International Archives of the 
Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B7. Istanbul 2004 
  
0.9 
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0.7 
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0.4 
SAVI 
  
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Reflectance 
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Wavelength 
Figure 3. Spectral reflectance of alfalfa under 100 cm water table 
Moreover, NDVI and SAVI was computed for all the 
treatments (figure 5) was shown that SAVI has the ability to 
demonstrate alfalfa response to vartiation in water table level. 
  
cete ence 
a 
—e— SAVI 
  
  
  
0 cm 50cm 100 cm 150 cm 
Figure 5.NDVI and SAVI of alfalfa grown undervarying 
water table depths 
In addition to that, the relationship between canopy surface 
temperature and vegetation indices was studied. Figure 7 
show the Ts-Ta-SAVI (temperature difference and soil 
  
SAVI 
  
  
  
  
  
0 1 2 3 4 5 
Ts-Tc (°C) 
Figure 6 Temperature diference — SAVI trapezoid of alfalfa 
adujsted vegetation index. 
4. REFERENCES 
Gurney, R.J., Ormsby, 1B. Hall, DK. 1983. A comparison 
of remotely sensed surface temperature and biomass 
estimates for aiding evapotranspiration determination in 
1000 1300 1600 1900 2200 2500 
central Alaska. Proceedings International 
Conference of Permafrost, 401-404. 
Hope, A.S. and McDowell, T.P. 1992. The relationship 
of Fourth 
between surface temperature and a spectral vegetation 
index of a tallgrass prairie: effects of burning and other 
landscape controls. International Journal of Remote 
Sensing, 13, 2849-2863. 
Huete, A. (1988) Soil-adjusted vegetation index (SAVI). 
Remote Sensing of Environment, 25, 295-309. 
Idso, S.B., Jackson, R.D., Pinter, P.J., Reginato, R.J. and 
Hatfield, J.L. 1981. Normalizing the stress-degree-day 
parameter for environmental variability. Agricultural 
Meteorology, 24, 24-55. 
Jackson, R.D., Moran, M.S., Gay, L.W. and Raymound, L.H. 
1987. Evaluating evaporation from field crops using airborne 
radiometry and ground-based meteorological data. /rrigation 
Science, 8, 81-90. 
Moran, M.S., Clarke, T.R., Inoue, Y. and Vidal, A. 1994. 
Estimating crop water deficit using the relation between 
surface-air temperature and spectral vegetation index. 
Remote Sensing of Environment, 49, 246-263. 
Moran, M.S., Jackson, R.D., Hart, G.F., Slater, P.N., Bartell, 
R.J., Riggar, S., Gellman, D. and Santer, P. 1990. Obtaining 
surface reflectance factors from atmospheric and view angle 
corrected SPOT-1 HRV data. 
Environment, 32, 203-214. 
Moran, M.S., Pinter, P.J., Clothier, B.E. and Allen, S.G. 
Remote Sensing of 
1989. Effects of water stress on the canopy architecture and 
spectral indices of irrigated alfalfa. Remote Sensing of 
Environment, 29, 251-261. 
Price, J.C. 1982. On the use of satellite data to infer surface 
fluxes at meteorological scale. Journal of Applied 
Meteorology, 21, 1111-1122. 
Reginato, R.J., Idso, S.B., Vedder, J.F., Jackson, R.D., 
Blanchard, M.B. and Goettelman, R. 1976. Soil water content 
and evaporation determined by thermal parameters obtained 
from ground-based and remote measurements. Journal of 
Geophysical Research, 81, 1617-1620. 
1985. 
Reginato, R.J., Jackson, R.D. and Pinter, P.J. 
Evapotranspiration calculated from remote multi spectral 
and ground station meteorological data. Remote Sensing of 
Environment, 18, 73-89. 
Shakir, S.H. and B. Girmay-Gwahid 1998. Spectral 
Characterization of Water Stress Impact on Some