 This paper examined the potential of Sentinel-1A and Sentinel-2A satellite images for land cover mapping at three levels of spatial detail, exploratory, reconnaissance, and semi-detailed. Two different image classification approaches were compared, I, a traditional pixel-wise approach, and II, an object-oriented approach. The case study was designed to identify a set of radar channels, optical bands, and indices that are relevant for classification. The results showed that the integration of multispectral and radar data as explanatory variables for classification provided better results than the use of a single data source. This article was authored by Juan Ricardo Mancera Flores and Ivan Alberto Lizarazzo Salcedo.