In: Wagner W., Szekely, B. (eds.): ISPRS TC VII Symposium - 100 Years ISPRS, Vienna, Austria, July 5-7, 2010, IAPRS, Vol. XXXVIII, Part 7B 
V demolished A vegetation 
A new X terrain 
t> partly demolished m others 
<1 partly new 
Fig 8. Detected changes labelled by reference and clustered by 
elevation change and area 
area [sqm] 
Fig. 9. Overall accuracy of detected building changes as a 
function of changed area. The solid line shows the 
actual accuracy distribution, while the dashed line 
shows the theoretical accuracy distribution, if 
vegetation would be classified correctly. 
6. CONCLUSION AND OUTLOOK 
The presented study shows that urban areas are highly dynamic 
environments where major changes on buildings occur also in 
rather short time intervals (three months). Changes in ALS data 
appear from several sources such as anthropogenic objects, 
temporary objects, vegetation, and changes due to data capture 
conditions and data quality. The assessment of the change 
detection results shows that the appearance and phenological 
changes of high vegetation influence the detection success 
most. If the building detection method tends to misclassify 
vegetation, care has to be taken to the phenological behaviour 
of the vegetation between the data acquisition times. One would 
expect similar good detection results for demolished buildings 
if a winter and spring data set is compared. Misclassification 
due to planting of new trees did not occur in the data set. The 
results show the importance of a reliable vegetation detection 
procedure in order to be able to monitor changes in urban areas. 
A more advanced vegetation detection working in the point 
cloud and making use of full-waveform information might 
improve the results significantly (e.g. Rutzinger et al., 2008). 
Future work should focus on the detection and differentiation of 
building footprints with an area below 100 sqm and height 
changes below 3 m in order to be able to detect changes on 
small buildings and to distinguish them from temporary objects. 
In order to be able to analyse objects in this scale an algorithm 
working in the point cloud directly might be needed. 
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