Diurnal Variation in Hyperspectral Vegetation Indices Related to Winter Wheat Biomass Formation

Diurnal Variation in Hyperspectral Vegetation Indices Related to Winter Wheat Biomass Formation In this study, a comparison of six vegetation indices derived from hyperspectral reflectance measurements is presented. The aim was to assess the suitability of the indices to detect agronomically relevant crop parameters in the course of a day. Irradiance and reflectance of winter wheat (Triticum aestivum L.) were recorded simultaneously with a portable device, equipped with two spectrometers, on a near-canopy scale in a field trial. Variations in reflection properties of the wheat canopies were induced by (i) growing wheat varieties differing in growth characteristics or leaf colour, and (ii) applying different nitrogen amounts. Biomass samples were taken to determine above-ground biomass yield, N concentration in biomass, and N uptake. The indices were compared by means of analysis of variance and multiple comparisons of means. In winter wheat, considerable differences between the indices were measurable. The red edge inflection point (REIP), and the infrared index (IRI) were least subjected to diurnal variations and simultaneously proved to be most sensitive to N rate. For the REIP, the infrared green index (IRG) and the IRI, no saturation effects were observed for a high N supply. These indices seem to be most advantageous to detect agronomically relevant crop parameters in winter wheat in the course of a day. A practicable concept is proposed for the application of vegetation indices as a tool to optimise N fertilisation. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Precision Agriculture Springer Journals

Diurnal Variation in Hyperspectral Vegetation Indices Related to Winter Wheat Biomass Formation

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Publisher
Kluwer Academic Publishers
Copyright
Copyright © 2004 by Kluwer Academic Publishers
Subject
Life Sciences; Agriculture; Soil Science & Conservation; Remote Sensing/Photogrammetry; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences; Atmospheric Sciences
ISSN
1385-2256
eISSN
1573-1618
D.O.I.
10.1007/s11119-004-5322-0
Publisher site
See Article on Publisher Site

Abstract

In this study, a comparison of six vegetation indices derived from hyperspectral reflectance measurements is presented. The aim was to assess the suitability of the indices to detect agronomically relevant crop parameters in the course of a day. Irradiance and reflectance of winter wheat (Triticum aestivum L.) were recorded simultaneously with a portable device, equipped with two spectrometers, on a near-canopy scale in a field trial. Variations in reflection properties of the wheat canopies were induced by (i) growing wheat varieties differing in growth characteristics or leaf colour, and (ii) applying different nitrogen amounts. Biomass samples were taken to determine above-ground biomass yield, N concentration in biomass, and N uptake. The indices were compared by means of analysis of variance and multiple comparisons of means. In winter wheat, considerable differences between the indices were measurable. The red edge inflection point (REIP), and the infrared index (IRI) were least subjected to diurnal variations and simultaneously proved to be most sensitive to N rate. For the REIP, the infrared green index (IRG) and the IRI, no saturation effects were observed for a high N supply. These indices seem to be most advantageous to detect agronomically relevant crop parameters in winter wheat in the course of a day. A practicable concept is proposed for the application of vegetation indices as a tool to optimise N fertilisation.

Journal

Precision AgricultureSpringer Journals

Published: Dec 30, 2004

References

  • Airborne multispectral data for quantifying leaf area index, nitrogen concentration, and photosynthetic efficiency in agriculture
    Boegh, E.; Soegaard, H.; Broge, N.; Hasager, C. B.; Jensen, N. O.; Schelde, K.; Thomsen, A.
  • Comparing prediction power and stability of broadband and hyperspectral vegetation indices for estimation of green leaf are index and canopy chlorophyll density
    Broge, N. H.; Leblanc, E.

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