An investigation of the utility of remote sensing imagery for predicting the distribution and abundance of the tsetse fly (Diptera: Glossinidae)

This thesis investigates the potential contribution of data from the Advance Very High Resolution Radiometer (A VHRR) on-board the National Oceanic and Atmospheric Administrations (NOAA) polar-orbiting meteorological satellites and data from the High Resolution Radiometer (HRR) on-board the Meteosat geostationary meteorological satellites for predicting the distribution and abundance of the tsetse fly (Diptera: Glossinidae) in Africa. The images were processed to produce a range of monthly land surface temperature, atmospheric moisture and rainfall indices for the period 1988 to 1990. The performance of these indices, derived from several different methods, was tested using meteorological records collected during these years at stations across continental Africa and the most accurate used to form a refined dataset for subsequent analysis. The time-series of these land surface temperature, atmospheric moisture and rainfall indices and a range of Spectral Vegetation Indices (SVI) were subject to temporal Fourier analysis to parameterise the seasonal variation in these variables. These data, in combination with elevation information from a digital elevation model (DEM) were used to predict the land-cover of Nigeria determined independently by an aerial survey in 1990. The Normalised Difference Vegetation Index (NDVI) performed best and so was used in combination with the satellite proxy meteorological and D EM data to predict the distribution and abundance of eight tsetse fly species in Cote d'Ivoire and Burkina Faso, West Africa. The results are discussed in relation to the ecology of the different tsetse species. Conclusions are then drawn on the potential of such meteorological satellite data for remote tsetse fly population surveillance and, in the wider context, to the study and control of arthropod vectors of disease.