Combining observations in the reflective solar and thermal domains for improved carbon and energy flux estimation

This study investigates the utility of integrating remotely sensed estimates of leaf chlorophyll (C _ab) into a thermalbased Two-Source Energy Balance (TSEB) model that estimates land-surface CO2 and energy fluxes using an analytical, light-use-efficiency (LUE) based model of canopy resistance. The LUE model component computes canopy-scale carbon assimilation and transpiration fluxes and incorporates LUE modifications from a nominal (species-dependent) value (LUE _n) in response to variations in environmental conditions. However LUE _n needs adjustment on a daily timescale to accommodate changes in plant physiological condition and nutrient status. Day to day variations in LUE _n were assessed for a corn crop field in Maryland U.S.A. through model calibration with CO ₂ flux tower observations. The optimized daily LUE _n values were then compared to estimates of C _ab integrated from gridded maps of chlorophyll content weighted over the tower flux source area. The time-continuous maps of daily C _ab over the study field were generated by fusing in-situ measurements with retrievals generated with an integrated radiative transfer modeling tool using at-sensor radiances in green, red and near-infrared wavelengths acquired with an aircraft imaging system. The resultant daily changes in C _ab within the tower flux source area exhibited a curvilinear relationship with corresponding changes in daily calibrated LUE _n values derived from the tower flux data, and hourly water, energy and carbon flux estimation accuracies from TSEB were significantly improved when using C _ab for delineating spatio-temporal variations in LUE _n. The applicability of the established relationship between LUE _n and C _ab is currently being tested for an agricultural area near Bushland, Texas using a combination of reflective and thermal satellite imagery from SPOT, Landsat and ASTER.