The main objective of this project is to advance national agriculture monitoring by using Earth Observations (EO) data in East and Southern Africa through the development of in-season semi-automated baseline datasets derived from scalable machine learning tools and open data, both of which are needed for more accurate agriculture monitoring.

This research will advance methods for field data collection in support of in-season crop assessments and test EO-based, automated conditions as well as yield assessment. The project will strengthen the capacity of the SERVIR E&SA-Hub and the Regional Center for Mapping of Resources for Development (RCMRD) to implement and support scaling up methodologies to other use-cases, including operational national crop monitors, disaster risk, and insurance programs.