Because of regression calibration the intensities in both 
  
  
AX, = studentized difference of Xe {AM, ASD} 
  
  
  
  
dependent and independent images were scaled to the level of AXı = difference of X e{AM,, ASd, } expressed in dn on 
independent image. When more generic training data was channel i 
considered, the regression calibrated difference observations RMSE = root mean square error of the calibration model 
were studentized (in the sense of Weisberg 1985) according to channel i 
the leverage and regression error (equation 7) (e.g. Olsson lev, leverage of stand x mean intensity on channel i 
1994). (Weisberg 1995). 
AX rure (7) 
RMSE, \[1+ lev, 
3. RESULTS 
The coefficients of determination in calibration models are 
presented in table 3. Studentized 
4p difference 
Table 3. The coefficients of determination of the models - 
applied in calibration | 
Coefficient of determination at different sol 
calibration intervals I 
™ H93-90 H92-90 H93-92 .. ppm: 
channel xL |. . | 
1 0.66 0.79 0.84 TE di 
2 0.66 0.79 0.80 | 
3 0.59 0.82 0.75 10|- 
4 0.93 0.94 0.93 | mu 
5 0.92 0.93 0.94 | I“ Standard 
6 0.83 0.90 0.73 0 deviation 
7 0.80 0.85 0.88 Br ne 9 
  
The RMSE's of the regression calibration varied from 0.22 on 
channel 7 to 0.88 on channel 6 expressed in eight bit digital 
number (DN) scale. 
After regression calibration and studentization, the timing of 
the changes within the three-year interval did not affect to the 
separability of the change classes (Figures 1, 2, 3 and 4). The 
only exception was the regeneration cut where the earlier 
treatments seemed to have larger spectral responses compared 
to later ones. However, this was probably due to the small 
number of observations.. The class 'untreated' did not differ 
from zero according the T-test at 1% risk. The decreasing 
response in 'clear cut' is due to soil preparation which was 
combined with two earlier intervals, but had not yet been 
accomplished in the later interval (Figures 1 and 2) 
The separability of different forest management treatments 
based on their spectral response was compared between 
uncalibrated and regression calibrated/studentized difference 
images with three-year interval between images. According 
to T-test all the treatment classes were separable at least on 
one channel based, on differences of stand mean intensities 
only. The best channels for separating different treatments 
were TM 2,3,5 and 7. None of the change classes were 
separable on channel four. The calibration error was relatively 
small compared to spectral changes due to treatments 
(Figures 1,2,3 and 4). However, the channels from which the 
different treatments were separable varies between 
uncalibrated and regression calibrated/studentized calibration 
alternatives. 
Implementation period 
Figure 1. Spectral change of clear cut on the difference image 
H93-90, TM channel 3. 
  
  
  
  
Studentized 
150 difference 
100} | 
50H 
M calib 
error 
| Standard 
0 deviation 
90-91 91-92 92-93 
Implementation period 
Figure 2. Spectral change of clear cut on the difference image 
H93-90, TM channel 5. 
International Archives of Photogrammetry and Remote Sensing. Vol. XXXI, Part B7. Vienna 1996 
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