SEIRS is a system for monitoring change in agronomic practices using remote sensing combined with deep learning techniques to construct synthetic counterfactual variables. It makes it possible to analyze change in practices and their impact on crop production in a cost-effective way. SEIRS rests on the concept that good agricultural yields are generally correlated with more vegetation vigor during the growing season.