• DocumentCode
    2143560
  • Title

    A method for estimating chlorophyll content of wheat from reflectance spectra

  • Author

    Xiang, Zhao ; Suhong, Liu ; Jindi, Wang ; Zhenkun, Tian

  • Author_Institution
    Res. Center for Remote Sensing & GIS, Beijing Normal Univ.
  • Volume
    7
  • fYear
    2004
  • fDate
    20-24 Sept. 2004
  • Firstpage
    4504
  • Abstract
    Chlorophyll and carotenoid, relating to the physiological function of leaves, are two pigments which can absorb the light energy during the process of plant photosynthesis. Among the pigments, the chlorophyll plays an important role in the photosynthesis, and its content, as a predictor of the nutritional status of vegetation, is one of the main factors to evaluate the environment and growth conditions for the winter wheat. This paper, based on the reflectance spectra of wheat in Xiao Tangshan County, in China, took PLS regression as the quantitative inversion method to have established the hyperspectral inversion model between chlorophyll content and the reflectance spectra of wheat. Through analysis, it indicated that the chlorophyll content of wheat was highly relative to the reflectance of hyperspectral from 350 nm to 1060 nm. The correlation coefficient between the prediction value and the measured value is as high as 0.9, and the RMSEP is lower than 0.4. The research provided an effective method to estimate the chlorophyll content using the quantitative inversion technology of hyperspectral RS
  • Keywords
    biochemistry; crops; least squares approximations; photosynthesis; physiology; reflectivity; regression analysis; vegetation mapping; 350 to 1060 nm; China; PLS regression; Xiao Tangshan County; carotenoid; chlorophyll content; correlation coefficient; environmental conditions; growth conditions; hyperspectral inversion model; hyperspectral reflectance spectra; leaves physiology; light energy absorption; nutritional status; physiological function; pigments; plant photosynthesis; quantitative inversion method; vegetation; winter wheat; Chemicals; Crops; Geographic Information Systems; Hyperspectral imaging; Hyperspectral sensors; Least squares methods; Pigments; Reflectivity; Remote sensing; Yield estimation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium, 2004. IGARSS '04. Proceedings. 2004 IEEE International
  • Conference_Location
    Anchorage, AK
  • Print_ISBN
    0-7803-8742-2
  • Type

    conf

  • DOI
    10.1109/IGARSS.2004.1370154
  • Filename
    1370154