The application of geospatial science methods to enhance our understanding of how hydrological, meteorological, climatological and biogeochemical processes vary within and across landscapes is integral to understanding ecosystem function across spatial and temporal scales. Quantifying these spatial relationships and understanding how they scale is critical for accurate large- and small-scale environmental modelling. This session brings together field observations, spatial modelling using Remote Sensing, Geo AI, and geospatial techniques to improve our understanding of processes such as evapotranspiration, carbon accumulation, nutrient fluxes, contaminant transport and landscape changes Geospatial methods have undergone significant methodological changes and rapid advancement with the advent and implementation of Geo AI techniques such as machine learning, deep learning, and neural networks across natural and managed environments. We encourage contributions that use geospatial techniques, Geo AI, and Remote sensing to answer ecohydrological and biogeochemical questions.