Combining Deep Learning and Street View Imagery to Map Smallholder Crop Types

Accurate crop type maps are an essential source of information for monitoring yield progress at scale, projecting global crop production, and planning effective policies. To date, however, crop type maps remain challenging to create in low and middle-income countries due to a lack of ground truth labels for training machine learning models. Field surveys are the gold standard in terms of accuracy but require an often-prohibitively large amount of time, money, and statistical capacity. In recent years, street-level imagery, such …

cs.ai cs.cv deep learning global income information labels low map maps monitoring planning production progress scale street truth type types view