Crop Monitoring Using Smartphone Based Near-Surface Remote Sensing: Ground Pictures of Wheat and Auxiliary Data from Northern India

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.