In: Wagner W., Szekely, B. (eds.): ISPRS ТС VII Symposium - 100 Years ISPRS, Vienna, Austria, July 5-7, 2010, IAPRS, Vol. XXXVIII, Part 7B 
correct: 90.37% 
ground truth 
forest 
non-forest 
estimation 
forest 
40.01% 
7.68% 
non-forest 
1.96% 
50.36% 
Table 4: Confusion matrix of forest segmentation. 
Forest Border Lines. Finally, forest border lines can directly be 
extracted from the segmentation result via edge detection. Fig 
ure 8 shows some examples. Overall, the quality of extracted 
forest border lines is higher for huge dense forests than for small 
isolated stands (this aspect was also observed in (Breidenbach et 
al., 2009)), where small stands are often not detected at all. Nev 
ertheless, forest border lines are in general very well extracted 
and their accuracy is directly dependent on the forest segmenta 
tion. 
ground truth TerraSAR-X derived 
Figure 8: Detailed views on forest border line extraction for two 
subsets. On the left ground truth border lines are given and on 
the right the automatically extracted borders using TerraSAR-X 
alone. 
5 CONCLUSIONS AND FUTURE WORK 
TerraSAR-X imagery enables the retrieval of certain forest 
parameters. In particular, multiple TerraSAR-X images 
representing the same area on ground under different look angles 
can be used to fully automatically derive accurate DSMs. In case 
when reference DTMs are available the canopy height model 
can be extracted. Such forest canopy height is an important 
parameter as it is strongly correlated with forest parameters, such 
as forest biomass, timber volume or carbon stocks. Furthermore, 
it serve as an important cue for classification of forest types 
and condition, forest morphology, crown closure, vertical 
structure and stands height (Hyyppa et al., 2000). The presented 
study revealed that the height of the canopy is systematically 
underestimated as the SAR signal in X-band penetrates into the 
canopy. Therefore, a forest segmentation is proposed yielding 
an accuracy of 90%. This segmentation result is subsequently 
applied to correct the canopy height bias in regions of forest. 
Incorporating this approach, the TerraSAR-X DSMs have an 
average height accuracy of 20 cm and a standard deviation of 
about 2 meters on bare ground and over forest. 
However, the canopy underestimation depends on various 
aspects, including tree species, forest stand density, tree height 
and look angles. The forest used in the presented study 
domiciles more or less exclusively dense stands of deciduous 
trees. It is therefore expected that the canopy underestimation 
will be larger for coniferous trees and for clearer stands. 
Future work should focus on a comparison to TanDEM-X DSMs 
compromising multiple InSAR pairs with different look angles 
to further understand the penetration into the canopy of X-band 
signals. 
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