*Principal Investigator Integrating Remote Sensing and Modeling to Assess Temporal and Spatial Variability of Greenhouse Gas

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. Approach and Procedures The objective is met by combining remotely sensed data with field information and modeling results to estimate the potential for CO2 and N2O emission at the plot, field, county and, eventually, the regional scale. Carbon assimilation from the atmosphere through plant productivity is a major carbon pathway into terrestrial systems. We combine images from NASA’s Earth Observing System (MODIS and ASTER satellites) to monitor crops grown on specific parcels in Yolo County in order to integrate remote sensing and modeling i