The objectives of this study are to quantify, based on remote sensing data, processes of land-cover change and to test a Markov-based model to generate short-term land-cover change projections in a region characterised by exceptionally high rates of change. The region of Lusitu, in the Southern Province of Zambia, has been a land-cover change 'hot spot' since the resettlement of 6000 people in the Lusitu area and the succession of several droughts. Land-cover changes were analysed on the basis of a temporal series of three multispectral SPOT images in three steps: (i) land-cover change detection was performed by combining the postclassification and image differencing techniques; (ii) the change detection results were examined in terms of proportion of land-cover classes, change trajectories and spatio-temporal patterns of change; (iii) the process of land-cover change was modelled by a Markov chain to predict land-cover distributions in the near future. The remote sensing approach allowed: (i) to quantify land-cover changes in terms of percentage of area affected and rates of change; (ii) to qualify the nature of changes in terms of impact on natural vegetation; (iii) to map the spatial pattern of land-cover change. 44% of the area has been affected by at least one change in land cover during the period 1986 to 1997. The average annual rate of land-cover change was 4.0%. Agricultural expansion was the dominant change process. Land-cover change trajectories highlighted the dynamic character of changes. The results obtained by applying a Markov chain for projecting future evolutions showed the continuing upward trend of bare soils and cultivated land, and the rapid downward trend of forests and other natural vegetation covers.