Optimizing spectral indices and chemometric analysis of leaf chemical properties using radiative transfer modeling

By Jean-Baptiste F'eret, Christophe François, Anatoly A. Gitelson, Gregory P. Asner, K. Barry, C. Panigada, Andrew D. Richardson, Stephane Jacquemoud. 2011

320 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Ecology, Plant Science

View Paper: https://www.semanticscholar.org/paper/c23eba0018b889d2e55ce70eec1a88c8a7d012c1

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In Analytical Chemistry

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Citations in the corpus

How the Optical Properties of Leaves Modify the Absorption and Scattering of Energy and Enhance Leaf Functionality (2020, methodology): “These methods can easily be overfitted, so care is needed to produce a realistic result (Féret et al. 2011).”
Seasonal variability of multiple leaf traits captured by leaf spectroscopy at two temperate deciduous forests. (2016, unknown): “This suggests that the variability of leaf traits in our dataset was not fully captured by the SVIs, despite that our dataset covering a broad ranges of values observed by others (Féret et al., 2011).”
Different units of measurement of carotenoids estimation in cotton using hyperspectral indices and partial least square regression (2014, background): “Those results showed that the main disadvantage of band selection indices probably was their empirical base, which can result in a lack of generality (Féret et al., 2011).”
Combining leaf physiology, hyperspectral imaging and partial least squares-regression (PLS-R) for grapevine water status assessment (2015, background): “To date, despite successful implementations in studies of various species and stress factors (e.g., Feret et al., 2011; Hansen and Schjoerring, 2003; Herrmann et al., 2011; Li et al., 2014; Nguyen and Lee, 2006; Ramoelo et al., 2013; Yi et al., 2014), only a couple of water deficit-related…”
Proximal Remote Sensing Buggies and Potential Applications for Field-Based Phenotyping (2014, background): “The power of many of these techniques can be enhanced by a combination with radiative transfer modelling [71,72], which allows one to correct for complexity introduced by shadowing and complex canopy structure.”
A physically-based model for retrieving foliar biochemistry and leaf orientation using close-range imaging spectroscopy (2016, unknown): “The distributions of PROSPECT parameters were estimated from seventeen independent data sets made available by Féret et al. (2011); Féret, personal communication.”
A Bayesian object based approach for estimating vegetation biophysical and biochemical variables from APEX at sensor radiance data (2013, result): “Contrary to other studies using broad ranges for N in order to include various plant species or development stages (Atzberger, 2004; Combal et al., 2002; Féret et al., 2011), Nwas assumed to vary little within a crop type, and smaller variation ranges were therefore used (Darvishzadeh et al., 2011).”
Hyperspectral remote sensing of plant biochemistry using Bayesian model averaging with variable and band selection (2013, methodology): “This difficulty is directly manifested by a lack of commonality in the chosen wavebands and spectral indices among prior research for estimating the same biochemical of interest (Feret et al., 2011; Grossman et al., 1996), though with few exceptions (e.”