Journal of Remote Sensing & GIS

Moussa S Sanfo

Publications

• Research Article
  Unbiasing a Stochastic Endmember Interpolator Using ENVI Object-BasedClassifiers, a Farquhar's Single Voxel Leaf Photosynthetic ResponseExplanatory Model and Boolean Time Series Statistics for ForecastingShade-Canopied Simulium damnosum s.l. Larval Habitats in Burkina Faso
  Author(s): Benjamin Jacob*, Robert J Novak, Laurent Toe, Moussa S Sanfo, Semiha Caliskhan, Alain Pare, Laurent Yameogo, Mounkaila Noma and Thomas UnnaschBenjamin Jacob*, Robert J Novak, Laurent Toe, Moussa S Sanfo, Semiha Caliskhan, Alain Pare, Laurent Yameogo, Mounkaila Noma and Thomas Unnasch
  
  Endmember spectra recovered from sub-meter resolution data [e.g., Quick Bird visible and near infra-red (NIR) 0.61m wavebands ratio] of an arthropod-related infectious disease aquatic larval habitat can act as a dependent variable within a least squares estimation algorithm. By so doing, seasonal endemic transmission -oriented risk variables can be accurately interpolated. Spectral mixing, however, is a problem inherent to multi-dimensional canopy-oriented arthropod-related infectious disease larval habitat feature attributes resulting in few image sub-pixel spectra representing "pure" targets. This can lead to a biased endmember target signature due to spectrally unquantitated mixed sub-pixel radiance originating from different canopy-oriented larval habitat object types. An erroneous endmember larval habitat signature will render inconsistent residual forecasts in a stocha.. View More»
  DOI: 10.4172/2169-0049.1000109

  Abstract PDF