2006
DOI: 10.1093/jxb/erl123
|View full text |Cite
|
Sign up to set email alerts
|

Hyperspectral remote sensing of plant pigments

Abstract: The dynamics of pigment concentrations are diagnostic of a range of plant physiological properties and processes. This paper appraises the developing technologies and analytical methods for quantifying pigments non-destructively and repeatedly across a range of spatial scales using hyperspectral remote sensing. Progress in deriving predictive relationships between various characteristics and transforms of hyperspectral reflectance data are evaluated and the roles of leaf and canopy radiative transfer models ar… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

10
359
0
15

Year Published

2010
2010
2020
2020

Publication Types

Select...
7
2

Relationship

0
9

Authors

Journals

citations
Cited by 585 publications
(421 citation statements)
references
References 119 publications
10
359
0
15
Order By: Relevance
“…In addition, differences in plant structure, changes in soil reflectance, and changes in soil moisture and leaf moisture might affect the relationship between Landsat 8 VIs and CC at ESU level [43] particularly at LAI < 3 [89].…”
Section: Chl Mapmentioning
confidence: 99%
See 1 more Smart Citation
“…In addition, differences in plant structure, changes in soil reflectance, and changes in soil moisture and leaf moisture might affect the relationship between Landsat 8 VIs and CC at ESU level [43] particularly at LAI < 3 [89].…”
Section: Chl Mapmentioning
confidence: 99%
“…In addition, they suffer from the so-called ill-posed problem [40,41] due to model and measurements uncertainties; that is, different model parameters might result in very similar spectra [42]. The VI approach is based on the statistical or empirical relationship between arithmetic combinations of two or more spectral bands and a particular leaf or canopy characteristic (i.e., chlorophyll concentration) [43]. It has been argued that this approach is sensor-specific, site-dependent, and does not account for variability in LAI.…”
Section: Introductionmentioning
confidence: 99%
“…Thin films of insect wings are the parts of the visual surroundings of Odonata which can produce spectral features of a width in the order of 30 nm. In comparison, no features of this sharpness are encountered by vegetation (Blackburn, 2006; Thenkabail & Lyon, 2016) and absorption of organic pigments or chromophores do not exhibit such sharp spectral features (Hill & McGraw, 2006a; Popp, Tuchin, Chiou, & Heinemann, 2011). Structural interference colors are common in insects and Odonata, and they arise from dominant spatial frequencies of refractive index of submicron organized structures or organelles (omochrome granules) and exhibit spectral features of some 150 nm width (Nixon, Orr, & Vukusic, 2013, 2015; Shawkey et al., 2009).…”
Section: Introductionmentioning
confidence: 99%
“…During wheat growth, the leaves, canopy and spikes can absorb, reflect, or transmit energy reaching the surface due to interaction of incident radiation with the plant structure and photosynthetic elements [10,11]. By determining the spectral signature of canopy and leaf reflectance with a spectroradiometer, it is possible to indirectly measure agronomic and physiological traits [9,12] such as chlorophyll content [13,14], aerial biomass [15], plant water content [16], or grain yield [17,18].…”
Section: Introductionmentioning
confidence: 99%