Transcript Adaptation of the leaf optical property model PROSPECT to thermal infrared

Adaptation of the leaf optical
property model PROSPECT to
thermal infrared
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
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
Leaf optical properties
depend on anatomical leaf structure and
biochemical leaf composition
reflected + emitted
absorbed
transmitted + emitted
Description of the PROSPECT model
Is
Surface effects
reflectance
()
Elementary layer:
n: refraction index
K: global absorption coefficient
N
identical
layers
Hemispheric fluxes
Global absorption:
K kiCi
i
Specific
absorption
coefficients
Content in
absorbing
material
()
transmittance
SCATTERING
Refractive index: n()
1
1
n1
n2
2
n1  sin 1  n2  sin 2
Snell’s law
ABSORPTION
Specific absorption coefficient of constituent i: ki()
k      ki     Ci
d
     exp  k     d 
Beer law
PROSPECT
N
Cab
Cbp
Cw
Cdm
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, Cab = 50 g.cm2, Cdm = 0.005 g.cm2
PROSPECT
()
()
PROSPECT INPUTS
N - Number of layers
Cab - Chlorophyll a+b content
Cbp - Brown pigment content
Cw - Equivalent water thickness
Cdm - Dry matter content
PARAMETERS
n(λ) - Refractive index
ki(λ) - Specific absorption
coefficients of constituants
PROSPECT OUTPUTS
() – leaf reflectance
() – leaf transmittance
between 0.4 and 2.5 µm
PROSPECT INPUTS
N - Number of layers
Cab - Chlorophyll a+b content
Cbp - Brown pigment content
Cw - Equivalent water thickness
Cdm - Dry matter content
PARAMETERS
n(λ) - Refractive index
ki(λ) - Specific absorption
(λ) kdm(λ)
coefficients ofkwconstituants
between
between0.4
2.5and
and2.5
18 µm
µm
PROSPECT OUTPUTS
() – leaf reflectance
() – leaf transmittance
ε () – leaf emissivity
PROSPECT INPUTS
refractive index n(λ) ?
PROSPECT INPUTS
specific absorption coefficient of water kw(λ)
0.4-2.5 µm
PROSPECT INPUTS
* specific absorption coefficient of dry matter: kdm(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, Cw, Cdm may be obtained from library, measurements or
from PROSPECT inversion between 0.4 and 1.8 µm
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
N, Cw, Cdm
Thermal infrared
kdm(λ), n(λ)
Specific absorption coefficient of dry matter: kdm(λ)
 inversion of PROSPECT against ‘ASTER’ dry spectra
 result of inversion compared to cellulose and lignin spectra
some cellulose and
lignin features
Lignin
but not always specific
0.4-2.5 µm
Specific absorption coefficient of dry matter: kdm(λ)
 comparison to water
Opposite behavior of H2O and dry matter
Difficult zone because
of high absorption of both
dry matter and H2O
Low absorption zone
Determination of the refractive index : n(λ)
inversion of wet spectra gave refrative index
Lowest absorption
zone
COMPARISON OF PROSPECT OUTPUTS / MEASUREMENTS
Data from
-ASTER spectral library
-Salisbury and D’Aria 1992
-MODIS spectral library
Comparison of simulated reflectance to data from
Salisbury and D’Aria 1992
senescent beech leaf
Comparison of simulated reflectance to data from the
MODIS spectra library
3 dry grass spectra
Comparison of simulated reflectance to data from the
MODIS spectra library
various fresh leaves
Comparaison de simulations à des mesures
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
High transmittance
0.0512
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)
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)
Emissivity lower
than expected from
reflectance
0.0512
0.0002
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 ?
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)
sensitivity to incident angle from 10
to 90° by step of 10°
10°
90°
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
The end
S. Knap & N. Knight, 2001, Flora,
Harry N Abrams, 80 pages.