Land-cover studies based on optical remote sensing in regions which exhibit disorderly urban growth and quick-use conversion of farmland to non-farm usage face problems due to inaccurate discrimination of cover types and hence inaccurate extent estimations. The use of data in the visible and infrared areas of the electromagnetic spectrum for classifying crop types has been extensively explored, concluding that data acquisitions must be made during critical crop development periods. This raises a concern in Central Mexico where such periods coincide with important cloud coverage and where good estimates of the extent of agricultural areas and of particular crops are keenly sought by government agencies for planning purposes. Due to the interest in accurate and updated maps for this area, repeated studies have been carried out over a number of years by the National Institute of Research for Forestry, Agriculture and Livestock for the Ministry of Agriculture of Mexico. Taking into consideration the difficulties of acquiring and analysing data derived from optical sensors, the objective of this study was to assess the advantages of combining synthetic aperture radar (SAR) and optical remote sensing in producing more accurate maps. The study area covers 15 634 ha and is located in Central Mexico in a region where agricultural plots of varied sizes and forms are interspersed with rapid urbanization spaces. We investigated alternative supervised classification schemes combining the Radarsat-1 C-band with Landsat Enhanced Thematic Mapper Plus (ETM+) bands to estimate land cover distributions and assess the quality of results with field data. Then, we set forth and evaluated a methodology which applies data fusion of selected Landsat ETM+ bands and the C-radar band. The separation and similarities for vegetated and non-vegetated cover types depends on whether the selected agricultural crops are annual or perennial, and on whether there are bare soils present. This knowledge for the particular study area influenced the selection of dates for image take and analysis. Partial fused and non-fused land-cover maps were assessed for accuracy and were combined to obtain a final map. The results demonstrate that the combined utilization of optical and radar imagery yields useful land cover information and improved classification accuracy over those obtained using either type of image on its own.