1126 
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part Bl. Beijing 2008 
Figure 5. Scattergram for both the elevation error of ESRI 
SRTM with topographic map and slope 
Aspect 
Min 
Max 
Mean 
Std Dev. 
-1 (flat unit) 
-255 
196 
-4.69 
31.09 
0-45 deg. 
-710 
646 
-13.39 
25.77 
45-90 deg. 
-704 
496 
-11.00 
27.92 
90-135 deg. 
-540 
688 
-2.94 
32.13 
135-180 deg 
-515 
711 
2.92 
31.56 
180-225 deg 
-525 
668 
2.26 
27.99 
225-270 deg 
-546 
674 
-1.40 
28.70 
270-315 deg 
-639 
630 
-12.31 
30.11 
315-360 deg 
-699 
634 
-15.50 
28.88 
Tables 4. Statstics of the elevation error of ESRI SRTM with 
DEM from topographic map on different aspect of terrain 
A histogram analysis of the elevation errors was made to those 
land covers. It can be seen that the distributions of elevation 
errors in mountain glaciers, in mountain conifer forests, and in 
sandy desert areas are represented as Gaussian normal 
distribution form with all peaks between -20m and 0m. The 
raster units with more than 200m of elevation error in glacial 
areas, or more than 100m in conifer forests and sandy deserts, 
happen in lower frequencies. 
£teu**an mm act«* ire») 
4.6. The effect of land cover 
Land cover is an important factor affecting the calculation of 
elevation when using Interferometer Synthetic Aperture Radar 
(InSAR). Forested areas with dense vegetation obstruct the 
penetration and backscattering of the radar irradiance and the 
resulting higher estimation of elevation than its true value. 
Conversely, the penetration ability of the radar signal in snow 
and dry sandy ground often results in a lower estimation of the 
true elevation. To correct these effects, evaluations were made 
to estimate their magnitude in different settings that included a 
mountain glacier, a mountain conifer forest and a sandy setting 
in the Badamjaram Desert. The elevation error data in these 
areas were extracted according to their land cover using the 
data described in Section 4.1. These statistics are shown in 
Table 5. It can be seen that there are both positive and negative 
elevation errors for all land cover types. The mean elevation 
errors are all small negative values. 
140006 
I2»X#X> 
c Swidy dtfsen 
100006 
80006 
60000 
D 
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j* Ë Z Ü Ü 
iff??« 
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Figure 7. Statistical distributions of elevation errors for several 
land covers. 
Types of land cover 
Min 
Max 
Mean 
Dev 
Glaciers 
-620 
241 
-25.75 
53.30 
Mountain conifer 
-229 
226 
-16.60 
40.02 
forest 
Sandy desert 
-183 
134 
-7.00 
30.38 
Table 5. Statistics on the ESRI SRTM errors (m) for some 
typical land covers. 
5. CONCLUSION 
In conclusion, the 3 arc sec SRTM data are high quality and can 
be used to replace the DEM from 1:250000 scale topographic 
maps in many situations, e.g. for the study of mountain 
geomorphology, ecology, and hydrology. The DSF algorithm 
for void filling used by ESRI does not improve the total data 
quality or error structure. Compared with the actual DEM 
determined after ground surveys, the absolute elevation error is 
less than 5m in relatively flat basins and wide valleys on the 
plateau, while it is larger in mountainous areas. There are both 
positive and negative elevation errors associated with lakes and