Full text: XVIIIth Congress (Part B4)

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offsets determination, one of the images is aligned to the 
other by polynomial interpolation. 
Next, the images are cross correlated to generate the 
interferogram, which is a complex image by its self. 
Selecting a flat terrain area in the image and performing 
a 2D FFT on its interferogram, the azimuth and range 
phase trends for a plane approximating the observed 
surface are determined. These trends are then 
subtracted from the interferograms. The interferogram is 
then multi-looked by typically 10 pixels in azimuth and 2 
pixels in range. The interferogram image is smoothed by 
adaptive low pass filtering, i.e. moving box averaging and 
directional gauss filter, before being unwrapped. For the 
unwrapping the cuts placing algorithm was used. For 
display purposes, the resulting wrapped and unwrapped 
phases are also scaled to gray value images. 
The unwrapped data are then converted to a ground 
range DTM by selecting control tie points (GCP) from a 
reference map of the area and the use of the orbit 
information extracted from the CEOS format file header 
information. For details of the DTM generation procedure 
see (Kenyi and Raggam 1995). 
4. RESULTS 
The Weilerswist data, fringes could only be generated 
from the first third of the scene. Therefor, the analysis 
were only concentrated on this area. Luckily, for the area 
around the city of Dortmund the coherency was 
excellent, almost the whole quarter scene and all two 
orbit pairs. Good quality fringes were generated which 
implies generation of a DTM for the whole quarter scene 
(partial quarter scenes INSAR DTMs are mostly 
presented in the literature). 
Normally, the wrapped or unwrapped phase images 
follow the contour or shape of the topography of the 
imaged terrain. However, as observed in the phase 
images generated, it is not the case for Weilerswist area 
test data. Deviations from the local topography were 
observed in the fringe image of this area. These phase 
deviations have been identified as atmospheric effects 
(Kenyi and Raggam 1995). Figure 1 shows the flatten 
fringe image of the Weilerswist area, where the phase 
anomalies are clearly visible in the center of the image. 
However, no such phase anomalies were detected in the 
fringes of the area around the city of Dortmund; instead 
small details such as artificial hills and man made 
features could be clearly detected. Figure 2 shows a 
flatten fringe of the dortmund area, namely orbit pair 
13896 - 13939. 
In figure 3, the INSAR generated DTM for the Weilerswist 
area is shwon in a contour lines presentation. For 
comparison a DTM was created from digitised contour 
lines of a topographic map in a 1:50.000 scale. Figure 4 
Shows this map-derived reference DTM in a contour lines 
coding similar to that of the INSAR generated DTM. In 
order to assess the errors in the INSAR DTM, a 
difference of the two DTMs was computed. Figure 5 
shows the difference DTM in contour lines presentation 
443 
too. Whereas, in tables 1 and 2 the statistical errors for 
respectively, the generated DTM (GCPs) and the 
difference DTM are presented. 
5. DISCUSSION 
For the entire area the standard deviation of the elevation 
differences was about 11 meters. This is slightly worse 
than the RMS height error of about 9 meters for the 
GCPs (see Tables 1 and 2). Moreover, the 
interferometric DTM is shifted on average by 2 meters in 
comparison to the map derived DTM. The maximum 
error was around 50 meters, whereas that of the GCPs 
was about 14 meters. The 50 meters error turned out as 
local deviations due to the atmospheric turbulence. 
6. CONCLUSIONS 
Although, work is still going on for the generation of the 
DTMs from the unwrapped fringes of the Dortmund test 
area by the time of preparation of this paper, it can be 
concluded that even at relatively small baseline INSAR 
derived DTMs gives height information with acceptable 
errors. However, enough care must be exercise due to 
the fact that atmospheric turbulence can introduce errors 
of large magnitude in the INSAR height measurements. 
Whereas, concerning fringe smoothing, the moving box 
averaging filter performs best within largely spaced 
fringes and conversely the Gaussian directional filter. 
7. REFERENCES 
Geudtner, D., M. Schwäbisch and R. Winter, 1994. SAR- 
interferometry with ERS-1 data. In: Proceedings of 
PIERS'94 Conference, Noordwijk, The Netherlands. 
Kenyi, LW., H. Raggam and E. Kubista, 1996. Feasibility 
of atmospheric effect in interferometric data and its 
interpretation. ESA ESTEC-XEP Report, Prepared by the 
Institutes of Digital Image Processing and Applied 
Systems Technology, Joanneum Research. 
Massonet, D., M. Rossi, C. Carmona, F. Adragana, G. 
Peltzner, K. Feigl and T. Rabaute, 1993. The 
displacement field of the Landers earthquake mapped by 
radar interferometry. In: Nature, Vol. 364, pp. 138-142. 
Prati, C., F. Rocca and A. Monti-Guarnieri, 1992. SAR 
interferometry experiments with ERS-1. In: Proceedings 
of 1st ERS-1 Symposium, Cannes, France, pp. 211-218. 
Zebker, H., and J. Villasenor, 1992. Decorrelation in 
interferometric radar echoes. In: IEEE Trans. Geoscience 
and Remote Sensing, Vol. 30, No. 5, pp. 950-959. 
Zebker, H., C. Werner, P. Rosen and S. Hensley, 1994. 
Accuracy of topographic maps derived from ERS-1 
interferometric radar. n: IEEE Trans. Geoscience and 
Remote Sensing, Vol. 32, No. 4, pp. 823-836. 
International Archives of Photogrammetry and Remote Sensing. Vol. XXXI, Part B4. Vienna 1996 
 
	        
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