4.7 Article

Modeling gross primary productivity for winter wheat-maize double cropping System using MODIS time series and CO2 eddy flux tower data

Journal

AGRICULTURE ECOSYSTEMS & ENVIRONMENT
Volume 129, Issue 4, Pages 391-400

Publisher

ELSEVIER
DOI: 10.1016/j.agee.2008.10.017

Keywords

Crop intensity; Vegetation index; Vegetation photosynthesis model; Multiple cropping

Funding

  1. National Science Foundation of China [40601064]
  2. State Key lab of Resources and Environmental Information System
  3. National Key Project of Scientific and Technical Supporting Programs [200613AC08B03, 2006BAC08B06]
  4. CAS [CXTD-Z2005-1]
  5. NASA [NNH04ZYS005N, NNG05GH80G]

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Accurate and spatially explicit monitoring of gross primary productivity of agricultural ecosystems at a large scale is of great significance to assessment of crop conditions and agricultural production, and is necessary for understanding the carbon balance of the terrestrial biosphere. Identifying crop intensity (including multiple cropping and crop calendar) dynamics and assigning appropriate light use efficiency to C3 and C4 crops could substantially improve our ability to model and evaluate the seasonal dynamics of carbon flux in intensified agricultural ecosystems. In this paper, we have analyzed temporal dynamics of vegetation indices and phenological characteristics in the winter-wheat and maize double cropping system using multi-year satellite images from the moderate resolution imaging spectral radiometer (MODIS) and in situ observation of key crop phenological transition dates. The multiple cropping and crop calendar information were incorporated into simulations of the satellite-based vegetation photosynthesis model (VPM). Canopy-level maximum light use efficiency, a key parameter in the satellite-based VPM model, was estimated for both winter wheat (0) and maize (C4) based on the observed CO2 flux data from an eddy flux tower site in a winter wheat-maize double cropping agro-ecosystem in the Huang-Huai-Hai plain, China. The seasonal dynamics of GPP predicted by the VPM model agreed well with estimated GPP from eddy flux tower data. These results demonstrate the potential of the satellite-driven VPM model for scaling-up GPP estimation of intensified agricultural ecosystems, which is relevant to food production and security. (C) 2008 Elsevier B.V. All rights reserved.

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