Articles | Volume 12, issue 15
https://doi.org/10.5194/bg-12-4577-2015
https://doi.org/10.5194/bg-12-4577-2015
Research article
 | 
03 Aug 2015
Research article |  | 03 Aug 2015

Predicting landscape-scale CO2 flux at a pasture and rice paddy with long-term hyperspectral canopy reflectance measurements

J. H. Matthes, S. H. Knox, C. Sturtevant, O. Sonnentag, J. Verfaillie, and D. Baldocchi

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Cited articles

Asner, G. and Martin, R.: Spectral and chemical analysis of tropical forests: Scaling from leaf to canopy levels, Remote Sens. Environ., 112, 3958–3970, https://doi.org/10.1016/j.rse.2008.07.003, 2008a.
Asner, G. P. and Martin, R. E.: Airborne spectranomics: mapping canopy chemical and taxonomic diversity in tropical forests, Front. Ecol. Environ., 7, 269–276, https://doi.org/10.1890/070152, 2008b.
Baldocchi, D., Falge, E., and Wilson, K.: A spectral analysis of biosphere-atmosphere trace gas flux densities and meteorological variables across hour to multi-year time scales, Agr. Forest Meteorol., 107, 1–27, https://doi.org/10.1016/s0168-1923(00)00228-8, 2001b.
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This research used a long-term data set of near-surface canopy hyperspectral reflectance collected over 5 years to test the ability of these measurements to predict ecosystem carbon flux at a pasture and rice paddy in the California Delta, USA. We determined that each reflectance sampling event best captured the integrated prior week of carbon dioxide uptake, providing an important benchmark for understanding the lagged correlation between ecosystem carbon uptake and biochemical reflectance.
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