a 
  
  
d 
d 
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Inclusion of multispectral data would also help reduce the 
dependency on the presence of straight edges to identify an 
object as a building (rather than a tree). This way, we would 
also be able to detect other shapes of new buildings such as the 
oval building in the northeast side of this test dataset. 
1.6 Conclusion 
IMAGINE Objective appears to provide a robust capability for 
detecting specific types of change between point cloud data 
from two different dates, even in the absence of other ancillary 
information such as co-registered and contemporaneous 
multispectral data or even pre-classification of the height points. 
Additionally, the approach outlined requires no training of the 
classifier. The user does not need to specify locations to serve 
as examples of the change of interest. Traditionally, having to 
provide training samples slows down the analysis process and 
results in approaches which can't easily be transported between 
data sets. Instead the user might have to make minor 
adjustments to some of the parameters in the IMAGINE 
Objective project to better reflect the local conditions, but that 
is all. 
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B7, 2012 
XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia