Full text: Proceedings; XXI International Congress for Photogrammetry and Remote Sensing (Part B1-1)

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part Bl. Beijing 2008 
360 
Fig.2 Distribution of GCPs and Pass Points 
Image 
X 
Mean Square Error(m) 
Y Z horizontal 
1321-01 
2.9 
3.4 
1.9 
4.5 
1309-40 
2.9 
3.4 
1.9 
4.5 
1321-08 
2.2 
2.4 
2.8 
3.3 
1309-33 
2.2 
2.4 
2.8 
3.3 
Averag 
e 
2.6 
2.9 
2.4 
3.9 
Table 1. Combined Adjustment Accuracy 
Image 
X 
Mean Square Error(m) 
Y Z horizontal 
0701-71 
1.9 
2.1 
0.9 
2.8 
0831-06 
1.8 
2.5 
0.8 
3.1 
0629-06 
0.7 
1.3 
1.9 
1.5 
0701-76 
1.1 
1.6 
2.3 
1.9 
0701-82 
1.4 
1.6 
2.9 
2.1 
0701-87 
1.0 
0.8 
3.8 
1.3 
0831-11 
1.1 
1.2 
3.0 
1.6 
0831-16 
1.6 
1.2 
2.4 
2.0 
0831-22 
1.5 
0.7 
3.9 
1.7 
0629-12 
1.3 
1.4 
1.7 
1.9 
0629-18 
1.2 
1.3 
2.1 
1.8 
Averag 
e 
1.3 
1.4 
2.3 
2.0 
Table 2. Combined Adjustment Accuracy 
In the two experiments, the GCPs and the Pass Points are 
distributed rationally in each image. The two experimental 
results show that the coordinate accuracy of Pass Points is 
feasible for 1:10 000 scale ortho-image making and topographic 
map updating. There are four images in the first experiment, 
and nine GCPs and ten Pass Points are used. There are eleven 
images in the second experiment, and nine GCPs and thirty Pass 
Points are used. The second experimental result is better than 
the first one. Because the Pass Points are twice overlap in the 
first experiment and the most Pass Points are more than twice 
overlap in the second one. 
4. CONCLUSIONS 
The experimental results show as follows: 
Firstly, this method can satisfy accuracy requirement of 1:10, 
000 scale image ortho-rectification and map updating. 
Secondly, compared with conventional ortho-rectification of 
single image, the number of GCPs has decreased greatly based 
on this method. 
Thirdly, when computing ground coordinates of pass points, the 
elevation value is obtained from 1:50,000 scale DEM. The 
experimental results show that the accuracy of pass point is 
improved enormously used this method. 
Fourthly, this method can apply to multi-photo combined 
adjustment of any airborne SAR image, such as different 
temporal, different side-looking-orientation, different flight 
height, different resolution. 
According to functions above, this method can also apply in 
multi-photo spacebome SAR images and spacebome SAR 
images with airborne ones, but time and data is limited, this 
method will be researched with more kinds of data later. 
REFERENCES 
Huang G.M., Yue X.J., Zhao Z. et al, 2008. Block Adjustment 
with Airborne SAR Images Based on Polynomial Ortho- 
rectification. Geomatics and Information Science of Wuhan 
University, in press. 
Zhu C.Y. Xu Q. Wu C.H. et al, 2003. Study on Mathematical 
Models for Airborne SAR Image Rectification. Journal of 
Remote Sensing, Vol.7(2), pp. 112-117. 
Franz Leberl, 1978. Radar Grammetry For Image Interpretation. 
ITC Technical Report. 
G. Domik, Franz Leberl, 1988. Radar Image Simulation and Its 
Application in Image Analysis, 16th ISPRS Congr, Comm. 3. 
Shu N., 2003. Principles of Microwave Remote Sensing[M]. 
Chinese Earth quakePress, pp. 129. 
Wang D.H., Liu J., Zhang L., 2005. Precise Rectification of 
Spacebome SAR Images Based on Improved F.Leberl Model. 
Bulletin of Surveying and Mapping, Vol(10), pp. 12-15. 
Xiao G.C. Zhu C.Y., 2001. Radar Photogrammetry[M], Chinese 
Earth quakePress, pp. 54-56. 
Fan H.D., 2007. Study on Methods of DEM Generation from 
Airborne Stereo SAR Images[D], China University of Mining 
and Technology. 
ACKNOWLEDGEMENT 
This work was supported by State Bureau of Surveying and 
Mapping Key Laboratory of Geographic Information 
Engineering Foundation of Researches, No 200731.
	        
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