• DocumentCode
    3690530
  • Title

    A wavelet-based technique for extracting the red edge position from vegetation reflectance spectra

  • Author

    Tao Cheng;Dong Li;Xia Yao;Yongchao Tian;Yan Zhu;Weixing Cao

  • Author_Institution
    National Engineering and Technology Center for Information Agriculture (NETCIA), Jiangsu Key Laboratory for Information Agriculture, Nanjing Agricultural University, One Weigang, Nanjing, Jiangsu 210095, China
  • fYear
    2015
  • fDate
    7/1/2015 12:00:00 AM
  • Firstpage
    2673
  • Lastpage
    2676
  • Abstract
    The red edge position (REP) of a reflectance spectrum has been used as means to estimate the foliar chlorophyll content at leaf and canopy level. Most methods for extracting the REPs are based on the first derivative spectra and many studies have shown discontinuities in the REP data due to the existence of a double-peak feature in the first derivative spectra. This study proposes a new technique based on the continuous wavelet transform of foliar reflectance spectra, so that the double-peak problem could be avoided for extracting the REPs. The performance of the REPs extracted by the wavelet-based method was evaluated with data at leaf and canopy levels from a small-plot experiment of wheat crops. Our experimental results demonstrated that the wavelet-based method performed better than the two traditional methods. For the wavelet-based method, the best scale for extracting the REPs from canopy spectral data were higher than that from leaf spectral data. The findings are useful for us to understand the effect of canopy structure on REPs and the scale-dependent spectral contributions of foliar chemistry and canopy structure.
  • Keywords
    "Reflectivity","Continuous wavelet transforms","Extrapolation","Remote sensing","Data mining","Agriculture"
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium (IGARSS), 2015 IEEE International
  • ISSN
    2153-6996
  • Electronic_ISBN
    2153-7003
  • Type

    conf

  • DOI
    10.1109/IGARSS.2015.7326363
  • Filename
    7326363