In: Wagner W„ Szekely, B. (eds.): ISPRS TC VII Symposium - 100 Years ISPRS, Vienna, Austria, July 5-7, 2010, IAPRS, Vol. XXXVIII, Part 7B 
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the detection mask. Varying water level can result in detected 
changes at the coast. 
Obviously, every object or parameter which caused a 
significant backscatter change will result in a detection. 
However, customers may only be interested in specific changes, 
like e.g. in new constructions. 
To analyse the scenery to gain additional knowledge for the 
qualification of detected changes, different measures have been 
used for segmentation and classification: Coefficient of 
variation, Coherence and statistics of the intensity. 
Five broad classes have been evaluated: water, forest, open 
land, urban and coastal areas. The result of this classification is 
shown in Figure 5. 
Assuming a certain application and that a user is only interested 
in changes on land and not in variations on the sea e.g. due to 
waves, varying water level and ships, the following reduction 
has been applied. Changes on water and coastal areas have been 
eliminated as unrequested changes. 
The information about the change direction of the backscatter 
(reduced or increased) has been combined with the 
classification results of Figure 5. The result is shown in Figure 
6 and a detail of it in Figure 7. 
Figure 7: Detail of detected and assessed changes. 
The clearing on the left hand side has been classified as a 
change type in forest areas with a decreased backscatter, which 
is typically the case for clearings. At the new forest edges an 
increased backscatter is caused by layover. 
The new construction at the area around the airport were 
classified as open land, which is true since in the first 
acquisition there was bare soil and the increased backscatter 
gives the indication of a new object. The temporarily parked 
wagons at the runway are classified as a change in urban areas, 
where usually many changes are occurring independent on the 
change direction. Domain specific interpretation knowledge is 
needed to verify the plausibility of such changes and qualify it 
as temporary change. 
The detected and assessed changes are plausible. However, the 
assessment depends on the quality of the classification. Even 
though no apriori information and only a small amount of SAR 
data sets have been available the customer can be provided 
with, a rough idea about the type of occurring changes. 
5. CONCLUSION 
In this paper an approach for a combined detection and 
qualification of changes has been presented. The integration of 
additional information derived directly from the images is 
helpful to restrict search areas and to give more information to 
judge the plausibility of changes, if other a-priori information is 
not available. 
The assessment depends on the accuracy of the classification of 
the imagery. However, an indication about the change direction 
can be given and can be helpful for further interpretation. 
In future tasks, the improvement of the assessment can be 
conducted by using e.g. dual-polarised data and a comparison 
of classifications of pre and post event images. 
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