F11. Land surface monitoring and prediction using remote sensing

Remote sensing has become a key tool for monitoring and prediction of environmental variables. Remotely sensed observations from ground based, airborne and space borne instruments are providing improved understanding of the water, energy, and carbon exchanges between the ground and atmosphere. These data are also being used to improve the prediction capabilities of land surface processes. This session aims to highlight recent advances in remote sensing of the land surface and how this has been used to improve physical process understanding and predictive skill. Specific areas of interest include new remote sensing techniques, innovative land surface parameter retrieval algorithms, improved interpretation of remotely sensed observations for physical process understanding, and improvements in model predictive skill.