convolutional CNN model that, without explicit supervision,learns to identify complex features such as roads, urban ar-eas, and various terrains. Using these features, we are ableto approach the performance of data collected in the ﬁeld forpoverty estimation. Remarkably, our approach outperformsmodels based directly on the data-rich proxies used in ourtransfer learning pipeline. Our approach can easily be gen-