In: Wagner W„ Szflcely, 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 CAPABILITIES OF TERRASAR-X IMAGERY FOR RETRIEVAL OF 
FOREST PARAMETERS 
Roland Perko, Hannes Raggam, Karlheinz Gutjahr and Mathias Schardt 
Institute of Digital Image Processing, Joanneum Research, Graz, Austria 
{roland.perko, hannes. raggam, karlheinz.gutjahr,mathias. schardt} @joanneum. at 
Technical Commission VII Symposium 2010 
KEY WORDS: Forestry, Mapping, Photogrammetry, Classification, DEM/DTM, SAR, High resolution. 
ABSTRACT: 
The TerraSAR-X mission was launched in June 2007 operating a very high resolution X-band SAR sensor. In Spotlight mode images 
are collected with 0.75m GSD and also at various look angles. The presented paper reports methodologies, algorithms and results 
emerged from the Austrian research project “Advanced Tools for TerraSAR-X Applications in GMES” with emphasis on retrieval of 
forest parameters. For deriving forest features like crown closure, vertical stand structure or stand height a digital forest canopy model 
serves as an important source of information. The procedures to be applied cover advanced stereo-radargrammetric and interferometric 
data processing, as well as image segmentation and image classification. A core development is the multi-image matching concept 
for digital surface modelling based on geometrically constrained matching, extending the standard stereo-radargrammetric approach. 
Validation of surface models generated in this way is made through comparison with LiDAR data, resulting in a standard deviation 
height error of less than 2 meters over forest. Image classification of forest regions is then based on TerraSAR-X backscatter information 
(intensity and texture), a 3D canopy height model and interferometric coherence information yielding a classification accuracy above 
90%. Such information is then directly utilized to extract forest border lines. Overall, the TerraSAR-X sensor delivers imagery that 
can be used to automatically retrieve forest parameters on a large scale, being independent of weather conditions which often cause 
problems for optical sensors due to cloud coverage. 
1 INTRODUCTION 
Figure 1: Proposed workflow for deriving forest parameters using 
TerraSAR-X data. 
underestimated. The reason for that is the fact, that the SAR 
signal in X-band penetrates into the forest canopy changing the 
InSAR phase center and therefore the reconstructed height. 
This aspect has been observed on InSAR-based processing of 
airborne X-band data (Izzawati et al., 2006, Tighe et al., 2009). 
To tackle all these difficulties we first derive digital surface 
models using a multi-image stereo-radargrammetric approach. 
Then, the resulting DSMs are corrected (undoing the canopy 
height underestimation) by applying an empirically learned 
correction model on regions of forest. 
The radargrammetric processing is described in detail in 
(Raggam et al., 2010a) and can be applied successfully due to 
the very exact pointing accuracy of the TerraSAR-X sensor 
(Bresnahan, 2009, Raggam et al., 2010b). The main steps in 
the DSM extraction are pairwise stereo matching followed by 
a joint point intersection procedure. To get robust matching 
results image triplets are used, i.e. three TerraSAR-X images 
acquired under different look angles. The main point is, that 
adjacent images (similar look angles) provide good matching, 
however unfavorably geometric properties. Therefore, for 
triplets image 1 can be matched to image 2 and image 2 to image 
3. Thus, points from image 1 are transferred to image 3 yielding 
a large intersection angle and therefore a more robust result. In 
addition image 1 and image 3 are directly matched resulting in 
TerraSAR-X is the first German satellite out of a public private 
partnership (PPP) between German Aerospace Center (DLR) 
and Astrium GmbH and was launched in June 2007. The 
novel X-band SAR sensor can acquire image products in 
Spotlight, Stripmap and ScanSAR mode at very high resolutions 
down to 0.75m (Eineder et al., 2008). One main aspect of the 
Austrian research project “Advanced Tools for TerraSAR-X 
Applications in GMES” (AT-X) dealt with the derivation of 
forest related parameters using TerraSAR-X imagery. The first 
part consists of precise image matching of such imagery for fully 
automatic derivation of digital surface models (DSM) which are 
subsequently used to derive a canopy height models (CHM). 
The second part concerns image classification with the focus on 
distinguishing forest from non-forest regions. 2 
2 OUR METHODS 
The big picture of our workflow is sketched in Figure 1. As seen, 
a DSM is extracted using multi-image radargrammetry. This 
DSM is utilized together with InSAR products and backscatter 
information to derive a forest classification. Finally, this 
segmentation helps to correct the height of canopy regions 
resulting in the final corrected DSM. 
2,1 Multi-Image DSM Generation 
The accurate 3D reconstruction of timbered regions using 
TerraSAR-X imagery alone is very challenging due to two 
reasons. First, the traditional InSAR-based processing does 
not yield appropriate results over forest as the InSAR phase 
decorrelates within the 11 days TerraSAR-X repeat cycle 
(Bamler et al., 2008). Second, even in cases of temporal 
phase correlation the resulting canopy height is systematically