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g^ value is reached after the entry of three out of the six possible 
thematic mapper bands. However, the 'C ' values indicate that five 
bands would have to be used to have an unbiased prediction of leaf 
area index and four bands would be necessary for percent soil cover. 
The agreement between the measured and predicted leaf area index 
is shown in Figure 7. Similar results were obtained for the other 
canopy variables. There are several factors that make a perfect pre- 
diction impossible for these data, including: (1) the agronomic 
measurements of the crop canopy were subject to measurement error, 
(2) plant maturity stage has an effect on reflectance (for example, 
a canopy with an LAI of 1.0 early in the season has a different 
spectral response than a canopy with an LAT of 1.0 later in the 
season), (3) the data that the prediction equations are derived from 
contains variation induced by the different agronomic treatment levels, 
and (4) the time of day that the data were collected may have some 
effect on canopy reflectance. Despite the variation induced by each 
of these factors, measurements in a small number of wavelength bands 
in important regions of the spectrum can explain much of the variation 
in canopy variables and thus, result in satisfactory predictions of 
canopy variables. 
Table 3 shows the maximum R^ value obtainable using the Landsat 
bands, the best four out of the six possible thematic mapper bands, 
and then all six thematic mapper bands to predict each canopy variable. 
In every case the best four out of six thematic mapper bands explained 
more of the variation in a canopy variable than the four Landsat bands. 
Addition of the other two thematic mapper bands resulted in only small 
increases in the RZ values. 
Summary and Conclusions 
Spectral and agronomic measurements of spring wheat canopies were 
analyzed to determine the relation of agronomic properties of crop 
canopies to their spectral reflectance. Initial analyses showed that 
several agronomic treatments such as soil moisture and nitrogen fer- 
tilization affect the spectra of wheat. A strong relationship between 
spectral response and percent soil cover, leaf area index, biomass and 
plant water content was found. The relationship, however, is influenced 
by crop maturity. The best time period for assessing these canopy vari- 
ables is from the tillering to heading stages of development. Prior to 
tillering the spectral response is strongly dominated by the soil back- 
ground and, as the crop begins to ripen, the spectral sensitivity to 
measures such as leaf area index, biomass, and plant water content 
decreases. 
In each wavelength region, the correlation of the thematic mapper 
band with crop canopy variables was greater than that of the corresponding 
Landsat MSS band. Prediction equations developed to explain the variation 
in crop canopy variables showed that the 2.08-2.35 um wavelength band was 
the single most important band in explaining the variation in fresh