HR: 0800h
AN: B51C-0215    [Abstracts]
TI: Novel Technique for Remote Estimation of Gross Primary Production in Crops: Implications for the Synoptic Monitoring of Vegetation Productivity
AU: * Gitelson, A A
EM: gitelson@calmit.unl.edu
AF: University of Nebraska, 102 Nebraska Hall, Lincoln, NE 68588 United States
AU: Vina, A
EM: vina@msu.edu
AF: University of Nebraska, 102 Nebraska Hall, Lincoln, NE 68588 United States
AU: Verma, S B
EM: sverma@unlnotes.unl.edu
AF: University of Nebraska, 102 Nebraska Hall, Lincoln, NE 68588 United States
AU: Rundquist, D C
EM: drundquist@calmit.unl.edu
AF: University of Nebraska, 102 Nebraska Hall, Lincoln, NE 68588 United States
AU: Arkebauer, T J
EM: tarkebau@unlnotes.unl.edu
AF: University of Nebraska, 102 Nebraska Hall, Lincoln, NE 68588 United States
AU: Burba, G G
EM: GBurba@unlserve.unl.edu
AF: University of Nebraska, 102 Nebraska Hall, Lincoln, NE 68588 United States
AU: Suyker, A E
EM: asuyker@unlnotes.unl.edu
AF: University of Nebraska, 102 Nebraska Hall, Lincoln, NE 68588 United States
AB: Accurate estimation of spatially distributed CO2 fluxes is of great importance for regional and global studies of carbon balance. We have found that in irrigated and rainfed crops (maize and soybean) mid-day GPP is closely related to total crop chlorophyll content. We applied a recently developed technique for remote estimation of crop chlorophyll content to assess gross primary production (GPP). The technique is based on reflectance in two spectral channels: the near-infrared and either the green or the red-edge. The technique provided accurate estimations of mid-day GPP in both crops under rainfed and irrigated conditions with root mean square error of GPP estimation of less than 0.3 mg CO2/m2s in maize (GPP ranged from 0 to 3.1 mg CO2/m2s) and less than 0.2 mg CO2/m2s in soybean (GPP ranged from 0 to 1.8 mg CO2/m2s). Validation using an independent dataset for irrigated and rainfed maize showed robustness of the technique; RMSE of GPP prediction was less than 0.27 mg CO2/m2s. Given the substantial improvement in the accuracy of GPP estimation by the models developed in this study, as compared to the currently used methods, it is worthwhile to fully explore the efficacy of these techniques over different crops, at different sites. Further validation of this technique over other crops and vegetation types is required using the green and NIR bands of satellite-based systems such as MODIS, Landsat TM and ETM, and Hyperion (onboard EO-1 satellite) as well as the red-edge and NIR bands of satellite systems such as MERIS and Hyperion. With further validation (using data from already established FluxNet and SpecNet sites), this technique may be found useful in a variety of terrestrial ecosystems. The end result may be an inexpensive yet accurate tool for estimating mid-day GPP.
DE: 0402 Agricultural systems
DE: 0422 Bio-optics
DE: 0480 Remote sensing
DE: 4806 Carbon cycling (0428)
SC: Biogeosciences [B]
MN: Fall Meeting 2005