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International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B3. Istanbul 2004 
no systematic offsets were observed. Most likely, the offsets 
shown in Figure 5 are caused by the monoplotting procedure 
used for the production of the topographical database. After 
applying the determined shifts to the database objects, this 
error should not lead to errors in the subsequent change 
detection step. 
i a 
C 
  
Figure 5: Systematic offsets between building segments in 
the laser data and the contours of the 
TOP1Ovector map. 
6.4 Analysis of detected changes 
The results of the change detection are visualised in Figures 6 
and 7. Figure 6 shows the detected new and demolished 
buildings. The buildings classified as changed are shown in 
Figure 7. All demolished buildings are detected correctly. If a 
building was demolished and replace by a completely new 
building, this building was classified as changed. Also these 
type of demolished and rebuild buildings were detected 
correctly. 
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Figure 6: Results of detection of new and demolished 
buildings. The segments extracted from the laser 
data are shown in light grey and green. The map 
objects of the TOP10vector map are overlaid in 
black and red. The red objects are classified as 
demolished buildings. The green segments are 
classified as new buildings. 
The detection of new buildings appeared to be more difficult. 
All new buildings are detected correctly, but in addition some 
sheds were detected in the laser data that are not present in 
the map. These incorrectly detected “new” buildings were 
caused by a different interpretation of the visibility rule in the 
mapping catalogue. Whereas our algorithm checks for a line 
of sight between the shed and the nearest road, the mapping 
agency first determines the main building to which the shed 
belongs and then argues whether the shed can be seen from 
the road at the front of the main building. Such a rule is 
actually quite complex and requires some scene interpretation 
that is difficult to implement. 
Figure 7: Segments in the laser data classified as changed 
buildings. 
The buildings that were classified as changed fell into three 
categories: 
e Several buildings were indeed changed, or demolished 
and replaced. 
e In a few cases vegetation adjacent to buildings led to 
enlarged laser data segments. These were incorrectly 
interpreted as building extensions. 
e Finally, the change detection revealed several errors in 
the topographical database. One example is shown in 
Figure 8. Whereas the operator mapped three separate 
buildings, the laser data shows that these buildings are 
connected by lower parts with flat roofs. 
  
Figure 8: Detected mapping error (see text). Left: laser data 
segments (grey) and database objects (green 
(dark)) Right: colour image of a three-line 
scanner 
7. CONCLUSIONS 
In this paper a study for automated change detection of 
buildings in a medium scale digital map using airborne laser