The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B7. Beijing 2008 
Correlation analysis between chlorophyll content and 
spectral reflectance 
Towards exploring the bands range which could have high 
significant correlation with chlorophyll content, correlation 
analysis was carried out in 400-900nm spectral region. Linear 
and nonlinear correlation analysis was performed respectively 
to locate the optimal spectral regions (Figure 1 and Figure 2). 
Figure 1. Variation with wavelength (400-900nm) in linear 
correlation coefficient (R) between reflectance and chlorophyll 
content 
0.8 
0.7 
0.6 
0. 5 
R 2 0.4 
0.3 
0.2 
0. 1 
0 
400 500 600 700 800 900 
wavelength (nra) 
Figure 2. Variation with wavelength in the coefficient of 
determination (R 2 ) obtained when regressing reflectance against 
chlorophyll content, using an exponential model 
The reflectance in 400-500nm region showed the lowest 
correlation both linear and nonlinear with chlorophyll content. It 
has been previously shown (e.g., Gitelson et al., 1996a) that the 
red wavelength reflectance near 670nm is only sensitive to 
chlorophyll a levels below 0.003mg/cm 2 . Such low levels of 
chlorophyll can only be found in highly stressed or senescing 
leaves, such as yellow autumn leaves of deciduous species (Datt, 
1998). Though the nonlinear correlation between reflectance 
near 670-680nm and chlorophyll content is higher, due to the 
strong absorption by chlorophyll, the reflectance at 680nm 
remained nearly constant with increasing chlorophyll content. 
So 400-500nm and 670-680nm spectral regions are not the 
optimal band to estimate chlorophyll content. And the 
reflectance near 705nm showed highest correlation both linear 
and nonlinear with mixed leaves chlorophyll content. 
Correlation analysis between chlorophyll content and the 
first derivative of reflectance 
The first derivative of the reflectance curves can provide 
information about rate of change along the curve and at what 
wavelength these changes occur. Such insight is not apparent 
with simple reflectance curves. Chlorophyll variations can 
induce changes in the first derivatives of the reflectance spectra. 
The first derivatives of reflectance spectra can be defined as: 
DR: = 
Pi+\ Pi-\ 
A/t 
(1) 
where p i+l and p j _ l are the reflectance at wavelength i +1 
and i -1 respectively, AX is the wavelength difference between 
i +1 and i-1, so AX is equal to 2 here. According to this 
equation, the first derivatives of the reflectance of fresh leaves 
in LOPEX93 database can be calculated. 
Figure 3. Variations with wavelength in the correlation 
coefficient obtained when regressing chlorophyll content 
against 5R, using a linear model 
Figure3 illustrated the variations with wavelength in the 
coefficient for the relationship between the amplitude of the 
first derivative, 5R, and chlorophyll content. The plot was 
constructed using a linear regression model to derive the R 
value. The plot showed a good degree correlation in several 
bands within the 400-800nm region. However, the highest 
correlation between 8R and chlorophyll content was near 
530-545nm and 725-735nm. 
wavelength (run) 
Figure 4. Variations with wavelength in the coefficient of 
determination (R 2 ) obtained when regressing 8R against 
chlorophyll content, using an exponential model 
Figure 4 illustrated the variations with wavelength in the 
coefficient of determination for the relationship between the 
amplitude of the first derivative, 8R, and chlorophyll content. 
The plot was constructed using an exponential regression model 
to derive the R 2 value, the best fit model for most wavelengths, 
and shows a good degree correlation in several bands within the 
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