The Water–Food–Land nexus represents a complex and interconnected system in which changes in water availability, agricultural production, land use, and ecosystem dynamics influence one another across spatial and temporal scales. Addressing these interconnected challenges requires integrated approaches that can capture both local variations and broader regional and global patterns.

This session explores the emerging role of GeoAI (Geospatial Artificial Intelligence) and multi-scale Earth Observation (EO) in understanding, monitoring, and managing the Water–Food–Land nexus. Advances in satellite remote sensing, cloud computing, geospatial analytics, machine learning, and AI are enabling the integration of diverse Earth observation datasets to generate timely and actionable information.

The session will highlight innovative approaches for monitoring water resources, crop and vegetation dynamics, land-use and land-cover change, drought and environmental stress, and the interactions among these systems. Particular emphasis will be placed on multi-scale analysis, data fusion, AI-driven modelling, and decision-support frameworks that can bridge field-level observations with landscape, regional, and global assessments.

By bringing together researchers, practitioners, and policymakers, the session aims to showcase how GeoAI and Earth Observation can support sustainable resource management, climate resilience, food and water security, and evidence-based planning within the interconnected Water–Food–Land nexus.