PROSPECT-4 and 5: Advances in the leaf optical properties model separating photosynthetic pigments

By Jean-Baptiste F'eret, Christophe François, Gregory P. Asner, Anatoly A. Gitelson, Roberta E. Martin, L. Bidel, Susan L. Ustin, Guerric le Maire, Stephane Jacquemoud. 2008

317 citations recorded by the source corpus.

Subfields: Ecology, Environmental Engineering, Plant Science

View Paper: https://www.semanticscholar.org/paper/1f9fb0292f4daed022afdfda5644cf56cc3c6844

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Citations in the corpus

Hyperspectral remote sensing of plant biochemistry using Bayesian model averaging with variable and band selection (2013, methodology): “, 2011), even given that recent advances in modeling leaf and canopy spectra have facilitated physically-based inversion (Feret et al., 2008).”
Discrete Anisotropic Radiative Transfer (DART 5) for Modeling Airborne and Satellite Spectroradiometer and LIDAR Acquisitions of Natural and Urban Landscapes (2015, unknown): “- Calculation of foliar reflectance and transmittance properties with the PROSPECT leaf RT model [16], using leaf biochemical properties (i.”
A visible band index for remote sensing leaf chlorophyll content at the canopy scale (2013, methodology): “Spectral indices are also an important method for analyzing maging spectrometer data (Gitelson, 2012; Zhu et al., 2012). Visible nd near-infrared spectral indices are sensitive to both chlorophyll ontent and LAI (Gitelson et al., 2002; Baret et al., 2007), so develpment of better indices with increa”
Calibration and validation of hyperspectral indices for the estimation of broadleaved forest leaf chlorophyll content, leaf mass per area, leaf area index and leaf canopy biomass (2008, methodology): “At leaf scale, we continue the study done in le Maire et al. (2004) using an improved and newly calibrated version of the PROSPECT model (Feret et al., 2008), and a larger experimental database.”
A physically-based model for retrieving foliar biochemistry and leaf orientation using close-range imaging spectroscopy (2016, unknown): “In the shortwave infrared (SWIR) range (between 1000 and 2500 nm), this assumption does not hold because the leaf refractive index actually depends on wavelength (Féret et al., 2008; Vanderbilt & Grant, 1985), especially due to the non-negligible in ﬂ uence of water absorption.”
Retrieving LAI, chlorophyll and nitrogen contents in sugar beet crops from multi-angular optical remote sensing: Comparison of vegetation indices and PROSAIL inversion for field phenotyping (2017, methodology): “In this study, we implemented the PRO4SAIL model (available at http://teledetection.ipgp.jussieu.fr/prosail/) that combines PROSPECT 5b (Feret et al., 2008) and 4SAIL (Verhoef et al. 2007).”