AI and Satellites may promote food security in the Mediterranean

The Mediterranean region, known for its diverse crops and challenging climate, faces growing pressure from droughts, temperature extremes, and resource scarcity. A new study by Wondimagegn Abebe Demissie, Luca Sebastiani, and Rudy Rossetto from the Institute of Crop Science at Scuola Superiore Sant’Anna (Pisa, Italy) highlights how combining artificial intelligence (AI) and remote sensing (RS) technologies can transform this fragile agroecosystem into a model of sustainable resilience.

Published in the European Journal of Agronomy, the research systematically reviewed 106 scientific studies to identify how AI-driven models and satellite data—particularly from Sentinel, MODIS, and Landsat missions—can predict crop yields and assess plant growth dynamics with unprecedented accuracy. Machine learning algorithms such as Random Forest, Support Vector Machines, and Neural Networks proved highly effective for analyzing satellite imagery, while emerging deep learning models showed promise for integrating spatio-temporal data on crop stress and phenology.

The study emphasizes that hybrid frameworks, which blend satellite, drone, and field data, offer the best potential for precise agricultural monitoring. However, it also calls for broader data sharing, standardized validation methods, and stronger collaboration across Mediterranean countries—especially in underrepresented regions of North Africa and the Middle East.

By bridging data science and agronomy, the Institute of Crop Science and its researchers are leading the way toward climate-smart agriculture. Their work contributes to global food security in an era of accelerating environmental change.