The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part BI. Beijing 2008 
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scale topographic map in Zone 17 of the Transverse Mercator 
(or Gauss-Kriiger) projection system. It includes the Qilian 
Mountains, located at the margin of the Qinghai-Tibet Plateau. 
It is more than half of the total study area from the northwest to 
southeast side. The southwest comer belongs to the eastern 
Qadam Basin; the northeast part extends in the Hexi Corridor 
area and the Badamjaram Desert; the southeast comer is the 
Longyangxia Reservoir, in the upper part of the Yellow River 
drainage basin. The study area is well suited for the evaluation 
of the SRTM data as the major types of land cover that affect 
radar imaging are within its limits, including lakes and 
reservoirs, glaciers and permanent snow, dense conifer forests 
and sandy deserts. 
2.2. Data and Preparation 
Standard DEM data are from a set of 16 digital topographic 
maps at a scale of 1:250,000 in the national geographic data 
base. Horizontal and vertical data are the Krasovsky spheroid, 
Beijing 1954 system, and Huanghai Altitude System, 
respectively. The SRTM data are from the Data & Maps 2006 
data set in ESRI’s ArcGIS 9.2 package and the NASA website 
(ftp://e0srp01u.ecs.nasa.gov/srtm/). respectively. They are 
afterward named as ESRI SRTM and NASA SRTM3, 
respectively. Their vertical and horizontal data are EGM 96 and 
WGS 84, respectively. Voids in ESRI SRTM data were filled 
using the Delta Surface Fill (DSF) algorithm (Grohman, et al., 
2006; ESRI Inc., 2007). The results are continuous and 
seamless, but they are stored in a lossy JPEG 2000 format. The 
void raster units in the NASA SRTM data create gaps in the 
study area. In order to complete this study, additional 
vectorized data for land cover with glaciers and permanent 
snow, mountain conifer forests, and sandy deserts were 
extracted according to the interpretation to Landsat TM images. 
2.3. Preprocessing to DEM data 
All DEM data, including ESRI SRTM and NASA SRTM3, and 
the DEM from topographic maps were transformed from 
geographic coordinate system into a Gauss-Kriiger coordinate 
system. A cubic convolution method is used for the re-sampling 
process with the resulting grid size of 90x90 m. Then, the data 
were cut to create the largest rectangle possible within this 
fan-shaped dataset. The remaining data consist of a 5645x4852 
grids corresponding to a region measuring 437x508 km. 
Altitudes within this study area range from 1148-5801 m above 
sea level according to the DEM from topographic maps. 
Similar results were obtained from the NASA SRTM3 
(1112-5767m) and the ESRI SRTM (1113-5762m). The slope 
and aspect of terrain were calculated according to the function 
in ArcGIS 9.2. Statistically, the 13263 raster units with void 
data in these two data sets encompass about 2005km 2 or 
0.904% of the study area. 
3. EVALUATION ON LOCATION PRECISION 
3.1. Extraction of mountain ridges and valleys 
The extraction of ridge and valley data from the ESRI SRTM 
and the topographic map DEM was conducted using Tang’s 
algorithm based ArcGIS's Spatial Analyst (Tang, G, et al., 
2006). During this processing, there was little modification to 
the original algorithm. The former threshold for slopes was 70 
degrees. While this might be suitable for a topographic map 
DEM at the scale of 1:50000, better results were obtained using 
a 20 degree threshold with a map scale of 1:250000. As a result, 
redundant raster units were created to represent ridges and 
valleys and, while there were two or three raster strings in some 
areas, the resulting ridges and valleys were continuous and 
have integrity. The same process was also used for the SRTM 
data. 
3.2. Coincidence analysis 
A visual inspection was conducted of the ridge and valley raster 
data created from the topographic map DEM and ESRI SRTM 
data. The analysis showed a high degree of coincidence 
between them (Figure. 2). It is clear that most coincident ridge 
and valley raster units are surrounded by those that are 
not-coincident. Statistics for all ridge and valley raster units are 
shown in Table 1. These were calculated according to the 
number of coincident raster units divided by the total number 
of ridge or valley raster units, respectively. It is clear that the 
coincidence of both ridge units and valley units reaches about 
30% of the total ridge and valley units in the DEM from 
1:250000 scale topographic map and the ESRI SRTM. The 
result is good as considering that the ridge and valley data are 
redundant. 
Figure 2. Location precision of mountain ridges and valleys 
from ESRI SRTM and the DEM from topographic maps. 
Topographic condition 
Ridge 
Valley 
Topographic map DEM 
2972336 
3574962 
ESRI SRTM 
3406633 
3848405 
Coincidence 
Raster units 
943592 
1063413 
Percentage in map 
DEM 
31.7 
29.7 
Percentage in ESRI 
SRTM 
27.7 
27.6 
Table 1. Coincidence analysis of ridges and valleys from the 
topographic map and SRTM DEMs 
4. EVALUATION ON ALTITUDE PRECISION 
4.1. Result from subtraction operation 
The raster data set representing the SRTM error can be 
obtained by subtracting the ESRI SRTM data from the map