Iman Akhtar Smith

Iman Akhtar Smith is a Geospatial Analyst and an alumna of the Xylem Lab research group, where she served as a Research Assistant. Her work centres on remote sensing, machine learning, and food security monitoring across Sub-Saharan Africa.

During her graduate studies at the University of Maryland, Iman's research focused on remote sensing techniques to map complex farming landscapes in the Ashanti Region of Ghana. As a member of Dr. Nakalembe's Satlabel team, she contributed to projects integrating field observations with satellite imagery to improve agricultural monitoring, including the Kenya Street2Sat project, where she validated crop labels generated by a deep learning classifier, strengthening the training dataset used for crop-type classification. She also supported a NASA Harvest project assessing crop abandonment across southern Sudan, analyzing satellite imagery to identify abandoned fields and evaluate the impacts of conflict on food security.

Today, Iman is a Geospatial Analyst supporting the USDA Foreign Agricultural Service (FAS) International Production Assessment Division (IPAD). She produces crop production (AYP) maps for the USDA Crop Explorer database and conducts geospatial analyses used for agricultural monitoring across Sub-Saharan Africa, helping to integrate machine learning into crop classification and assessment workflows to improve the efficiency and accuracy of food security monitoring.

Iman's interests focus on how climate variability and weather extremes influence agricultural production and food security. She is also interested in integrating satellite imagery, machine learning, and seasonal climate forecasting to improve early warning systems, with attention to climate drivers such as the El Niño/Southern Oscillation (ENSO).

Iman holds an M.S. and B.S. in Geographical Sciences from the University of Maryland, College Park.