Increasing climate variability and water scarcity are placing unprecedented pressure on agricultural systems worldwide. To address these challenges, the agricultural sector is rapidly adopting precision technologies that combine remote sensing capabilities with artificial intelligence to optimize crop water management. This session focuses on cutting-edge applications of remote sensing technologies and AI-driven analytics in transforming agricultural water management practices. We welcome research that demonstrates innovative approaches to monitoring, predicting, and managing agricultural water resources by integrating datasets from Earth observation satellites, unmanned aerial systems, Internet of Things (IoT) sensors and using advanced computational methods.
Key topics include:
Multi-platform remote sensing applications (satellite, UAV, hyperspectral, SAR, thermal infrared) for estimation of soil moisture and crop water requirement.
Deep learning and AI-driven detection of crop water stress and yield prediction.
Precision irrigation systems and automated water management technologies.
Multi-sensor data fusion combining space-based, airborne, and ground observations.
Real-time monitoring systems and subseasonal-to-seasonal water demand forecasting models.
Digital agriculture platforms and decision support tools for sustainable water management.
LLM-augmented modeling and digital twin of the agri-climatic or agri-weather landscape.
This session aims to showcase practical solutions that bridge the gap between technological innovation and real-world agricultural applications, emphasizing scalable approaches that support both productivity and environmental sustainability.