Considerations for AI-EO for agriculture in Sub-Saharan Africa
Catherine Nakalembe, Hannah Kerner
Abstract
With the ever-growing urgency of food insecurity and the threat of climate change, there is increasing interest in using artificial intelligence for Earth observations (AI-EO) for agriculture, particularly in Sub-Saharan Africa (SSA). This paper provides an overview of the primary research areas within AI-EO for agriculture in SSA. %(cropland and crop type classification, field boundary delineation, yield estimation, and pest/disease monitoring). We discuss examples and limitations of current research and opportunities for future work. In addition, we identify ten key considerations for future efforts involving AI-EO for agriculture in SSA.
Topics & Concepts
AgricultureFood securityClimate changeFood insecurityYield (engineering)AgroforestryEnvironmental scienceWork (physics)GeographyAgricultural engineeringEnvironmental resource managementEcologyEngineeringMechanical engineeringBiologyMetallurgyArchaeologyMaterials scienceRemote Sensing in AgricultureSmart Agriculture and AILand Use and Ecosystem Services