The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part Bl. Beijing 2008 
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DEM data. The error statistics are shown in Table 2. 
Data Source 
Min 
Max 
Mean 
Dev 
ESRI SRTM 
-710 
711 
-6.625 
29.888 
NASA SRTM3 
-420 
463 
-6.635 
29.163 
Comparing the ESRI SRTM with topographic map DEM, 25% 
of raster units have an absolute elevation error of less than 5m; 
50%, <15m; 75%, <32m; 90%, <49m; 95%, <62m; 99%, 92m; 
and 99.9%, <143m. This level of error is greater than that 
obtained by Rodriguez, et al. (2005) at the same area. 
4.2. NASA SRTM3 
Table 2. Comparative error statistics of the ESRI SRTM and 
NASA SRTM3 with topographic map DEMs. 
A histogram of the elevation error is presented in Figure 3. It 
shows a normal distribution around -6.625, very close to zero. 
A very narrow peak appears to the right of mean peak 
representing the flat surface of Qinghai Lake. 
Fig. 3. Error histogram comparing the ESRI SRTM and 
topographic map DEMs. 
Min 
Max 
Mean 
Dev 
-393 
469 
-6.640 
29.414 
Table 3. Comparative errors between the ESRI SRTM without 
void filling and the topographic map DEM. 
Grouping statistics provide insights on the absolute error of the 
data as shown in Figure 4. It is clear that raster units with an 
identical elevation represent only 2.42% of the total, while 
about 36% have an absolute error between l-10m and more 
than 85% within 20m. Therefore, most of the raster units are 
distributed near an absolute error of zero meter as shown in 
Figure 3. 
An operation similar to that in Section 4.1 was used for the 
NASA SRTM3 data. The resulting elevation error statistics 
were similar to that from ESRI SRTM (Table 2) with greater 
minimum and smaller maximum elevation error. 
4.3. The effect of void filling on ESRI SRTM 
The void boundary data from ESRI SRTM dataset were used to 
delete the elevation measurement of the void unit and to assign 
it a value of no data (NODATA), i.e. -32767 in these data. 
Statistics for these new data are shown in Table 3, which are 
similar to that for the NASA SRTM3. Thus, the void filling 
operation does not significantly change the structure of the 
elevation error of the resulting combined DEM. These results 
are closer to that for NASA SRTM3 with void. It can be found 
that the higher elevation errors in ESRI SRTM data exist in the 
void area. It can be concluded that although the DSF algorithm 
(ESRI Inc., 2006) guarantees the spatial continuity of SRTM 
data, it leads to the deterioration of the data quality. 
4.4. The effect of landform on ESRI SRTM 
From the subtraction process of both the ESRI SRTM and 
topographic map DEM described above, it can be seen that 
topographic relief have clear effects on the quality of the SRTM 
data. In basins or wide valleys with low relief, such as the 
Qadam Basin and the Hexi Corridor, there is a high precision in 
the elevation measurements with a typical absolute elevation 
error of less than 5m. In alpine ridges and plateaus, there is a 
greater elevation error and no clear trend in these variations. 
The two largest water bodies in the region, Qinghai Lake and 
Har Lake, have elevation errors of 44m and -24m, respectively. 
Other smaller water bodies, such as Tuosu Lake and Kurlek 
Lake in the Qadam Basin, Longyangxia Reservoir in the upper 
Yellow River, and the Yuanyangchi and Jiefangcun Reservoirs 
in the Hexi Corridor, have elevation errors of -56m, -27m, 
-31m, -54m and -7m, respectively. The magnitude of the error 
is different even for two neighboring reservoirs, only 3km apart 
in the Hexi Corridor area. In addition, there are about 100m of 
negative elevation errors in sand dune units at the northeast 
side of Qinghai Lake. The similar result were obtained for the 
NASA SRTM3 data. 
Figure 4. Histogram of absolute elevation differences between 
the ESRI SRTM and topographic map DEMs. 
4.5. The effect of slope and aspect of terrain 
A scattergram was drawn for both the elevation error of ESRI 
SRTM with topographic map DEM and slope of terrain. As 
shown in Figure 5, the horizontal axis is the elevation error 
(-710-711 m), the vertical axis is the slope ( 0-64.7 degree). It 
is clear that the dots arrange symmetrically around the mean 
elevation error (-6.625m), and have no slope specific. 
The elevation errors of ESRI SRTM with DEM from 
topographic map were group into eight directions as described 
in Spatial Analyst, ArcGIS, plus flat units. The statistics to the 
errors were shown in Table 4. All the distributions of the errors 
are Gaussian form. But the errors at northern slope are greater 
than that at southern slope. In addition, the northern slope has 
higher minus mean error compared with the southern one.