This study aims to provide trypanosomiasis-affected countries with standardized datasets and methodologies for mapping the habitat of the tsetse fly ( Glossina spp., the disease vector) by customizing and integrating state-of-the-art land cover maps on different spatial scales. Using a combination of inductive and deductive approaches, land cover and fly distribution maps are analysed in a geographic information system (GIS) to estimate the suitability of different land cover units for the three groups (subgenera) of Glossina. All land cover datasets used for and produced by the study comply with the Land Cover Classification System (LCCS). At the continental scale, a strong correlation between land cover and tsetse habitat is found for both the fusca and palpalis groups, whereas a weaker correlation found for the morsitans group may be indicative of less restrictive ecological requirements. At the regional and national levels, thematic aggregation of the multi-purpose Africover datasets yielded high-resolution, standardized land cover maps tailored for tsetse habitat for eight East African countries. The national maps provide remarkable spatial resolution, thematic detail and geographical coverage. They may be applied in subsequent phases of tsetse and trypanosomiasis control projects, including the planning of entomological surveys, actual tsetse control operations and planning for land use in reclaimed areas. The methodology and datasets discussed in the paper may have applications beyond the tsetse and trypanosomiasis issue and may be used with reference to other arthropod vectors, vector-borne and parasitic diseases. This study aims to provide trypanosomiasis-affected countries with standardized datasets and methodologies for mapping the habitat of the tsetse fly ( Glossina spp., the disease vector) by customizing and integrating state-of-the-art land cover maps on different spatial scales. Using a combination of inductive and deductive approaches, land cover a