Primary Convener:
Alwaseela Hassan, Colorado State University

Convener:
Meijian Yang, Columbia University of New York
Phuong Dao, Department of Agricultural Biology, Colorado State University, 307 University Avenue, Fort Collins, CO 80523, USA
Alexander Ruane, NASA Goddard Institute for Space Studies
Kaitlin Gold, Cornell University, Cornell Agritech
Danyang Yu, Cornell University
Yuchi Ma, Stanford University

Early Career Convener:
Zhenqi Luo, Cornell University

Chair:
Meijian Yang, Columbia University of New York
Phuong Dao, Department of Agricultural Biology, Colorado State University, 307 University Avenue, Fort Collins, CO 80523, USA
Kaitlin Gold, Cornell University, Cornell Agritech
Danyang Yu, Cornell University

Agricultural systems are increasingly exposed to rapid environmental change and growing climatic variability, yet our ability to forecast crop performance often falls short of the precision needed for timely intervention. Recent advances in data assimilation (DA) provide a pathway to integrate diverse observations within process-based models, improving the alignment between simulated projections and field realities. In parallel, multimodal AI and remote sensing technologies are transforming our capacity to observe crops at multiple scales, from satellites to drones to in-field sensors. Together, these approaches offer real-time monitoring, anomaly detection, and dynamically updated predictions. Challenges remain in ensuring data quality, interoperability, uncertainty quantification, and biophysical balance across scales and variables. This session invites contributions that advance DA methodologies, AI frameworks, and multi-source data fusion for agricultural decision support. Our goal is to deliver robust, climate-smart forecasting systems that empower farmers, policymakers, and researchers with actionable, data-driven insights.

Index Terms
0402 Agricultural systems
0430 Computational methods and data processing
0466 Modeling
0480 Remote sensing
0540 Image processing
1942 Machine learning

Cross-Listed:
IN - Informatics

Suggested Itineraries:
Climate Change and Global Policy
Machine Learning and AI

Neighborhoods:
3. Earth Covering