measurements are sufficiently acquired over buildings (see 
figure 13 (a)). However, as lidar points are acquired with 
less point density over a building, more errors are produced 
around its boundaries (figure 13 (b) and (c)). This is because 
the detection of data-driven lines and model-driven lines is 
more difficult over a building with coarser point density than 
the one with denser point density. As a result, mis-location 
of data-driven lines and model-driven lines leads to the 
generation of delineation errors around building boundaries. 
    
       
     
E Et » a 
Figure 13. Building delineation errors; the first column 
shows cut-out Ikonos images overlaid with 
building-labelled lidar points; the second column 
shows building delineation errors 
     
(c) UCL building map — (d) OS MasterMap 
Figure 14. Reference data errors 
  
Reference data error: these errors are caused by the 
inherent faults in the OS MasterMap” (see yellow coloured 
pixel in figure 12). As can be seen in figure 14, the UCL 
building map can successfully delineate boundaries of a 
building based on the result of lidar measurements and 
Ikonos image. However, the OS building map missed some 
part of that building (cf. figure 14 (c) and (d)). As outlined 
earlier, this error caused by a time difference between the 
acquisition of the Ikonos image and lidar data, and the 
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B3. Istanbul 2004 
construction of the OS data. The analysis of the reference 
errors suggests that the developed building extraction 
technique can be also used for applications detecting 
changes in an urban environment and supporting map 
compilation. 
7. CONCLUSIONS 
This paper presented a system for automatically detecting 
building objects and delineating their boundaries from 
Ikonos images and lidar data. A few new ideas to combine 
complementary nature of intensity images and high-quality 
of 3D information to solve problems associated with 
building detection and building description are introduced. 
The overall success of the developed building extraction 
system was evaluated in comparison with the OS 
MasterMap" ground plan. The results highlights Ikonos 
images can be used in topographic mapping at large scale in 
a combination of lidar data. The current system is limited to 
delineating polygonal shapes of buildings with flat roofs. 
Thus, a further development must be directed to reconstruct 
3D roof structures based on the ground plans extracted by 
the current techniques. 
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