Precision Agriculture

, Volume 14, Issue 5, pp 541–557 | Cite as

Retrieval of biophysical vegetation parameters using simultaneous inversion of high resolution remote sensing imagery constrained by a vegetation index

  • A. J. Berjón
  • V. E. Cachorro
  • P. J. Zarco-Tejada
  • A. de Frutos


This study proposes a new method for inverting radiative transfer models to retrieve canopy biophysical parameters using remote sensing imagery. The inversion procedure is improved with respect to standard inversion, and achieves simultaneous inversion of leaf area index (LAI), soil reflectance (ρsoil), chlorophyll content (Ca+b) and average leaf angle (ALA). In this approach, LAI is used to constrain modelling conditions during the inversion process, providing information about the phenological state of each plot under study. Due to the small area of the vegetation plots used for the inversion procedure and in order to avoid redundant information and improve computation efficiency, existing plot segmentation was used. All retrieved biophysical parameters, except LAI, were assumed to be invariant within each plot. The proposed methodology, based on the combination of PROSPECT and SAILH models, was tested over 16 cereal fields and 51 plots, on two dates, which were chosen to ensure crop assessment at different phenological stages. Plots were selected to provide a wide range of LAI between 0 and 6. Field measurements of LAI, ALA and Ca+b were conducted and used as ground truth for validation of the proposed model-inversion methodology. The approach was applied to very high spatial resolution remote sensing data from the QuickBird 2 satellite. The inversion procedure was successfully applied to the imagery and retrieved LAI with R 2 = 0.83 and RMSE = 0.63 when compared to LAI2000 ground measurements. Separate inversions for barley and wheat yielded R 2 = 0.89 (RMSE = 0.64) and R 2 = 0.56 (RMSE = 0.61), respectively.


Radiative transfer model inversion Leaf area index (LAI) 



The author gratefully acknowledges the extensive help provided by Dr. Richard Santer (Maison de la Recherche en Environnement Naturel, Université Cote d’Opale, France) on atmospheric correction. Financial support was provided by project GR-220 of the Government of the Autonomous Community of “Junta de Castilla y León” and now by projects AGL2009-13105, CGL2011-23413 of the Spanish “Ministerio de Educación y Ciencia”. Thanks to AERONET and PHOTON teams for provided atmospheric parameters, and also to Department of Agricultural Engineering of E. T. S. of Agriculture Engineering of Palencia at the University of Valladolid for their help.


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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • A. J. Berjón
    • 1
    • 2
  • V. E. Cachorro
    • 1
  • P. J. Zarco-Tejada
    • 3
    • 4
  • A. de Frutos
    • 1
  1. 1.Grupo de Optica Atmosférica (GOA-UVA)Universidad de ValladolidValladolidSpain
  2. 2.Atmospheric Research Center (CIAI-AEMET)Spanish Meteorological ServiceSanta Cruz de TenerifeSpain
  3. 3.Instituto de Agricultura Sostenible (IAS), Consejo Superior de Investigaciones Científicas (CSIC)CórdobaSpain
  4. 4.MARS-GeoCAPInstitute for Environment and Sustainability (IES), Joint Research Centre (JRC), European CommissionIspraItaly

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