Agriculture lies at the heart of global food and energy security but is increasingly vulnerable to environmental change, land degradation, and resource scarcity. This session explores how remote sensing, environmental modeling, digital twins, and AI-driven analytics can transform agricultural monitoring and decision-making. We invite contributions that apply Earth observation, digital technologies, and AI to assess crop health, water and nutrient use, soil conditions, yield forecasting, and greenhouse gas emissions across diverse agroecosystems. Integrated modeling frameworks and digital twin platforms that simulate the dynamic interactions between agricultural practices, climate, and resource flows in near real time are also welcome. Topics may include digital agriculture, smart farming, land management, early warning systems, and decision-support tools. We encourage interdisciplinary research that bridges data science, agronomy, environmental modeling, and socio-economic perspectives to inform more resilient, efficient, and sustainable food systems in the face of global environmental change.

• GC - Global Environmental Change
• H - Hydrology
• IN - Informatics