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International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B7. Istanbul 2004 
Swath width 
With a broader swath width the capacity of the satellites is also 
increased. In fact a 4 satellites with a swath of 20km can cover 
the same area as 8 satellites with 10km swath. The effect of the 
swath is shown in figure-8. It can be seen that the effectiveness 
of a wide swath drops after a swath width wider than 15km. 
When the situation of 8 satellites with a 10km swath is 
compared to 
À constellation of 4 satellites with 20km swath results in 43% 
of monitoring capacity, while a constellation of 8 satellites with 
LOkm swath has a capacity of 4996. The higher value probably 
is an effect of the more detailed following of the pipeline 
trajectory and the more frequent observation opportunities. 
% of total monitoring days versus field of view 
  
  
  
  
  
  
  
  
  
7096 
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field of view 
Figure-8: The effect of different swath widths in % of total 
required monitoring capacity. 
Pointing range 
Finally different ranges for the pointing in along and across 
track direction are simulated. See figure-9. As expected the 
effectiveness of the system increases with larger pointing 
ranges. This as a consequence of the wider area in which 
pipeline trajectories can be selected and clouded regions 
avoided, and as a consequence of the longer observation time as 
a consequence of the larger forward/afterward pointing range. 
From an interpretation point of view a pointing range wider 
than 33 degrees is not realistic however. 
% of total monitoring days for all elements 
  
  
  
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90% 
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pointing range | 
  
Figure-9: The effect of the pointing range in 96 of total required 
monitoring capacity. 
6. OUTLOOK 
The simulation results provide good insight in the use of high 
resolution optical satellites for monitoring of the European gas 
pipeline network. Additional simulations will be carried out in 
order to obtain answers to several questions. In the first place 
simulations with constellations of larger number of satellites 
and some wider swathes. Theoretically in a non clouded 
situation the network should can be covered with 8 satellites. As 
the found effect of cloud cover is about 50% this means that 
simulations with constellations up to 15 satellites are required. 
Secondly attention will be paid to the combination of high 
resolution optical satellites with other collection assets like SAR 
satellites and airborne platforms with optical or SAR sensors, 
either manned 'platforms or UAV's (Hausemann, 2003). For 
this the less suited pipeline trajectories (non dense areas and 
east-west directed lines) can be filled in by this other platforms 
and left out of the scheduling. As a consequence the high 
resolution optical satellite effectiveness may increase. 
A third point of interest is to simulate situations for higher 
monitoring frequencies of 10 or 7 days. 
Finally attention will be paid to the satellite scheduling strategy. 
It is expected that by optimising the scheduling algorithms the 
results can be improved. 
7. CONCLUSIONS 
It can be concluded that for the two weekly monitoring of the 
extended European pipeline network with high resolution 
optical satellites a large constellation is required. The 
simulations learn that in case of optimal use of cloud 
information 29% of the monitoring work can be obtained with 4 
satellites and 49% with 8 satellites. 
A wider swath, better scheduling algorithms and proper co- 
ordination with other SAR and airborne collection assets can 
obtain further optimisation ofthe constellation. 
The use of proper cloud information is essential for the 
effectiveness of the optical satellite constellation. The 
simulations shows an increase of 104% 
The CLIMAS simulation tool is a powerful tool for simulation 
of the capabilities of an optical satellite constellation related to 
a specific application and with realistic cloud coverage 
conditions. 
8. REFERENCES AND AKNOWLEDGEMENTS 
8.1 References 
Algra, T.; Kamp, A van der; Persie, M. van. Results with 
CLIMAS, a simulation tool for cloud avoidance scheduling in 
optical remote sensing missions. SpaceOPS Conference 2004, 
Montreal, Canada, May 17-21, 2004 
Algra, T. Real-time cloud sensing for efficiency improvement 
of optical high-resolution satellite remote sensing. Proc. 
IGARSS'03, Toulouse, 2003 
Dekker, R.J.; Lingenfelder, I; Brozek, B.; Benz, U; Broek, A.C. 
van den. Object-based detection of hazards to the European gas 
pipeline network using SAR images. 2004 
Haar, T.H. von der; et al. Climatological and Historical 
Analysis of Clouds of Environmental Simulations (CHANCES) 
Database — Final report. PL-TR-95-2101, Philips Laboratory, 
Hanscom Air Force Base, Mass., (1995) 
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