Xylem supports the AGRA and COMESA-led Regional Food Balance Sheet (RFBS), which uses data from various public and private sources to develop near real-time and forward-looking food balance estimates. Our team develops crop yield analytics from satellite and historically reported yields to forecast seasonal yields and crop production for RFBS countries.

The Harvest Africa initiative aims to enhance food security, agricultural productivity, and resilience across Africa by promoting the use of Earth Observation (EO) data among national and regional agencies. This program focuses on strengthening monitoring and early warning systems to deliver actionable agricultural intelligence, refining underlying methodologies, building local capacity for data-driven decision-making, and fostering lasting partnerships. Through these efforts, Harvest Africa works to empower African institutions with the tools and expertise needed to leverage satellite data for improved agricultural outcomes and food security planning.

The Helmets Labeling Crops Project (“Helmets” for short)Lacuna Fund- funded by the Lacuna Fund is developing and applying innovative, scalable data collection approaches that can inform machine learning (ML) tools to support higher-frequency crop-type mapping.

NASA Harvest is NASA’s Food Security and Agriculture Program. Led by the Univerity of Maryland. Harvest's mission is to enable and advance the adoption of satellite Earth observations by public and private organizations to benefit food security, agriculture, and human and environmental resiliency in the US and worldwide. We accomplish this through a multidisciplinary and multisectoral Consortium of leading scientists and agricultural stakeholders, led by researchers at the University of Maryland and implemented with our global partners. Dr. Nakalembe is the Africa Program lead for NASA Harvest. 

Earth Observations for National Agriculture Monitoring (EO-NAM) for West Africa

Funded by NASA SERVIR and working with CSE Senegal, 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 AI and machine learning tools and open data for more accurate agriculture monitoring.

Developing a Framework for Regional Yield Data Collection, 2023

The second round of work under ECAAS built upon key lessons from Phase-1. Early collaboration with the Ministry of Agriculture ensured program alignment with monitoring needs and sustainable institutionalization. Developing sampling frameworks well in advance guided effective data collection while utilizing county extension agents leveraged their valuable local knowledge and farmer relationships. The UMD team's direct involvement in field training and data collection facilitated skill transfer, and Kenya's approach served as a model for developing sampling frameworks in other focus countries.

Our EO-FARM project, EO-FARM, was funded by the SwissRe Foundation. The project aimed to develop semi-automated, scalable remote sensing-based datasets and information products for maize and wheat conditions and yield assessment.

Our project collected rice field data in Tanzania with Sokoine University and Flamingoo Food Limited partners. Using ECAAS's Open Data Kit to demonstrate how to optimize data collection while reducing costs for critical agricultural decision-making.