Abstract
To predict and respond to famine and other forms of food insecurity, different early warning systems are using remote analyses of crop condition and agricultural production, using satellite-based information. To improve these predictions, a reliable estimation of the cultivated area at national scale must be carried out. In this study, we developed a data mining methodology for extracting cultivated domain patterns based on their temporal behavior as captured in time-series of moderate resolution remote sensing MODIS images.