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A.Olioso, S. Jacquemoud* & F. Baret UMR Climat, Sol et Environnement INRA Avignon, France * Institut de Physique du Globe de Paris (IPGP) Département de.

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1 A.Olioso, S. Jacquemoud* & F. Baret UMR Climat, Sol et Environnement INRA Avignon, France * Institut de Physique du Globe de Paris (IPGP) Département de Géophysique Spatiale et Planétaire Université Paris 7 - Denis Diderot Adaptation of the leaf optical property model PROSPECT to thermal infrared

2 Radiative properties of leaves in the thermal infrared are required for implementing radiative transfer models ex: => remote sensing studies => fire propagation studies Model of leaf properties are required for => analysing variations of leaf properties (ex. with leaf moisture) => linking leaf properties to plants processes There is no such model ! => building a model on the basis of the PROSPECT model (Jacquemoud and Baret 1990) which is working in the solar domain

3 transmitted + emitted absorbed Leaf optical properties reflected + emitted depend on anatomical leaf structure and biochemical leaf composition

4 Description of the PROSPECT model N identical layers IsIs Elementary layer: n : refraction index K : global absorption coefficient Surface effects Hemispheric fluxes Global absorption: Specific absorption coefficients Content in absorbing material reflectance  ( )  ( ) transmittance

5 Refractive index: n( ) n1n1 n2n2 11 11 22 SCATTERING Snell’s law

6 Specific absorption coefficient of constituent i: k i ( ) d ABSORPTION Beer law

7 N C ab C bp C w C dm PROSPECT  ( )  ( ) leaf structure parameter chlorophyll a+b concentration (  g.cm  2 ) brown pigment concentration (  g.cm  2 ) equivalent water thickness (cm) dry matter content (g.cm  2 ) N = 1.5, C ab = 50  g.cm  2, C dm = 0.005 g.cm  2 PROSPECT

8 PROSPECT INPUTS N - Number of layers C ab - Chlorophyll a+b content C bp - Brown pigment content C w - Equivalent water thickness C dm - Dry matter content n(λ) - Refractive index k i (λ) - Specific absorption coefficients of constituants  ( ) – leaf reflectance  ( ) – leaf transmittance PARAMETERS between 0.4 and 2.5 µm PROSPECT OUTPUTS

9 PROSPECT INPUTS N - Number of layers C ab - Chlorophyll a+b content C bp - Brown pigment content C w - Equivalent water thickness C dm - Dry matter content n(λ) - Refractive index k i (λ) - Specific absorption coefficients of constituants  ( ) – leaf reflectance  ( ) – leaf transmittance PARAMETERS between 0.4 and 2.5 µm PROSPECT OUTPUTS ε ( ) – leaf emissivity k w (λ) k dm (λ) between 2.5 and 18 µm

10 refractive index n(λ) ? PROSPECT INPUTS

11 specific absorption coefficient of water k w (λ) 0.4-2.5 µm PROSPECT INPUTS

12 * specific absorption coefficient of dry matter: k dm (λ) -> no info available at the moment -> to be obtained by inverting PROSPECT against leaf spectrum data (in particular from dry leaf) * idem for leaf layer refractive index n(λ) (inversion from fresh leaf spectra) * N, C w, C dm may be obtained from library, measurements or from PROSPECT inversion between 0.4 and 1.8 µm PROSPECT INPUTS

13 DETERMINATION OF PROSPECT INPUTS: the only easily available data that made it possible to determine PROSPECT inputs were found in the ASTER spectral library Solar domain Thermal infrared N, C w, C dm k dm (λ), n(λ)

14 Specific absorption coefficient of dry matter: k dm (λ)  inversion of PROSPECT against ‘ASTER’ dry spectra  result of inversion compared to cellulose and lignin spectra 0.4-2.5 µm some cellulose and lignin features but not always specific Lignin

15 Specific absorption coefficient of dry matter: k dm (λ)  comparison to water Difficult zone because of high absorption of both dry matter and H2O Low absorption zone Opposite behavior of H2O and dry matter

16 Determination of the refractive index : n(λ) inversion of wet spectra gave refrative index Lowest absorption zone

17 COMPARISON OF PROSPECT OUTPUTS / MEASUREMENTS Data from -ASTER spectral library -Salisbury and D’Aria 1992 -MODIS spectral library

18 Comparison of simulated reflectance to data from Salisbury and D’Aria 1992 senescent beech leaf

19 Comparison of simulated reflectance to data from the MODIS spectra library 3 dry grass spectra

20 Comparison of simulated reflectance to data from the MODIS spectra library various fresh leaves

21 Comparaison de simulations à des mesures

22 Sensitivity to leaf water content sensitivity to Cw from 0.0002 cm -1 to 0.0512 cm -1 (0.0002, 0.0008, 0.0032, 0.0128, 0.0512 cm -1 ) 0.0002 0.0512 High transmittance

23 Sensitivity to leaf water content sensitivity to Cw from 0.0002 cm -1 to 0.0512 cm -1 (0.0002, 0.0008, 0.0032, 0.0128, 0.0512 cm -1 )

24 Sensitivity to leaf water content sensitivity to Cw from 0.0002 cm -1 to 0.0512 cm -1 (0.0002, 0.0008, 0.0032, 0.0128, 0.0512 cm -1 ) 0.0512 0.0002 Emissivity lower than expected from reflectance

25 Sensitivity of 8-14 µm emissivity to leaf moisture fresh leaves and dry leaves don’t have the same internal structure (parameter N = 2 and 4)  different responses  average behaviour in situ ?

26 Sensitivity to leaf surface properties various components (silica, waxes…) and / or structure (hair, epidermis cell shape…) may affect leaf surface – radiation interactions  introduction of new components  use the radiation incident angle of the plate model (set to 59° usualy) 10° 90° sensitivity to incident angle from 10 to 90° by step of 10°

27 Conclusion Encouraging first results There is a lot of work still to do  acquisition of leaf data for calibrating and testing the model  analysis of the effects of the various components in order to discriminate generic effects and specific effects  investigation of leaf surface effects  investigation of leaf drying impact…  ….  implementation in canopy radiative transfer model for the analysis of land surface emissivity spectra acquired from TIR multispectral sensors

28 The end S. Knap & N. Knight, 2001, Flora, Harry N Abrams, 80 pages.


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