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Clutter and Land Use  

 

 

Clutter data is classified as the man-made and natural features that may impair radio frequency propagation by reflection, diffraction, absorption, or scattering of the transmission waves. Our Clutter data production is derived from the latest satellite imagery, not from paper maps. Our remote sensing specialists employ extensive ancillary ground truth data to ensure the highest reliability of our clutter classifications.

 
 
 
 
 
 
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STL's Clutter Data has been developed for the Radio Frequency (RF) Propagation environment to help engineers refine their signal loss prediction models according to the characteristics of the underlying terrain and ground cover. STL uses recent high resolution satellite imageries that is the best source source available in the market. For rural areas, STL employs supervised classification techniques. For all rural areas, STL employs manual photo interpretation. This is the only reliable method consistently distinguishing urban zones according to their morphology and building density.

In today's competitive market, the wireless telecommunication industry has been driven by the need to provide better service coverage while reducing infrastructure costs. The solution lies in determining the optimum location of mast.
The resolution of our clutter data is contingent on the request of our clients and this in turn depends on the resolution of the source imagery.
Resolution refers to the cell size or inter-cell spacing in raster grids or the pixel size or inter-pixel spacing of an image as in a satellite image. However, with the launch of Nigeria's NigeriaSAT1 remote sensing satellite, we now have access to 32m resolution  source imageries that can be purchased right here in Nigeria with our own local currency “NAIRA”
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  See our huge database containing the location of all sites/mast of GSM operators in Nigeria
  20m resolution data for Gboko in Benue State.  This is just one of the over 100 cities STL had developed for the wireless industry in Nigeria. In addition we have 50m resolution clutter for the entire country                                                   
 

All 14 classes of our clutter data are carefully defined to meet RF engineering requirements in wireless planning. Urban variety classes are sampled in relation to the average street width and building type, te, thereby greatly increasing the accuracy of propagation model

 

 

 

 

 

 

 

 

 
     

Data Format:

  • Aircom ASSET
  • Planet
  • ASCII Binary

Availability:

STL has 20m resolution clutter data for over 100 cities in Nigeria See Map Catalogue

 

Benefits of Clutter Data to Wireless Companies:

  • Enhance service coverage and reduce dropped calls

  • Predict the performance of wireless services in transmission areas

  • Plan the build or redesign of their network

  • Optimize transmission site locations and reduce infrastructure costs

 

 

 

 

 

 

       
         
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