The RS-ET community continues to advance the monitoring and understanding of water use and availability across diverse landscapes. These developments increasingly support operational applications in agriculture, water management, climate adaptation, ecosystem monitoring and environmental services. This session provides a forum to share advances, address challenges and explore future directions in remote sensing of ET.

This session focuses on methodological advancements in the use of remote sensing (RS) to improve the quantification of ET across a range of climates and environments. We invite contributions that demonstrate how RS techniques can enhance ET assessment, validation, uncertainty quantification, and prediction in diverse settings including agricultural landscapes, riparian zones, urban areas and forest ecosystems. The session aims to provide an overview of recent developments in RS-based ET estimation from regional to global scales. By applying innovative approaches, we seek to address the challenges of ET quantification and deepen our understanding of water and vegetation dynamics across different landscapes.

With growing societal attention to climate change, drought and flood early warning systems, ecosystem monitoring, biodiversity conservation, and the pursuit of a sustainable future, the demand for accurate estimation, modelling, mapping and forecasting of ET has expanded. We welcome contributions that leverage physically-based and hybrid models, data assimilation and fusion, sharpening algorithms, empirical and statistical methods, as well as artificial intelligence (AI) and machine learning (ML). New spaceborne and airborne sensors are creating opportunities to quantify ET across scales and ecosystems. Cloud computing platforms enable scalable, reproducible analysis through access to large datasets and computational resources. By combining advances in observations, modelling, algorithms and computing, this session aims to advance next-generation ET products and applications for sustainable water management and understanding of the terrestrial water cycle.

We welcome research, commentary and debates on:
• recent developments in RS-based ET estimation
• application of AI, cloud computing and other technological advancements
• Integration of RS, modelling, data assimilation and ground measurements
• validation, calibration, uncertainty quantification and upscaling - challenges & solutions
• future directions in RS of ET.