 This paper proposes a novel methodology for producing land cover maps at country scale from high-resolution optical images. It utilizes existing databases as reference data for training and validation, and employs a supervised classifier to produce accurate results. The methodology is efficient, requiring only one pass through the acquired images, and can be used to quickly deliver land cover maps with a high degree of accuracy. This article was authored by Jordy Englata, Arthur Vincent, Marcella Arias, and others.