AI Mapping Framework Uses Satellite Data to Distinguish Maize Cropping Patterns in Kenya

A new mapping framework, Phenology-assisted Sample generation for Monoculture and Intercropped Maize machine learning mapping (PSMIM), utilizes satellite data and machine learning to accurately differentiate between monoculture and intercropped maize across Kenya's rainy seasons. This advancement reduces reliance on scarce field labels and offers a scalable method for monitoring food production in smallholder regions, where intercropping is often overlooked in official statistics.