This is a processed dataset of approximately 20,000 near-surface remote sensing images acquired using inexpensive smartphones within the context of a picture-based insurance (PBI) initiative of 1,685 smallholder farmers ﬁelds in northwest India. Monitoring crop growth and disturbances is critical in strengthening farmers’ ability to manage production risks. The data presented monitors winter wheat growth and includes meta-data, either manually or automatically derived, to quantify 5 crop greenness, phenology and damage events as well as management practices. Our dataset offers granular visual ﬁeld data, with processed images and detailed meta-data that provide information on the timing of key developmental phases of winter wheat and crop growth disturbances which are not registered by common satellite remote sensing vegetation indices or national crop cut surveys. The purpose of this high-resolution dataset is to provide a rich source of inputs in supporting of crop modeling and production risk assessment in support of food security in smallholder agricultural systems. We, therefore, foresee that these data will ﬁnd applications in crop modeling, remote sensing validation and machine learning-based crop assessment.
Feed shortages during the cropping season constrain to livestock production in small-scale crop-livestock systems in northern Ghana. The effect of stripping the lower leaves of maize at tasseling and silking to feed livestock on grain and stover yields of maize was tested over two years in northern Ghana.