red), 
— 1.75 
ents 
ntly 
model. 
ter- 
Theat 
ere 
re- 
al 
iment 
sure- 
ldron 
tili- 
m 
vars 
and 
land 
er- 
ropped 
sible, 
s for 
The effect of planting date on spectral response is also illus- 
trated in Figure 1. The differences are attributed primarily to 
differences in the amount of vegetation present, as well as differ- 
ences in maturity stage. 
Adding nitrogen fertilizer increased the amount of green vege- 
tation early in the growing season. The fertilized treatment had the 
spectral characteristics of a greener, denser vegetative canopy: 
decreased red reflectance, slightly greater near infrared reflectance, 
and reduced middle infrared reflectance. 
The two wheat cultivars, Olaf (semi-dwarf, awned) and Waldron 
(standard height, awnless), were similar in appearance before heading. 
After heading, some differences between the two cultivars were visually 
apparent, but are probably not significant. The greatest differences 
were in the middle infrared, indicating a difference in the moisture 
and biomass between the two cultivars at this growth stage. 
These spectra emphasize that the wheat canopy is very dynamic 
and that the spectral reflectance of a canopy is influenced by many 
cultural factors. More quantitative analyses of the effect of 
agronomic treatments and environmental variables on reflectance of 
wheat are currently being conducted. 
Relation of Canopy Variables to Multispectral Reflectance 
The primary objectives of this study were to determine the rela- 
tionship of canopy variables to reflectance and to assess the potential 
for estimating them from remotely sensed measurements of reflectance. 
The canopy variables selected for analysis are indicators of crop vigor 
and growth which could be inputs to a yield model and which preliminary 
analyses showed were most strongly related to spectral response. In 
the remainder of the paper the effect of varying amounts of vegetation 
and maturity stage on the spectra of wheat canopies, the relationship 
of canopy variables to reflectance in different regions of the spectrum, 
and the potential capability to predict canopy variables from reflectance 
measurements are examined. As part of the analysis the wavelength bands 
of current and proposed future satellite multispectral scanner systems 
were compared. 
The amount of vegetation present is one of the principal factors 
influencing the reflectance of crop canopies. Figure 2 illustrates 
the effect of amount of vegetation as measured by leaf area index, 
biomass, and percent soil cover on the spectral response during the 
period between tillering and the beginning of heading when the maximum 
green leaf area was reached. As leaf area and biomass increase there 
is a progressive and characteristic decrease in the reflectance of the 
chlorophyll absorption region, increase in the near infrared reflectance, 
and decrease in the middle infrared reflectance.