Deriving green crop area index and canopy chlorophyll density of winter wheat from spectral reflectance data

Deriving green crop area index and canopy chlorophyll density of winter wheat from spectral... Spectral vegetation indices (VIs) are frequently used to estimate the amount of live green canopy material. They have generally been developed as an attempt to reduce spectral effects caused by external factors such as the atmosphere and the soil background. The objective of this study is to compare the performance of selected VIs, including some hyperspectral VIs based on waveform analysis of the reflectance across the vegetation red edge. The analysis is based on biophysical data measured in a winter wheat field fertilized at three nitrogen (N) levels. The measurements were acquired continuously throughout the growing season and related to canopy spectral reflectance measured with a ground-based spectroradiometer. Green crop area index (GCAI) and canopy chlorophyll density (CCD) were the major variables determined from the biophysical data set. Canopy chlorophyll was measured using nondestructive methods based on two optical instruments. The prediction power of selected VIs calculated from spectra resampled to Landsat TM configuration was compared with narrow-band indices including some VIs based on waveform analysis techniques. It was concluded that an exponential relationship exists between the two biophysical parameters and all of the selected indices except for the simple ratio index (RVI), for which a linear relationship was formed. The results indicate that VIs based on waveform analysis using narrow bands across the red edge may improve the prediction of CCD. However, none of the hyperspectral indices that were included in the study was better at estimating GCAI than the best of the traditional VIs. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Remote Sensing of Environment Elsevier

Deriving green crop area index and canopy chlorophyll density of winter wheat from spectral reflectance data

Remote Sensing of Environment, Volume 81 (1) – Jul 1, 2002

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Publisher
Elsevier
Copyright
Copyright © 2002 Elsevier Science Inc.
ISSN
0034-4257
DOI
10.1016/S0034-4257(01)00332-7
Publisher site
See Article on Publisher Site

Abstract

Spectral vegetation indices (VIs) are frequently used to estimate the amount of live green canopy material. They have generally been developed as an attempt to reduce spectral effects caused by external factors such as the atmosphere and the soil background. The objective of this study is to compare the performance of selected VIs, including some hyperspectral VIs based on waveform analysis of the reflectance across the vegetation red edge. The analysis is based on biophysical data measured in a winter wheat field fertilized at three nitrogen (N) levels. The measurements were acquired continuously throughout the growing season and related to canopy spectral reflectance measured with a ground-based spectroradiometer. Green crop area index (GCAI) and canopy chlorophyll density (CCD) were the major variables determined from the biophysical data set. Canopy chlorophyll was measured using nondestructive methods based on two optical instruments. The prediction power of selected VIs calculated from spectra resampled to Landsat TM configuration was compared with narrow-band indices including some VIs based on waveform analysis techniques. It was concluded that an exponential relationship exists between the two biophysical parameters and all of the selected indices except for the simple ratio index (RVI), for which a linear relationship was formed. The results indicate that VIs based on waveform analysis using narrow bands across the red edge may improve the prediction of CCD. However, none of the hyperspectral indices that were included in the study was better at estimating GCAI than the best of the traditional VIs.

Journal

Remote Sensing of EnvironmentElsevier

Published: Jul 1, 2002

References

  • Comparing prediction power and stability of broadband and hyperspectral vegetation indices for estimation of green leaf area index and canopy chlorophyll density
    Broge, N.H; Leblanc, E
  • Comparison of broad-band and narrow-band red and near-infrared vegetation indices
    Elvidge, C.D; Chen, Z
  • Analyses of spectral–biophysical relationships for a corn canopy
    Gilabert, M.A; Gandia, S; Melia, J
  • Use of multispectral radiometry in wheat yellow rust experiments
    Hansen, J.G
  • Extinction coefficients of chlorophyll a and b in N , N -dimethylformamide and 80% acetone
    Inskeep, W.P; Bloom, P.R
  • Formulae for determination of chlorophylleous pigments extracted with N , N -dimethylformamide
    Moran, R
  • Chlorophyll determination in intact tissues using N , N -dimethylformamide
    Moran, R; Porath, D
  • Comparison of methods for simulating effects of nitrogen on green area index and dry matter growth in winter wheat
    Olesen, J.E; Petersen, B.M; Berntsen, J; Hansen, S; Jamieson, P.D; Thomsen, A.G
  • A modified soil adjusted vegetation index
    Qi, J; Chehbouni, A; Huete, A.R; Kerr, Y.H; Sorooshian, S
  • Estimating PAR absorbed by vegetation from bidirectional reflectance measurements
    Reujean, J; Breon, F
  • A decimal code for the growth stages of cereals
    Zadoks, J.C; Chang, T.T; Konzak, C.F

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