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Helmets Labeling Crops: Lacuna Fund Awarded to NASA Harvest Partners

car driving through fields

The Lacuna Fund is an initiative co-founded by The Rockefeller Foundation,, and Canada’s International Development Research Centre which aims to mobilize funding to support the development of high-quality labeled datasets in low- and middle-income contexts. The first round of funding in the agricultural AI for social good domain has now been awarded to several projects aimed at solving urgent regional problems in African countries, working hand-in-hand with organizations across Africa. Principal Investigator Dr. Catherine Nakalembe [NASA Harvest Africa Lead] has received support for the “Helmets Labeling Crops” proposal, which will ultimately produce unprecedented machine-learning-ready labeled datasets for crop type, crop pests and disease, and market prices in five African countries. This effort is supported through partnership with affiliate organizations across the NASA Harvest consortium including agricultural experts at: the University of Maryland, the Regional Universities Forum for Capacity Building in Agriculture (RUFORUM), the Center for Earth Observation and Citizen Science at the International Institute for Applied Systems Analysis, The Regional Center for Mapping of Resource for Development (RCMRD), The Eastern Africa Grain Council (EAGC), Lutheran World Relief Mali, International Maize and Wheat Improvement Center (CIMMYT), and the Radiant Earth Foundation. 


Kenya, Mali, Rwanda, Tanzania, and Dr. Nakalembe’s native Uganda are considered to be among Africa’s top food-producing regions and will be the countries of focus for this new and innovative approach to quickly collecting large amounts of labeled data through cooperative ground surveys. Together, the team will approach data collection by implementing camera-mounted equipment to the hoods of vehicles (ie. the “helmets”) and combining this information with additional crowdsourced data in order to maximize the data points available for labeling. Achieving a quality dataset that can be usefully applied to machine learning algorithm development requires a massive amount of data, which is notably challenging to obtain on a widespread scale especially during a pandemic and in high-conflict regions. It is for this reason that “Helmets Labeling Crops” places a strong focus on rapid and easy data collection supported by citizen scientists and academic researchers alike.


Not only will this project support the development of new African agricultural datasets, but a cross-benefit of this citizen science approach is that students, farmers, and others in the agricultural community will have an opportunity to explore image segmentation and receive training on how to collect and label the data. The hope is that individuals who are not usually involved in ‘typical’ academic research processes will feel empowered to use the tools already available to them (i.e. their smartphones) to take part in a community-based effort to bolster food security in their home countries. 


“My favorite part of my work is to spend time in the field. There’s so much to learn from the ground about the people, about the crops, and understanding why it is all-important. “Helmets Labeling Crops" is a one of a kind opportunity to address a critical gap, to learn and develop a cost-effective scalable approach to labeled data needed to improve the basis of agricultural monitoring. We'll also get a chance to train and work with students across Africa which is an exciting opportunity to encourage students into remote sensing, data science, and machine learning,” says Dr. Nakalembe. She has always remained true to her ambition to help build more resilient food systems through enhanced capacity building by connecting directly with farmers, governments, and other stakeholders across the agricultural sector as well as supporting young scientists and fostering powerful trust-based connections.


To learn more about the “Helmets Labeling Crops” project and the other Lacuna Fund awardees, visit

News Date
Feb 17, 2021
Mary Mitkish, Catherine Nakalembe