• DocumentCode
    31574
  • Title

    Improving Chlorophyll Fluorescence Retrieval Using Reflectance Reconstruction Based on Principal Components Analysis

  • Author

    Xinjie Liu ; Liangyun Liu

  • Author_Institution
    Key Lab. of Digital Earth Sci., Inst. of Remote Sensing & Digital Earth, Beijing, China
  • Volume
    12
  • Issue
    8
  • fYear
    2015
  • fDate
    Aug. 2015
  • Firstpage
    1645
  • Lastpage
    1649
  • Abstract
    Methods based on Fraunhofer line discrimination (FLD) for solar-induced chlorophyll fluorescence retrieval require making assumptions or estimations about true reflectance, which is a large source of error, particularly at the O2-B band. This letter presents an alternative solution, which is named the pFLD method, based on principal components analysis to reconstruct the reflectance spectra. The principal components were generated with simulated reflectance spectra covering the most common conditions of vegetation. The pFLD method has been tested with both simulated and field experiment data sets. Compared with the widely used three-band FLD and improved FLD methods, pFLD showed better performance at the O2-B band, particularly when the spectral resolution (SR) or the signal-to-noise ratio was relatively low. The pFLD method can be also successfully applied to field measurements with credible accuracy even at low SR.
  • Keywords
    principal component analysis; remote sensing; vegetation mapping; Fraunhofer line discrimination; O2-B band; chlorophyll fluorescence retrieval; error source; improved three-band pFLD methods; principal component analysis; reflectance reconstruction; reflectance spectra; signal-to-noise ratio; simulated reflectance spectra; solar-induced chlorophyll fluorescence retrieval; spectral resolution; terrestrial vegetation; Absorption; Accuracy; Atmospheric modeling; Interpolation; Principal component analysis; Remote sensing; Signal to noise ratio; $hbox{O}_{2}-hbox{B}$ band; Fraunhofer line discrimination (FLD); O2-B band; principal components analysis (PCA); reflectance reconstruction; solar-induced chlorophyll fluorescence (Fs);
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1545-598X
  • Type

    jour

  • DOI
    10.1109/LGRS.2015.2417857
  • Filename
    7088599