Hyperspectral remote sensing of foliar nitrogen content
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...
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creator | Knyazikhin, Yuri Schull, Mitchell A. Stenberg, Pauline Mõttus, Matti Rautiainen, Miina Yang, Yan Marshak, Alexander Carmona, Pedro Latorre Kaufmann, Robert K. Lewis, Philip Disney, Mathias I. Vanderbilt, Vern Davis, Anthony B. Baret, Frédéric Jacquemoud, Stéphane Lyapustin, Alexei Myneni, Ranga B. |
description | 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. |
doi_str_mv | 10.1073/pnas.1210196109 |
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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.</description><identifier>ISSN: 0027-8424</identifier><identifier>EISSN: 1091-6490</identifier><identifier>DOI: 10.1073/pnas.1210196109</identifier><identifier>PMID: 23213258</identifier><language>eng</language><publisher>United States: National Academy of Sciences</publisher><subject>Astrophysics ; Biochemistry ; Biological Sciences ; boreal forests ; canopy ; Carbon Cycle ; Climate ; Correlation analysis ; Data Interpretation, Statistical ; Earth and Planetary Astrophysics ; Ecosystem ; Leaves ; Light ; monitoring ; Nitrogen ; Nitrogen - analysis ; nitrogen content ; Nitrogen Cycle ; Physical Sciences ; Plant Leaves - chemistry ; Plant Leaves - metabolism ; Plant Leaves - radiation effects ; PNAS Plus ; PNAS PLUS: AUTHOR SUMMARIES ; reflectance ; Remote sensing ; Remote Sensing Technology - methods ; Scattering, Radiation ; Sciences of the Universe ; Spectroscopy, Near-Infrared - methods ; Trees - chemistry ; Trees - metabolism ; Trees - radiation effects ; Vegetation mapping ; wavelengths</subject><ispartof>Proceedings of the National Academy of Sciences - PNAS, 2013-01, Vol.110 (3), p.811-812</ispartof><rights>copyright © 1993-2008 National Academy of Sciences of the United States of America</rights><rights>Copyright National Academy of Sciences Jan 15, 2013</rights><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c600t-a8f016780155b8e6982fc7bc6394681a5de37987415e0f3ea574fe606a9176383</citedby><cites>FETCH-LOGICAL-c600t-a8f016780155b8e6982fc7bc6394681a5de37987415e0f3ea574fe606a9176383</cites><orcidid>0000-0002-1500-5256 ; 0000-0002-7655-8997</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Uhttp://www.pnas.org/content/110/3.cover.gif</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/42006356$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://www.jstor.org/stable/42006356$$EHTML$$P50$$Gjstor$$H</linktohtml><link.rule.ids>230,314,723,776,780,799,881,27901,27902,53766,53768,57992,58225</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/23213258$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttps://insu.hal.science/insu-02533285$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Knyazikhin, Yuri</creatorcontrib><creatorcontrib>Schull, Mitchell A.</creatorcontrib><creatorcontrib>Stenberg, Pauline</creatorcontrib><creatorcontrib>Mõttus, Matti</creatorcontrib><creatorcontrib>Rautiainen, Miina</creatorcontrib><creatorcontrib>Yang, Yan</creatorcontrib><creatorcontrib>Marshak, Alexander</creatorcontrib><creatorcontrib>Carmona, Pedro Latorre</creatorcontrib><creatorcontrib>Kaufmann, Robert K.</creatorcontrib><creatorcontrib>Lewis, Philip</creatorcontrib><creatorcontrib>Disney, Mathias I.</creatorcontrib><creatorcontrib>Vanderbilt, Vern</creatorcontrib><creatorcontrib>Davis, Anthony B.</creatorcontrib><creatorcontrib>Baret, Frédéric</creatorcontrib><creatorcontrib>Jacquemoud, Stéphane</creatorcontrib><creatorcontrib>Lyapustin, Alexei</creatorcontrib><creatorcontrib>Myneni, Ranga B.</creatorcontrib><title>Hyperspectral remote sensing of foliar nitrogen content</title><title>Proceedings of the National Academy of Sciences - PNAS</title><addtitle>Proc Natl Acad Sci U S A</addtitle><description>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.</description><subject>Astrophysics</subject><subject>Biochemistry</subject><subject>Biological Sciences</subject><subject>boreal forests</subject><subject>canopy</subject><subject>Carbon Cycle</subject><subject>Climate</subject><subject>Correlation analysis</subject><subject>Data Interpretation, Statistical</subject><subject>Earth and Planetary Astrophysics</subject><subject>Ecosystem</subject><subject>Leaves</subject><subject>Light</subject><subject>monitoring</subject><subject>Nitrogen</subject><subject>Nitrogen - analysis</subject><subject>nitrogen content</subject><subject>Nitrogen Cycle</subject><subject>Physical Sciences</subject><subject>Plant Leaves - chemistry</subject><subject>Plant Leaves - metabolism</subject><subject>Plant Leaves - radiation effects</subject><subject>PNAS Plus</subject><subject>PNAS PLUS: AUTHOR SUMMARIES</subject><subject>reflectance</subject><subject>Remote sensing</subject><subject>Remote Sensing Technology - 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PNAS</jtitle><addtitle>Proc Natl Acad Sci U S A</addtitle><date>2013-01-15</date><risdate>2013</risdate><volume>110</volume><issue>3</issue><spage>811</spage><epage>812</epage><pages>811-812</pages><issn>0027-8424</issn><eissn>1091-6490</eissn><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.</abstract><cop>United States</cop><pub>National Academy of Sciences</pub><pmid>23213258</pmid><doi>10.1073/pnas.1210196109</doi><tpages>2</tpages><orcidid>https://orcid.org/0000-0002-1500-5256</orcidid><orcidid>https://orcid.org/0000-0002-7655-8997</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Astrophysics Biochemistry Biological Sciences boreal forests canopy Carbon Cycle Climate Correlation analysis Data Interpretation, Statistical Earth and Planetary Astrophysics Ecosystem Leaves Light monitoring Nitrogen Nitrogen - analysis nitrogen content Nitrogen Cycle Physical Sciences Plant Leaves - chemistry Plant Leaves - metabolism Plant Leaves - radiation effects PNAS Plus PNAS PLUS: AUTHOR SUMMARIES reflectance Remote sensing Remote Sensing Technology - methods Scattering, Radiation Sciences of the Universe Spectroscopy, Near-Infrared - methods Trees - chemistry Trees - metabolism Trees - radiation effects Vegetation mapping wavelengths |
title | Hyperspectral remote sensing of foliar nitrogen content |
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