plain the poor correspondence for the dry and moist classes. This illustrates well the difficulties of 
including subjective components in the field measurements in an otherwise objective and unbiased system. 
FIGURE 2 
Correspondence matrix for computer and field estimates of sub-surface waterflow. 
Estimati 
on in the 
field: 
Seldom 
Shorter 
Longer 
Seldom 
582 
50 
17 
Estimation 
by computer: 
Shorter 
82 
57 
19 
Longer 
38 
52 
50 
FIGURE 3 
Correspondence matrix for field and computer estimates of ground moisture. 
Estimation in the field: 
Dry Mesic Moist 
Dry 
Estimation 
by computer: Mesic 
Moist 
5 165 3 
25 523 29 
1 162 30 
DISCUSSION 
It seems that site variables in the existing SCS system can be estimated digitally with good 
reliability. It seems also that the subjective measurements in the field can give doubtful results. It 
will probably always be troublesome to achieve, using the current technique, a field classification of 
sufficient accuracy to evaluate alternative methods. 
The continued work with digital site classification will not use the existing SCS as reference. This 
decision has been made partly because of the need to gain good ground truth, and because of low- 
precision in the regression equations due to the use of simplified parameters. The reference material 
will instead be plot data with site index determined with the higher-precision and also objective method 
based on measurement of the height and age of the trees. 
REFERENCES 
HAGNER, 0 1989. Computer aided forest mapping and estimation of stand characteristics using satellite 
remote sensing. SUAS, Remote Sensing Laboratory, Umea. 
HAGGLUND, B & LUNDMARK, J-E 1977. Estimation of growth potential through site variables, scots pine and 
norway spruce in Sweden (in Swedish). SUAS, Inst for Vaxtekologi och marklara, report 28. 
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