YIELD4CAST - Advancements in predicting crop yields under climate change and water scarcity scenarios through the integration of crop models, remote sensing, and computer vision

YIELD4CAST is a research project developing new tools to predict crop yields at different scales, from individual fields to regional level, by combining remote sensing, computer vision, crop modelling, and climatic and socioeconomic analysis.

The initiative aims to address the major challenges that climate change poses to agriculture, including rising temperatures, more frequent heatwaves, water scarcity, and the need for more sustainable production systems. These factors increasingly affect crop productivity and highlight the need for tools that can anticipate crop performance and support decision-making.

To achieve this goal, the project uses satellite imagery, drones, and ground-based sensors to estimate key vegetation and production parameters, integrates agronomic models to simulate crop growth and yield under different environmental and climatic scenarios, and evaluates the socioeconomic impacts associated with changes in agricultural production.

The project’s outcomes will provide scalable yield prediction systems for strategic crops in areas particularly vulnerable to climate change, generate yield maps to improve water management and agricultural planning, and deliver recommendations that help strengthen the sustainability, resilience, and food security of agricultural systems.

The YIELD4CAST project (PID2024-156495OR-C31) is funded by the State Research Agency (AEI) of the Ministry of Science, Innovation and Universities (MICIU/AEI/10.13039/501100011033/) and co-funded by the European Union (FEDER/UE).