The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Voi. XXXVII. Part B7. Beijing 2008 
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Measured SOM content <%) 
Figure. 4 Comparison between measured value 
and predicted with reflectance 
Measured SOM content (%) 
Figure. 6 Comparison between measured value and 
predicted with logarithm of reflectance 
4 CONCLUSIONS 
(1) In the studied 350-2500 nm wavelength range, 
absorption peak of SOM does not exist. But in the range of 
wavelength, spectral reflectance is negative correlated with 
SOM content, and the highest correlation is near 675 nm. The 
results are consistent with previous study ll4] , considering that 
SOM is negative correlated with reflectance in the whole range 
of visible light. This study further extends the conclusion to 
infrared bands. 
(2) The reciprocal of reflectance logarithmic l/lg 7? was 
inefficient for detecting SOM content. It can not increase the 
correlation between spectral indicator and SOM content, but 
decreased their correlation. All the other transforms, such as 
reciprocal, logarithm, square root and differentiate, improve 
sensitivity to SOM content to different extent. The transform 
type of (lg/?) is the most significant among them. The 
logarithmic transform of reflectance reduces effects of 
multiplicative factors induced by changes of illumination 
conditions. But it is insufficient to only perform logarithmic 
transform, it also need differential treatment to obtain better 
effect. Spectral differential technique can partially eliminate 
Figure 5 Comparison between measured value and 
predicted with square root of reflectance 
Measured SOM content (%) 
Figure. 7 Comparison between measured value and predicted 
with order 1 derivative of the logarithm of reflectance 
atmospheric effect; especially the first order differential 
treatment can remove effects of partially linear or 
approximately linear background and noise spectra on objective 
spectra. 
(3) Overall, before performing differential transform, the 
detect ability of SOM content at visible light wavebands is 
stronger than infrared bands, and the most sensitive band is near 
675 nm; while after spectral differential transform, infrared 
bands becomes more sensitive, and the correlation coefficient 
between (lgR)' and SOM content is as high as 0.89 at 2187 nm 
position, the maximum among congeneric correlation 
coefficients. 
(4) The optimal model for predicting SOM content is the 
regression equation composed with (lgi?)' value at 849 nm, 
1681 nm and 2187 nm wavebands as independent variables: 
Y = 1.772 + 1004.071X 2187 + 2893.272X 849 - 1682.9\5X m] 
In the equation X = (lg/?) » Y is SOM content (%). The 
Adjusted i? 2 =0.885 and RMSE=0.36. It is the best one among all 
models. Although the model is distinct from the predictive 
model for SOM content established by Krishnan , and the 
selected wavebands are also totally different, but they are in