The rural population of Zimbabwe has been growing rapidly since the country gained independence in April 1980. This increased pressure and degradation of the land; hence there was a need to sustain the growing population and its subsequent impacts on rural areas. This led to the implementation of the land reform programme in 2000, which intended to provide more land for settlement and crop production. Although this was successful to a certain extent, investigation is required to determine the changes in spatial and temporal variations in landcover for better management and allocation of natural resources to sustain the rural population and economic development. This study, therefore, used multispectral remote sensing Landsat images to determine landcover changes in one of the rural areas of Masvingo Province in Zimbabwe, using a maximum likelihood classifier. A post-classification change detection technique was also used to produce change through cross-tabulation. The findings of this study have demonstrated significant changes in landcover over the years (i.e. 1990–2010). For instance, it was observed that agricultural fields and human settlements increased dramatically during the period. Overall, the results of this study suggest that remotely sensed data provides an ideal platform for constant inventorying of natural resources.