Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - Retrieval of chlorophyll concentration from leaf reflectance spectra using wavelet analysis.
AU - Blackburn, George Alan
AU - Ferwerda, Jelle Garke
PY - 2008/4/15
Y1 - 2008/4/15
N2 - The dynamics of foliar chlorophyll concentrations have considerable significance for plant–environment interactions, ecosystem functioning and crop growth. Hyperspectral remote sensing has a valuable role in the monitoring of such dynamics. This study focussed upon improving the accuracy of chlorophyll quantification by applying wavelet analysis to reflectance spectra. Leaf-scale radiative transfer models were used to generate very large spectral data sets with which to develop and rigorously test refinements to the approach and compare it with existing spectral indices. The results demonstrated that by decomposing leaf spectra, the resultant wavelet coefficients can be used to generate accurate predictions of chlorophyll concentration, despite wide variations in the range of other biochemical and biophysical factors that influence leaf reflectance. Wavelet analysis outperformed predictive models based on untransformed spectra and a range of spectral indices. The paper discusses the possibilities for further refining the wavelet approach and for extending the technique to the sensing of a variety of vegetation properties at a range of spatial scales.
AB - The dynamics of foliar chlorophyll concentrations have considerable significance for plant–environment interactions, ecosystem functioning and crop growth. Hyperspectral remote sensing has a valuable role in the monitoring of such dynamics. This study focussed upon improving the accuracy of chlorophyll quantification by applying wavelet analysis to reflectance spectra. Leaf-scale radiative transfer models were used to generate very large spectral data sets with which to develop and rigorously test refinements to the approach and compare it with existing spectral indices. The results demonstrated that by decomposing leaf spectra, the resultant wavelet coefficients can be used to generate accurate predictions of chlorophyll concentration, despite wide variations in the range of other biochemical and biophysical factors that influence leaf reflectance. Wavelet analysis outperformed predictive models based on untransformed spectra and a range of spectral indices. The paper discusses the possibilities for further refining the wavelet approach and for extending the technique to the sensing of a variety of vegetation properties at a range of spatial scales.
KW - Chlorophyll
KW - Leaf
KW - Reflectance
KW - Hyperspectral
KW - Wavelet transform
UR - http://www.scopus.com/inward/record.url?scp=40649110037&partnerID=8YFLogxK
U2 - 10.1016/j.rse.2007.08.005
DO - 10.1016/j.rse.2007.08.005
M3 - Journal article
VL - 112
SP - 1614
EP - 1632
JO - Remote Sensing of Environment
JF - Remote Sensing of Environment
SN - 0034-4257
IS - 4
ER -