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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #298029
Title: Integrating solar induced flourescence and the photochemical reflectance index for estimating gross primary production in a cornfield

Author
item CHENG, Y - Collaborator
item MIDDLETON, E - National Aeronautics And Space Administration (NASA)
item ZHANG, Q - Universities Space Research Associaton
item CORP, L - Sigma Space Corporation
item HUEMMRICH, K - Collaborator
item CAMPBELL, P - University Of Maryland
item COOK, B - National Aeronautics And Space Administration (NASA)
item Kustas, William - Bill
item Daughtry, Craig

Submitted to: Remote Sensing
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/27/2013
Publication Date: 12/9/2013
Publication URL: http://handle.nal.usda.gov/10113/60247
Citation: Cheng, Y., Middleton, E.M., Zhang, Q., Corp, L.A., Huemmrich, K.F., Campbell, P., Cook, B.D., Kustas, W.P., Daughtry, C.S. 2013. Integrating solar induced flourescence and the photochemical reflectance index for estimating gross primary production in a cornfield. Remote Sensing. 5:6857-6879.

Interpretive Summary: Carbon sequestration by terrestrial ecosystems is a key factor for understanding the carbon budget at a global scale. Gross primary production is a measure of the amount of carbon fixed by plants at the ecosystem scale. Accurate measurements of gross primary productivity GPP will allow us to quantitatively assess impacts of climate changes and human activities. Remotely sensed data can track photosynthetic activity and detect environmental stresses that reduce light use efficiency at various spatial and temporal scales. Light use efficiency, gross primary production, and remotely sensed data were measured in a corn field over four growing seasons at the Beltsville Agricultural Research Center near Beltsville, Maryland. The remotely sensed data successfully captured the diurnal and seasonal dynamics of plant responses to environmental conditions. These results demonstrated that remotely sensed data can provide a powerful tool for carbon monitoring.

Technical Abstract: The utilization of remotely sensed observations for light use efficiency (LUE) and tower-based gross primary production (GPP) estimates was studied in a USDA cornfield. Nadir hyperspectral reflectance measurements were acquired at canopy level during a collaborative field campaign conducted in four growing seasons. The Photochemical Reflectance Index (PRI) and solar induced chlorophyll fluorescence (SIF), were derived. SIF retrievals were accomplished in the two telluric atmospheric oxygen absorption features centered at 688 nm (O2-B) and 760 nm (O2-A). The PRI and SIF were examined in conjunction with GPP and LUE determined by flux tower-based measurements. All of these fluxes, environmental variables, and the PRI and SIF exhibited diurnal as well as day-to-day dynamics across the four growing seasons. Consistent with previous studies, the PRI was shown to be related to LUE (r2=0.54 with a logarithm fit), but the relationship varied each year. By combining the PRI and SIF in a linear regression model, stronger performances for GPP estimation were obtained. The strongest relationship (r2=0.80, RMSE=0.186 mg CO2/m2/s) was achieved when using the PRI and SIF retrievals at 688 nm. Cross-validation approaches were utilized to demonstrate the robustness and consistency of the performance. This study highlights a GPP retrieval method based entirely on hyperspectral remote sensing observations.