The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B4. Beijing 2008 
object of similar reflectance properties, it could be considered 
as verified, too, despite the absence of the structural indicators. 
Another idea to enhance the segmentation results is to use a 
priori knowledge about the typical shape of management units 
to introduce additional constraints. Using the information that 
the boundaries of management units usually consist of straight 
line segments that are orthogonal or nearly orthogonal could 
improve the results for the examples given in Figure 7 and 
Figure 8. Unfortunately, these geometrical constraints could 
hardly improve the segmentation result in Figure 9. 
c) d) 
Figure 8. a) Original image, taken from the same IKONOS 
scene as Figure la; b) Results of segmentation 
(smoothness for Watershed = 1); c) Results of 
segmentation (smoothness for Watershed = 5); 
d) white lines: segment boundaries from c), black 
lines: results of edge detection. 
variations of the soil properties, the homogenous regions are to 
a large degree coherent with the different management units 
existing in a GIS object. The segmentation algorithm is still 
work in progress, but the preliminary results presented in this 
paper show the potential of the algorithm for the verification 
approach. Even though a complete segmentation of 
management units seems to be impossible, the segmentation 
algorithm enhances the automatic verification process of GIS 
object. The level of segmentation that could achieved is already 
an important improvement of the verification approach. 
Future work comprises an improvement of the segmentation 
algorithm, e.g. by introducing additional (geometrical) 
constraints, and the implementation of the synthesis of the 
verification results achieved for the individual segments: at this 
instance, segmentation errors could be compensated. 
Furthermore, a more detailed evaluation of the improvement 
achieved by the segmentation is to be carried out. 
ACKNOWLEDGEMENTS 
This work was supported by the German Federal Agency for 
Cartography and Geodesy (BKG). It was also supported by the 
Early Career Grant 600380 of the University of Melbourne. 
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Figure 9. RGB IKONOS image (left); grouping result with 
smoothness for watershed = 1 (middle); grouping 
result with smoothness for watershed = 5 (right) 
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