Land cover maps, derived from satellite data, are a valuable tool for various global research studies and are often used in multi-temporal approaches to document the dynamics of processes such as agricultural expansion or deforestation. In this study we show how the observed land cover change tendencies diverge widely depending on the scale of observation and on the characteristics of the data sources used. For the analysis we compared land cover changes using two different scale map time-series in the period 1990 -2009. Two regions were selected, for which there are high resolution imagery and/or ground data available for validation and verification purposes: the entire country of Guinea-Bissau and the Huambo province in Angola. The first map time series consists of data available in international projects (IGBP, GLC2000, and MODIS) obtained from classification of 1 Km resolution imagery for three dates in the study period. The second map-set results from classification and validation of 30 meter resolution images (Landsat TM and ETM+), covering the same area in approximately the same dates. For the comparisons, the different map legends had to be aggregated into a common nomenclature to define five common classes: Forests, Savannas/Shrublands, Grasslands, Croplands/Bare soil and Wetland. The results show large discrepancies in the observed trends in agricultural areas. For example for both regions, the increase in agricultural land during the analyzed period, which is observed in high resolution maps and confirmed by validation and field knowledge, is lost in the coarse resolution maps. The deforestation rates reported by the coarse resolution maps are not verified when high resolution is employed. The consequences of these observations are discussed and future work proposed.