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Modeling Canopy Spectral Properties to Retrieve Biophysical and Biochemical Characteristics

  • FrÉderic Baret
  • Stephane Jacquemoud
Part of the Eurocourses: Remote Sensing book series (EURS, volume 4)

Abstract

Retrieval of canopy biophysical and biochemical characteristics from high spectral resolution data is investigated using model simulation. In the first part, we describe leaf, soil and canopy reflectance models that will be coupled to give the SPECAN model. It allows to compute canopy reflectance spectra as a function of canopy biophysical and biochemical characteristics. Then two approaches for canopy characteristics retrieval are considered.

The first one is based on wavelength shifts observed in the red edge of canopy reflectance. This spectral index characterized by the wavelength position of the inflexion point of the red edge minimizes the effects of soil optical properties, specular component and of the atmosphere. It is sensitive to leaf area index, chlorophyll concentration and leaf inclination. However, this approach is rather empirical and the link to individual canopy characteristics is not explicit.

The second approach is based on model inversion. Preliminary results indicate that it can provide good estimates of both leaf chlorophyll concentration and water equivalent thickness. However, the inversion process has to be stabilized to get reasonable values of canopy structure parameters. Further, in the inversion process, soil background optical properties are supposed known.

Finally, the model is used to investigate the sensitivity of canopy reflectance to leaf optical properties. These results initiate a discussion about the capability of high spectral resolution to remotely sense leaf biochemical composition.

Keywords

Leaf Area Index Chlorophyll Concentration High Spectral Resolution Single Scattering Albedo Near Infrared Reflectance Spectroscopy 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© ECSC, EEC, EAEC, Brussels and Luxembourg 1994

Authors and Affiliations

  • FrÉderic Baret
    • 1
  • Stephane Jacquemoud
    • 1
  1. 1.INRA BioclimatologieMontfavet CedexFrance

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