Announcing the Winners of Radiant Earth’s Competition for Crop Detection in Africa

Five Data Scientists emerged as winners of Radiant Earth Foundation’s competition, in partnership with Zindi Africa, to create a machine learning model that classifies farm fields in Kenya by crop type using time series of Sentinel-2 satellite imagery collected during the growing season.

Earth observations provide critical data for agricultural monitoring at scale, and machine learning (ML) techniques are best suited to learn from these data. Yet, building agricultural ML models poses a problem in Africa due to limited training data, as well as add-on hurdles created by the relatively small size of the farms. These difficulties prompted Radiant Earth to design a competition to crowdsource data science skills globally for the best crop detection model.