Journal of Animal Ecology 1996, 65,371-380 © 1996 British Ecological Society Spatial analysis of the distribution of tsetse flies in the Lambwe Valley ,Kenya, using Landsat TM satellite imagery and GIS U. KITRON, L.H. OTIENO*, L.L. HUNGERFORD, A. ODULAJAt, W.U. BRIGHAMt, 0.0. OKELLOt, M. JOSELYNt, M.M. MOHAMED-AHMED* and E. COOKt Department of Veterinary Pathobiology, College of Veterinary Medicine. University of Illinois. Urbana. IL 61801. USA Summary 1. Satellite imagery, geographic information systems (GIS) and spatial statistics pro- vide tools for studies of population dynamics of disease vectors in association with habitat features on multiple spatial scales. 2. Tsetse flies were collected during 1988-90 in biconical traps located along transects in Ruma National Park in the Lambwe Valley, western Kenya. Fine spatial resolution data collected by Landsat Thematic Mapper (TM) satellite and reference ground environmental data were integrated in a GIS to identify factors associated with local variations of fly density. 3. Statistical methods of spatial autocorrelation and spatial filtering were applied to determine spatial components of these associations. Strong positive spatial associ- ations among traps occurred within transects and within the two ends of the park. 4. From satellite data, TM band 7, which is associated with moisture content of soil and vegetation, emerged as being consistently highly correlated with fly density. Using several spectral bands in a multiple regression, as much as 87% of the variance in fly catch values could be explained. 5. When spatial filtering was applied, a large component of the association between fly density and spectral data was shown to be the result of other determinants underlying the spatial distributions of both fly density and spectral values. Further field studies are needed to identify these determinants. 6. The incorporation of remotely sensed data imagery into a GIS with ground data on fly density and environnmental conditions can be used to predict favourable fly habitats in inaccessible sites, and to determine number and location ofHy suppression traps in a local control programme. Key-words: geographic information system, remote sensing, spatial statistics. Journal of Animal Ecology (1996) 65,371-380 development in large parts of subsaharan Africa (Ford Introduction 1971; Rogers & Randolph 1986). Due in part to Tsetse flies are the vectors of animal and human try- characteristics of the trypanosome parasites. control panosomiasis, among the most serious diseases of of these diseases is likely to depend largely on the cattle and people in Africa, and inhibit agricultural management of tsetse populations. Fnml an epi- demiological point of view, successful fly management will reduce the number and, or int<xli,'n ·Present address: Livestock Pests Research Programme, rate of flies below a transmission threshold. ICIPE, Nairobi, Kenya. Several species of tsetse and trypanosomes are tPresent address: Biomathematics Research Unit, ICIPE, responsible for disease transmission. Even for the Nairobi, Kenya. t Present address: Illinois Natural History Survey, Cham- same species of vector and parasite, spatial het- paign, IL 61820, USA. erogeneity in environmental conditions results in local 371