Estimating Net Primary Production for Croplands Using Advanced Wide Field Sensor (AWiFS) Time Series Data
Varaprasad
Bandaru, Oak Ridge National Laboratory, bandaruv@ornl.gov
(Presenting)
Tristram
West, Oak Ridge National Laboratory, westto@ornl.gov
Agricultural ecosystems influence regional carbon cycles, and net carbon emissions from these ecosystems can change due to changes in land management. Methods are being developed to account for site-specific changes in land management at regional to national scales. One component of carbon accounting that requires improvement is the estimation of cropland net primary production (NPP) at the field level and at regional to national scales. Developing this capability will allow improved estimates of carbon flux, along with improved estimates of land management and biomass availability. Remote sensing is often used to scale up carbon fluxes. However, major limitations for estimating cropland fluxes using remote sensing include (1) moderate resolution data (>500m) which limits the spatial delineation of crop species and represent multiple crops with single reflectance values, and (2) assumption of a single universal value for light use efficiency (LUE) in agricultural systems. In this study, we used Advanced Wide Field Sensor (AWiFS) data which provides relatively high spatial (56m) and temporal resolution (2-5 day revisit) data. Variable LUE values for different crop species, including corn and soybean, were determined using crop yield based NPP values. Annual NPP for corn and soybean were estimated with a production efficiency model. Results indicate higher LUE values for corn when compared to soybean which reflected in mean NPP values. Mean NPP for corn is 834.2 g C m-2 yr-1 whereas soybean mean NPP is 344.5 g C m-2 yr-1. It is concluded that variable LUE values and accurate crop vegetation with high resolution AWiFS data enables improved scale-up of NPP and carbon fluxes.
Presentation Type: Poster
Poster Session: Carbon Cycle Science
NASA TE Funded Awards Represented:
NONE: Related Activity or Previously Funded TE Award