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Assessing the Robustness of Vegetation Indices to Estimate Wheat N in Mediterranean Environments

Authors: Davide Cammarano; Glenn Fitzgerald; Raffaele Casa; Bruno Basso;

Assessing the Robustness of Vegetation Indices to Estimate Wheat N in Mediterranean Environments

Abstract

Remotely sensed vegetation indices have been extensively used to quantify plant and soil characteristics. The objectives of this study were to: (i) compare vegetation indices developed at different scales for measuring canopy N content (g∙N∙m−2) and concentration (%); and (ii) evaluate the effects of soil background reflectance, cultivar, illumination and atmospheric conditions on the ability of vegetation indices to estimate canopy N content. Data were collected from two rainfed field sites cropped to wheat in Southern Italy (Foggia) and in Southeastern Australia (Horsham). From spectral readings, 25 vegetation indices were calculated. The Perpendicular Vegetation Index showed the best prediction of plant N concentration (%) (r2 = 0.81; standard error (SE) = 0.41%; p < 0.001). The Canopy Chlorophyll Content Index showed the best predictive capability for canopy N content (g∙N∙m−2) (r2 = 0.73; SE = 0.603; p < 0.001). Canopy N content was best related to indices developed at the canopy scale and containing a red-edge wavelength. Canopy-scale indices were related to canopy N%, but such relationships needed to be normalized with biomass. Geographical location influenced mainly simple ratio or normalized indices, while indices that contained red-edge wavelengths were more robust and able to estimate canopy parameters more accurately.

Country
Italy
Keywords

biomass, Science, Q, Mediterranean environment, nitrogen, remote sensing, vegetation indices, wheat, nitrogen; vegetation indices; Mediterranean environment; wheat; biomass; remote sensing

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    82
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    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
82
Top 1%
Top 10%
Top 10%
gold