adapted from Jacquemoud et al., (2009) and PROSAIL site.
PROSPECT pioneered the simulation of directional–hemispherical reflectance and transmittance of various green monocotyledon and dicotyledon species, as well as senescent leaves, over the solar spectrum from 400 nm to 2500 nm (Jacquemoud & Baret, 1990). It is based on the representation of the leaf as one or several absorbing plates with rough surfaces giving rise to isotropic scattering. The model uses two classes of input variables: the leaf structure parameter N which is the number of compact layers specifying the average number of air/cell walls interfaces within the mesophyll, and the leaf biochemical content, which has changed since the original formulation of the model ( Fourty et al., 1996, Jacquemoud et al., 1996 and Jacquemoud et al., 2000). The absorption of light by photosynthetic pigments which predominates in the visible (VIS) spectrum was long assumed to be entirely caused by chlorophylls, although carotenoids (including xanthophyll pigments) and anthocyanins may be significant in greening or senescing leaves. Its latest version is PROSPECT-4- Feret et al. (2008) separated total chlorophylls from total carotenoids (PROSPECT-5)
ARTMO's PROSPECT-4 and PROSPECT-5 input windows.
From ARTMO v. 3.20 onwards, PROSPECT-4 has been coupled with the COSINE (ClOse-range Spectral ImagiNg of lEaves)) model. The COSINE model describes the spectral variability caused by variable BRDF effects and leaf orientation (Jay et al., 2016).
From ARTMO v. 3.22 onwards, PROSPECT-D has been added, which adds anthocyanins to chlorophylls and carotenoids, the two plant pigments in the current version (Feret et al., 2017).
ARTMO's PROSPECT-D input window.
From ARTMO v. 3.26 onwards, PROSPECT-DyN has been added, which replaces the dry matter by Protein content (related to N) and Cellulose+Lignin (Wang et al., 2018).
ARTMO's PROSPECT-DyN input window.
ARTMO's PROSPECT-PRO input window.
Contact:
- Stéphane JACQUEMOUD, Institut de Physique du Globe de Paris & Université Paris Diderot (UMR 7154), Géophysique spatiale et planétaire, Bâtiment Lamarck, Case 7011, 35 rue Hélène Brion, 75013 Paris, France (This email address is being protected from spambots. You need JavaScript enabled to view it.)
- Jean-Baptiste FERET, UMR TETIS - IRSTEA, Maison de la Télédétection, 500 rue Jean-François Breton 34093 Montpellier cedex 5, France (This email address is being protected from spambots. You need JavaScript enabled to view it.)
- Christophe FRANCOIS, Laboratoire Ecologie, Systématique et Evolution (UMR 8079), Université Paris-Sud, 91405 Orsay Cedex, France (This email address is being protected from spambots. You need JavaScript enabled to view it.)
References:
- Féret, J.B., François, C., Asner, G.P., Gitelson, A.A., Martin, R.E., Bidel, L.P.R., Ustin, S.L., le Maire, G., & Jacquemoud, S. (2008), PROSPECT-4 and 5: advances in the leaf optical properties model separating photosynthetic pigments, Remote Sensing of Environment, 112, 3030-3043.
- Fourty T., Baret F., Jacquemoud S., Schmuck G., & Verdebout J. (1996), Optical properties of dry leaves with explicite description of their biochemical composition: direct and inverse problems. Remote Sensing of Environment, 56, 104-117.
- Jacquemoud, S., Ustin, S.L., Verdebout, J., Schmuck, G., Andreoli, G., & Hosgood, B. (1996), Estimating leaf biochemistry using the PROSPECT leaf optical properties model. Remote Sensing of Environment, 56, 194-202.
- Jacquemoud, S., & Baret, F. (1990), PROSPECT: a model of leaf optical properties spectra, Remote Sensing of Environment, 34, 75-91.
- Jay, S., Bendoula, R., Hadoux, X., Féret, J. B., & Gorretta, N. (2016). A physically-based model for retrieving foliar biochemistry and leaf orientation using close-range imaging spectroscopy. Remote Sensing of Environment,177, 220-236.
- Féret J.B., Gitelson A.A., Noble S.D., Jacquemoud S. (2017), PROSPECT-D: towards modeling leaf optical properties through a complete lifecycle, Remote Sensing of Environment, 193, 204-215
- Wang, Z., Skidmore, A. K., Darvishzadeh, R., & Wang, T. (2018). Mapping forest canopy nitrogen content by inversion of coupled leaf-canopy radiative transfer models from airborne hyperspectral imagery. Agricultural and forest meteorology, 253, 247-260.
- Féret, J. B., Berger, K., de Boissieu, F., & Malenovský, Z. (2021. PROSPECT-PRO for estimating content of nitrogen-containing leaf proteins and other carbon-based constituents. Remote Sensing of Environment, 252.