• DocumentCode
    3375
  • Title

    On Hyperspectral Remote Sensing of Leaf Biophysical Constituents: Decoupling Vegetation Structure and Leaf Optics Using CHRIS–PROBA Data Over Crops in Barrax

  • Author

    Latorre-Carmona, Pedro ; Knyazikhin, Yuri ; Alonso, Luis ; Moreno, Jose F. ; Pla, Filiberto ; Yang Yan

  • Author_Institution
    Dept. de Lenguajes y Sist. Informaticos, Univ. Jaume I, Castellon, Spain
  • Volume
    11
  • Issue
    9
  • fYear
    2014
  • fDate
    Sept. 2014
  • Firstpage
    1579
  • Lastpage
    1583
  • Abstract
    Scattering from a leaf responds differently at different wavelengths to changes in leaf properties such as pigment concentrations, chemical constituents, internal structure, and leaf-surface properties. Radiation scattered by leaves and exiting the vegetation canopy toward the sensor is affected by canopy structure. The concept of canopy spectral invariants is used to decompose multiangular hyperspectral Compact High Resolution Imaging Spectroradiometer-PROBA surface reflectances over agricultural crops during peak growth season into structural and optical components. The former, called the directional area scattering factor, is determined by the canopy geometrical properties and varies with crop type. The latter is a function of the leaf scattering properties and more directly related to the leaf interior. For dense crops, the decomposition technique does not require the use of canopy radiation models, prior knowledge, or ancillary information regarding the leaf scattering properties and thus provides a powerful means to remove canopy structural influences in hyperspectral remote sensing of leaf biochemical constituents. Our results also suggest that leaf-surface characteristics can increase canopy scattering spectra. This may decrease the ability to remotely sense leaf biochemistry.
  • Keywords
    remote sensing; vegetation; Barrax; CHRIS-PROBA data; Compact High Resolution Imaging Spectroradiometer; agricultural crops; canopy geometrical properties; canopy radiation models; canopy spectral invariant concept; chemical constituents; decomposition technique; decoupling vegetation structure; hyperspectral remote sensing; internal structure; leaf biochemical constituents; leaf biophysical constituents; leaf optics; leaf scattering properties; leaf-surface properties; multiangular hyperspectral CHRIS-PROBA surface reflectances; optical components; pigment concentrations; remotely sense leaf biochemistry; vegetation canopy; Agriculture; Biochemistry; Hyperspectral sensors; Scattering; Sugar industry; Vegetation mapping; Canopy structure; hyperspectral remote sensing; leaf biochemical constituents; leaf optics; spectral invariants;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1545-598X
  • Type

    jour

  • DOI
    10.1109/LGRS.2014.2305168
  • Filename
    6747962