Fig. 11
An illustration of the ground-truth dataset (a subset of the GROW-Africa database) used to train the neural network in Fig. 14. Here, we show just the sub-national government yield statistics for maize over the period 2000-2022. In (a)-(c), the sub-national administrative boundaries (level 1 and level 2) are color-coded according to: (a) the number of years for which we have observations during the period 2000-2022, (b) the average yield value (metric tons (megagram, Mg) per hectare), and (c) the estimated fraction of the total administrative boundary that is cultivated with maize. In (c), the area fraction is determined by calculating the ratio between the reported region-total harvested area (hectares) by the total land area within the administrative boundary. Gray regions denote no data.
