Home > Research > Publications & Outputs > Meta-analysis of the detection of plant pigment...

Electronic data

  • fetchObject.action

    Rights statement: © 2015 Huang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

    Final published version, 1.87 MB, PDF document

    Available under license: CC BY: Creative Commons Attribution 4.0 International License

Links

Text available via DOI:

View graph of relations

Meta-analysis of the detection of plant pigment concentrations using hyperspectral remotely sensed data

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Published

Standard

Meta-analysis of the detection of plant pigment concentrations using hyperspectral remotely sensed data. / Huang, Jingfeng; Wei, Chen; Zhang, Yao et al.
In: PLoS ONE, Vol. 10, No. 9, e0137029, 10.09.2015.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

APA

Vancouver

Huang J, Wei C, Zhang Y, Blackburn GA, Wang X, Wei C et al. Meta-analysis of the detection of plant pigment concentrations using hyperspectral remotely sensed data. PLoS ONE. 2015 Sept 10;10(9):e0137029. doi: 10.1371/journal.pone.0137029

Author

Huang, Jingfeng ; Wei, Chen ; Zhang, Yao et al. / Meta-analysis of the detection of plant pigment concentrations using hyperspectral remotely sensed data. In: PLoS ONE. 2015 ; Vol. 10, No. 9.

Bibtex

@article{a6c516b954684e409a3d0bdae5219ada,
title = "Meta-analysis of the detection of plant pigment concentrations using hyperspectral remotely sensed data",
abstract = "Passive optical hyperspectral remote sensing of plant pigments offers potential for understanding plant ecophysiological processes across a range of spatial scales. Following a number of decades of research in this field, this paper undertakes a systematic meta-analysis of 85 articles to determine whether passive optical hyperspectral remote sensing techniques are sufficiently well developed to quantify individual plant pigments, which operational solutions are available for wider plant science and the areas which now require greater focus. The findings indicate that predictive relationships are strong for all pigments at the leaf scale but these decrease and become more variable across pigment types at the canopy and landscape scales. At leaf scale it is clear that specific sets of optimal wavelengths can be recommended for operational methodologies: total chlorophyll and chlorophyll a quantification is based on reflectance in the green (550–560nm) and red edge (680–750nm) regions; chlorophyll b on the red, (630–660nm), red edge (670–710nm) and the near-infrared (800–810nm); carotenoids on the 500–580nm region; and anthocyanins on the green (550–560nm), red edge (700–710nm) and near-infrared (780–790nm). For total chlorophyll the optimal wavelengths are valid across canopy and landscape scales and there is some evidence that the same applies for chlorophyll a.",
author = "Jingfeng Huang and Chen Wei and Yao Zhang and Blackburn, {George Alan} and Xiuzhen Wang and Chuanwen Wei and Jing Wang",
note = "{\textcopyright} 2015 Huang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.",
year = "2015",
month = sep,
day = "10",
doi = "10.1371/journal.pone.0137029",
language = "English",
volume = "10",
journal = "PLoS ONE",
issn = "1932-6203",
publisher = "Public Library of Science",
number = "9",

}

RIS

TY - JOUR

T1 - Meta-analysis of the detection of plant pigment concentrations using hyperspectral remotely sensed data

AU - Huang, Jingfeng

AU - Wei, Chen

AU - Zhang, Yao

AU - Blackburn, George Alan

AU - Wang, Xiuzhen

AU - Wei, Chuanwen

AU - Wang, Jing

N1 - © 2015 Huang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

PY - 2015/9/10

Y1 - 2015/9/10

N2 - Passive optical hyperspectral remote sensing of plant pigments offers potential for understanding plant ecophysiological processes across a range of spatial scales. Following a number of decades of research in this field, this paper undertakes a systematic meta-analysis of 85 articles to determine whether passive optical hyperspectral remote sensing techniques are sufficiently well developed to quantify individual plant pigments, which operational solutions are available for wider plant science and the areas which now require greater focus. The findings indicate that predictive relationships are strong for all pigments at the leaf scale but these decrease and become more variable across pigment types at the canopy and landscape scales. At leaf scale it is clear that specific sets of optimal wavelengths can be recommended for operational methodologies: total chlorophyll and chlorophyll a quantification is based on reflectance in the green (550–560nm) and red edge (680–750nm) regions; chlorophyll b on the red, (630–660nm), red edge (670–710nm) and the near-infrared (800–810nm); carotenoids on the 500–580nm region; and anthocyanins on the green (550–560nm), red edge (700–710nm) and near-infrared (780–790nm). For total chlorophyll the optimal wavelengths are valid across canopy and landscape scales and there is some evidence that the same applies for chlorophyll a.

AB - Passive optical hyperspectral remote sensing of plant pigments offers potential for understanding plant ecophysiological processes across a range of spatial scales. Following a number of decades of research in this field, this paper undertakes a systematic meta-analysis of 85 articles to determine whether passive optical hyperspectral remote sensing techniques are sufficiently well developed to quantify individual plant pigments, which operational solutions are available for wider plant science and the areas which now require greater focus. The findings indicate that predictive relationships are strong for all pigments at the leaf scale but these decrease and become more variable across pigment types at the canopy and landscape scales. At leaf scale it is clear that specific sets of optimal wavelengths can be recommended for operational methodologies: total chlorophyll and chlorophyll a quantification is based on reflectance in the green (550–560nm) and red edge (680–750nm) regions; chlorophyll b on the red, (630–660nm), red edge (670–710nm) and the near-infrared (800–810nm); carotenoids on the 500–580nm region; and anthocyanins on the green (550–560nm), red edge (700–710nm) and near-infrared (780–790nm). For total chlorophyll the optimal wavelengths are valid across canopy and landscape scales and there is some evidence that the same applies for chlorophyll a.

U2 - 10.1371/journal.pone.0137029

DO - 10.1371/journal.pone.0137029

M3 - Journal article

VL - 10

JO - PLoS ONE

JF - PLoS ONE

SN - 1932-6203

IS - 9

M1 - e0137029

ER -