Estimation of maize canopy properties from remote sensing by inversion of 1-D and 4-D models
Author(s)
Date Issued
2010
Type
Article
Abstract
The inversion of canopy reflectance models is widely used for the retrieval of
vegetation properties from remote sensing. However the accuracy of the estimates depends
on a range of factors, most notably the realism with which the canopy is represented by the
models and the possibility of introducing a priori knowledge on canopy characteristics to
constrain the inversion procedure. The objective of the present work was to compare the
performances and operational limitations of two contrasting types of radiative transfer
models: a classical one-dimensional canopy reflectance model, PROSPECT?SAIL
(PROSAIL), and a three-dimensional dynamic (4-D) maize model. The latter introduces
greater realism into the description of the canopy structure and implicit a priori information
on the crop. The assessment was carried out with multiple view angle data recorded from
field experiments on maize at stages V5 to V8. The simplex numerical optimization
algorithm was used to invert the two models, using spectral reflectance data for PROSAIL
and gap fraction data for the 4-D maize model. Leaf area index (LAI) was estimated with a
RMSE of 0.48 for PROSAIL and 0.35 for the 4-D model. Retrieval of average leaf
inclination angle (ALA) was problematic with both models. The effect of the number and
distribution of observation view angles was examined, and the results highlight the
advantage of oblique angle measurements.
Additional information
L'articolo é disponibile sul sito dell'editore: http://www.springerlink.com
Citation
Casa, R. et al. 2010. Estimation of maize canopy properties from remote sensing by inversion of 1-D and 4-D models. "Precision Agriculture" 11(4):319-334
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