Remote sensing for epidemiologists: what can satellite data contribute

The distribution of the African trypanosomiases, and their adverse impact on agricultural production systems, make this disease one of the most important constraints to livestock rearing in much of sub-Saharan Africa. Tsetse flies are vectors for both human (sleeping sickness) and animal trypanosomiases (nagana). An import step in understanding their ecology for the purposes of intervention is to determine the environmental causes of the spatial and temporal variation in tsetse fly (Glossinidae) numbers. For many years, high-resolution satellite-sensor data have found wide application in development projects, often providing the only maps available for remote sites. High cost, relatively small coverage per scene and low temporal resolution precludes use over wider geographical areas, as does the sheer volume of data involved. In this study a technique to increase the spatial resolution of the coarse multitemporal AVHRR data to a scale more appropriate for local scale tsetse and thus trypanosomiases control is demonstrated. The effectiveness of multi-sensor data fusion is demonstrated using Landsat TM and Fourier-processed AVHRR data. The latter provide seasonality layers aiding high-resolution image interpretation and classification. The methodology is based on a simple wavelet transform