International Archives of Photogrammetry and Remote Sensing, Vol. 32, Part 7-4-3 W6, Valladolid, Spain, 3-4 June, 1999 
5.2. Data processing 
The DEMs have been processed with commercial software 
packages. The SPOT DEMs are part of the DEM of the full 
scene, which has been generated by the Leica Helava DPW 770 
digital photogrammetric workstation, which uses cross 
correlation for point matching. The correlation coefficient of 
each DEM is not output directly, but is hidden behind a figure 
of merit (FOM). This FOM is scaled in a range from 0 to 100 
and is directly proportional to the correlation coefficient (Leica 
Helava, 1997). Height values below a FOM threshold of 33 are 
generally considered unreliable. Although the images were 
taken in a four-day interval, the SPOT data had to be enhanced 
by filtering. Further details of the SPOT pre-processing and the 
accuracy of the full scene DEM are given in (Patias, 1998). 
The InSAR DEM has been generated with the PCI IFSAR 
package. IFSAR offers both the LS and tree algorithms for 
phase unwrapping, but as the tree algorithm failed for test site 2 
and delivered the same RMS in site 1, LS has been applied to 
both regions, to keep the results comparable. Due to lack of 
ground control points (GCPs) in both areas, 5 GCPs had to be 
derived from the reference DEM for geocoding and baseline 
fitting. Baseline fitting has been performed by a technique 
proposed by Werner (1992). The amount of GCPs reduced 
remarkably the systematic error in the InSAR DEMs in 
comparison to earlier results with less GCPs (Honikel, 1998). 
6. RESULTS 
The SPOT and ERS DEMs have been compared to ground truth 
by bilinear interpolation of each height value in the reference 
DEM. All referred errors are absolute errors, unless something 
different is stated. Detailed investigations of the influence of the 
crop height on the measurements have not been carried out. 
Still, the fact that the signed average is larger in site 2 and 
negative indicates a bias between the tree canopies, measured in 
the DEMs, and the reference data derived from contour lines 
(see 5.1). 
The InSAR and stereo DEMs are very typical in both test sites. 
While InSAR performs well in test site 1, where it reaches a 
very good RMS error of 4.8m, while the RMS error drops in the 
presence of steeper slopes of test site 2 to 14.9m (Tab. 2). This 
behaviour proves the strong InSAR dependence on the 
coherence in general and especially on terrain slopes, as 
coherence in test site 2 is lower than in test site 1. In contrast to 
SPOT DEMs, where outliers of more than 90m occur in both 
sites, such extreme errors do not occur in the InSAR DEMs, 
where maximum errors of 24m and 63m arise. The reasons for 
this performance are the smooth terrain solution of LS 
unwrapping and the height interpolation during the ground 
range conversion process. Although outliers are avoided in 
InSAR DEMs, the amount of errors greater than 20m is 
significantly higher in test site 2, where InSAR performs worse, 
than in the SPOT case of test site 1. This is due to the fact, that 
LS unwrapping is capable to bridge only limited areas, but fails 
to recover large decorrelated areas. 
The SPOT stereo DEM performs robustly in both test sites. The 
RMS in both types of terrain differs only by 1.4m. Also, the 
correlation coefficient of test site 1 is with 0.7 a little higher 
than that of site 2 (0.66), proving that accuracy follows the 
correlation value also in the optical case. The robust 
performance is also underlined by the amount of height 
deviations greater than 20m. In test site 1, only 1.9% of all 
values showed such an error, in test site 2, 4.3%. In both cases 
almost all height errors (more than 99%) are below 40m. As a 
conclusion, stereo DEM errors are in part extremely high, but 
appear very localised and affect only their direct neighbours 
(Fig. 4). As expected, the correlation coefficient shows the same 
behaviour (Fig. 3). 
Due to the relatively short repeat pass interval of both sensors 
and the applied pre-processing, the mean correlation coefficient 
is relatively high with values between 0.54 and 0.7 for both 
sites and sensors. The cross-correlation shows distinct patterns 
for both sensors. While it follows closely the shape of the 
terrain in the SAR case, decreasing at the flanks of the hills and 
thus varying regionally, it shows extreme local variations in the 
optical case, where the correlation is corrupted at various spots. 
As the low correlation values appear in different locations in 
both InSAR and stereo-optical DEMs, the DEMs can be used 
complementarily by the proposed fusion process, which is 
demonstrated in the results of the fused DEMs. 
DEM 
Test site 1 
Test site 2 
InSAR 
(ERS-1) 
Signed average: 1.0m 
Average: 3.7m 
RMS: 4.7m 
Correlation: 0.61 
Signed average: -2.9m 
Average: 11.3m 
RMS: 14.9 
Correlation: 0.54 
Stereo-optical 
(SPOT) 
Signed average: 1.9m 
Average: 6.0m 
RMS: 7.9m 
Correlation: 0.7 
Signed average: -2.3m 
Average: 6.8m 
RMS: 9.3 
Correlation: 0.66 
Fused 
Signed average: 1,4m 
Average: 3.2m 
RMS: 4.0m 
Signed average: -2.2m 
Average: 4.9m 
RMS: 6.5m 
Table 2. Single sensor and fused DEM errors (reference 
DEM - generated DEM). 
The RMS decreased after the data fusion in both test sites. In 
test site 1, the RMS dropped to 4.0m after the fusion, a decrease 
of 16% compared to the ERS and of 49% compared to the 
SPOT DEM. In test site 2, the RMS dropped to 6.5m, a 
decrease of 30% compared to the SPOT case and 56 % to the 
ERS case (Tab. 2). 
The fact that no error greater than 20m occurs in test site 1 
proves the error sensitivity of the fusion procedure (Tab. 3). The 
partially extreme outliers of the SPOT DEM are completely 
rejected (Fig. 5) and only less erroneous values are fused with 
the very accurate InSAR DEM of test site 1.