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

摘要

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.