The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B4. Beijing 2008 
472 
Figure 4 and Figure 5 depicts the time spent for distributed 
orthorectification using several numbers of nodes. 
Distributed Orthorectification in LOA 
Number of node{s) 
bob Stand-alone in LPS 
rza Distributed Computing 
Trend 
у = 0 4278x-° ““ 
R : = 0 9978 
Figure 4. Orthorectification time in hours and minutes for 240 
images 
Distributed Orthorectification in LOA 
Number of node(s) 
a Distributed Computing 
Trend 
y = 36 019x' 3 9525 
R 2 = 0.9976 
Figure 5: Orthorectification time in hours and minutes for 858 
images. 
For Block 240, orthorectification in stand-alone mode using 
LPS was performed on one of the ortho nodes and took 10 
hours 20 minutes. The source data is located on the file server 
and for stand-alone mode the ortho images created were written 
to the local hard drive. Orthorectification in the distributed 
computing environment using 1 node took 10 hours 09 minutes. 
Using 5 nodes accelerated the orthorectification time by factor 
4.2 to 2 hours 27 minutes. 
For Block 858, orthorectification using 1 node took 1 day 12 
hours 37 minutes. Using 5 nodes decreased the processing 
time by a factor of 4.6 to 7 hours 59 minutes. 
5. RESULTS SUMMARY 
This experiment showed that distributed processing can be very 
beneficial when working with large orthorectification projects. 
As could be seen in Figure 4 and Figure 5, processing time 
decreases significantly with the number of nodes used. It is 
clear that distributed processing will be more efficient with 
larger ortho projects. 
Orthorectification is accelerated by a factor of 4.2 to 4.6 times 
using a 5 node cluster environment. 
When file caching is turned off for the 5 node run, it slowed 
down the process by only 3%. File caching might be necessary 
in order to prevent file writing errors. 
The system setup used for this experiment is sufficient. 
However it is not the ideal setup because the experiment was 
not done in a dedicated network. The ideal setup would be all 
ortho nodes; server and client machines and the data storage are 
in a dedicated network. This will prevent the network traffic 
that has been examined during this experiment. Also, the results 
would be faster and more reliable. However bottle-necks can 
always happen even in a dedicated network. 
As a future studies, this experiment will be repeated using a 
dedicated network. 
REFERENCES 
Graham, L. 2006. Enterprise Geospatial Production Revisited, 
Photogrammetric engineering and remote sensing, vol. 72, n°5, 
pp. 486-492 
ERDAS Ortho Accelerator, 
http://www.erdas.com/products/Product_Rdr.aspx7CURRENTI 
D=114 
GeoCue Corporation, http://www.geocue.com/