Integrating Remote Sensing and Modeling to Assess Temporal and Spatial Variability of Greenhouse Gas Emissions

Agriculture has been a major source of CO2 and N2O to the atmosphere. Although agricultural soil management is advocated as a viable option to reduce greenhouse gas (GHG) emissions, comprehensive assessments of GHG across multiple spatial and temporal scales have been challenging. The main objective was to use a timed series of remotely sensed plant biomass and soil moisture data as validation for a crop growth and soil water module of the ecosystem model. We seek to integrate remotely sensed measurements across spatial and temporal scales in order to reveal crop growth and production dynamics, enhancing accuracy in assessment of GHG emissions.