Predicting the distribution of tsetse flies in West Africa using temporal Fourier processed meteorological satellite data.

An example is given of the application of remotely-sensed, satellite data to the problems of predicting the distribution and abundance of tsetse flies in West Africa. The distributions of eight species of tsetse, Glossina morsitans, G. longipalpis, G. palpalis, G. tachinoides, G. pallicera, G. fusca, G. nigrofusca and G. medicorum in Côte d'Ivoire and Burkina Faso, were analysed using discriminant analysis applied to temporal Fourier-processed surrogates for vegetation, temperature and rainfall derived from meteorological satellites. The vegetation and temperature surrogates were the normalized difference vegetation index and channel-4-brightness temperature, respectively, from the advanced, very-high-resolution radiometers on board the National Oceanic and Atmospheric Administration's polar-orbiting, meteorological satellites. For rainfall the surrogate was the Cold-Cloud-Duration (CCD) index derived from the geostationary, Meteosat satellite series. The presence or absence of tsetse was predicted with accuracies ranging from 67%-100% (mean = 82.3%). A further data-set, for the abundance of five tsetse species across the northern part of Côte d'Ivoire (an area of about 140,000 km2), was analysed in the same way, and fly-abundance categories predicted with accuracies of 30%-100% (mean = 73.0%). The thermal data appeared to be the most useful of the predictor variables, followed by vegetation and rainfall indices. Refinements of the analytical technique and the problems of extending the predictions through space and time are discussed.