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Hyperspectral remote sensing of foliar nitrogen content

Knyazikhin, Y., M. A. Schull, P. Stenberg, M. Mõttus, M. Rautiainen, Y. Yang, A. Marshak, P. L. Carmona, R. K. Kaufmann, P. Lewis, M. I. Disney, V. Vanderbilt, A. B. Davis, F. Baret, S. Jacquemoud, A. Lyapustin, and R. B. Myneni (2012), Hyperspectral remote sensing of foliar nitrogen content, Proc. Natl. Acad. Sci., doi:10.1073/pnas.1210196109.

A strong positive correlation between vegetation canopy bidirectional reflectance factor (BRF) in the near infrared (NIR) spectral region and foliar mass-based nitrogen concentration (%N) has been reported in some temperate and boreal forests. This relationship, if true, would indicate an additional role for nitrogen in the climate system via its influence on surface albedo and may offer a simple approach for monitoring foliar nitrogen using satellite data. We report, however, that the previously reported correlation is an artifact—it is a consequence of variations in canopy structure, rather than of %N. The data underlying this relationship were collected at sites with varying proportions of foliar nitrogen-poor needleleaf and nitrogen-rich broadleaf species, whose canopy structure differs considerably. When the BRF data are corrected for canopy-structure effects, the residual reflectance variations are negatively related to %N at all wavelengths in the interval 423–855 nm. This suggests that the observed positive correlation between BRF and %N conveys no information about %N. We find that to infer leaf biochemical constituents, e.g., N content, from remotely sensed data, BRF spectra in the interval 710–790 nm provide critical information for correction of structural influences. Our analysis also suggests that surface characteristics of leaves impact remote sensing of its internal constituents. This further decreases the ability to remotely sense canopy foliar nitrogen. Finally, the analysis presented here is generic to the problem of remote sensing of leaf-tissue constituents and is therefore not a specific critique of articles espousing remote sensing of foliar %N.

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Radiation Science Program (RSP)