stress with decreasing value of NDVI.

4. References
· Clevers, J. G. P. W. 1988. The derivation of a simplified reflectance models for the estimation of leaf area index. Remote Sens. Environ. 25, pp.53-69.

· Clevers, J. G. P. W. 1989. The application of a weighted infrared-red vegetation index for estimating leaf area index by correcting for soil moisture. Remote Sens. Environ. 29, pp.25-37.

· Curran, P. J. 1989. Remote sensing of foliar chemistry. Remote Sens. Environ. 30, pp.271-278.

· Elvidge, C. D. 1990 Visible and near infrared reflectance characteristics of dry plant materials. Int. J. Remote Sens. 11, pp.1775-1795.

· Goetz, A. F. H. 1991. Imaging spectrometry for studying earth, air, fire and water. EARSeL Advances in Remote Sensing 1, pp.3-15.

· Horler, D. N. H., M. Dockray and J. Barber. 1983. The red edge of plant leaf reflectance. Int. J. Remoter Sens. 4, pp.273-288.

· Huete, A. R. 1988. A soil adjusted vegetation index (SAVI). Remote Sens. Environ. 25, pp.295-309.

· Kauth, R. J. and G. S. Thomas. 1976. The tasseled cap-a graphic description of the spectral-temporal development of agricultural crops as seen by Landsat. Proc. Symp. On March. Proc. Rem. Sens. Data, Purdue Univ., W. Lafayette, Ind., 4B. pp.41-51

· Richardson, A. J., and C. L. Wiegand. 1977. Distinguishing vegetation from soil background information. Photogram. Eng. Remote Sens. 43, pp.1541-1552.