Robert J Novak
University of South Florida
Department Of Public Health, Global Infectious Disease Research Program , College of Public Health,
Tampa, Florida
United States
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, Mounkaila Noma, Laurent Yameogo and Thomas Unnasch
Benjamin Jacob, Robert J Novak, Laurent Toe, Moussa S Sanfo, Semiha Caliskhan, Alain Pare, Mounkaila Noma, Laurent Yameogo 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