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

Huang, Jingfeng and Wei, Chen and Zhang, Yao and Blackburn, George Alan and Wang, Xiuzhen and Wei, Chuanwen and Wang, Jing (2015) Meta-analysis of the detection of plant pigment concentrations using hyperspectral remotely sensed data. PLoS ONE, 10 (9). ISSN 1932-6203

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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.

Item Type:
Journal Article
Journal or Publication Title:
PLoS ONE
Additional Information:
© 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.
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2700
Subjects:
ID Code:
75795
Deposited By:
Deposited On:
25 Nov 2015 11:56
Refereed?:
Yes
Published?:
Published
Last Modified:
21 Oct 2020 03:31