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Workshop: Machine Learning for the Developing World (ML4D): Improving Resilience

Invited Talk 5: Earth Observations and Machine Learning for Agricultural Development

Catherine Nakalembe


Abstract:

EO data offer timely, objective, repeatable, global, scalable, and long-dense records and methods to monitor diverse landscapes and often low-cost alternatives to traditional agricultural monitoring. The importance of these data in informing life-saving decision making can not be overstated. NASA Harvest is NASA’s Agriculture and Food Security Program. This talk will summaries the current state of food security in SSA based on the recent Status of Food Security and Nutrition Report and provide an overview of NASA Harvest’s Africa Program priorities and how we are leveraging Machine Learning to address critical data gaps necessary in planning, implementation and informing agricultural development and measuring progress towards SDG-2