The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B4. Beijing 2008 
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ADS40 Forest cove 
Threshold 
Quantize Window green=3x3. blue=axS, red=7x7 
Figure 3. Threshold vs. CBO of "Forest cove" 
qw=3x3 th=0.25 CBO=92.1 
qw=7x7 th=0.80 CBO=30.9 
qw=7x7 th=0.85 CBO=26.1 
Figure 4. CBO "forest cove" 
The evaluation of Figure 3 and 4 reveal the non-linear 
behaviour of the parameter space for th. The regression line for 
all quantization window sizes shows that higher threshold 
values yield lower errors, if the window size is 7x7. With 
smaller window sizes and increasing threshold, the error area is 
decreasing slower. 
The ground truth in Figure 5 contains a typical "straight" forest 
boundary and additionally one region as a representative gap in 
the forest cover. The smallest CBO-value of 9.8 (threshold=0.95) 
from Figure 7 confirms the correct selection by visual 
comparison. Missing or additional regions within the forest 
increase the CBO more than the comparatively small 
differences along the horizontal forest edge. This desired effect 
corresponds with the fact, that topological errors should be 
weighted more than boundary differences. Forest edges are 
often also cluttered with shadow artifacts and therefore the 
errors caused by under- and over-segmentations lead to more 
robust CBO-values. 
qw=7x7 th=0.25 CB067.9 
Figure 5. Ground truth "Straight forest edge" 
qw=5x5 th=0.85 CBO=64.2