Hyperspectral remote sensing of foliar nitrogen content

Research output: Contribution to journalArticleScientificpeer-review

Researchers

  • Yuri Knyazikhin
  • Mitchell A. Schull
  • Pauline Stenberg
  • Matti Mõttus
  • Miina Rautiainen

  • Yan Yang
  • Alexander Marshak
  • Pedro Latorre Carmona
  • Robert K. Kaufmann
  • Philip Lewis
  • Mathias I. Disney
  • Vern Vanderbilt
  • Anthony B. Davis
  • Frédéric Baret
  • Stéphane Jacquemoud
  • Alexei Lyapustin
  • Ranga B. Myneni

Research units

  • Boston University
  • United States Department of Agriculture
  • University of Helsinki
  • NASA Goddard Space Flight Center
  • Jaume I University
  • University College London
  • NASA Ames Research Center
  • Jet Propulsion Laboratory, California Institute of Technology
  • Institut National de la Recherche Agronomique
  • Université Sorbonne Paris Cité

Abstract

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.

Details

Original languageEnglish
Pages (from-to)E185-E192
JournalProceedings of the National Academy of Sciences of the United States of America
Volume110
Issue number3
Publication statusPublished - 15 Jan 2013
MoE publication typeA1 Journal article-refereed

    Research areas

  • Carbon cycle, Plant ecology, Radiative effect, Spurious regression

ID: 7045507