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4D modeling of canopy architecture for improved characterization of state and
functionning
F. Baret
INRA-CSE Avignon
2/16
Introduction
• The description of vegetation architecture is one of the main limiting factor in the estimation of canopy characteristics such as LAI
• Importance of the temporal dimension that drives the generation of canopy architecture and that offers regularities to be exploited
Turbid medium Geometric Explicit
3/16
Requirements
• Good dynamic description of canopy architecture• Low amount of parameters/variables (for better retrieval)• Fast computation of the radiative transfer
Objectives of the study
• Illustrate how canopy structure evolution could be generated• Present the corresponding variables and parameters used• Describe how to compute the radiative transfer• Conclude on the work to achieve
4/16
The context of high spatial and temporal resolution observations
• High spatial resolution: – Generally ‘pure’ pixels– object observed could be identified in terms of species
• High temporal resolution– Continuous monitoring to be exploited in the understanding of how the
architecture builds up (or destroys down!)
Case illustrated here: maize canopies with relatively simple and well known architecture
5/16
Modeling maize canopies architecture
Work derived from previous studies : M. Espana, B. Andrieu, M. Chelle, B. Koetz, N. Rochdi
• Describing the time course of individual leaves and stems• Based on a series of experiments• Semi-mechanistic models• Reduced number of variables• Reasonable level of details in canopy
architecture description
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-0.15
-0.1
-0.05
0
0.05
0.1
0.15
-80 -40 0 40 80
view zenith angle (°)
rela
tive
diffe
renc
e
(T1-T0)/T0 Red
(T1-T0)/T0 Infrared -0.15
-0.1
-0.05
0
0.05
0.1
0.15
-80 -40 0 40 80
view zenith angle (°)
rela
tive
diff
eren
ce
(T2-T0)/T0 Red(T2-T0)/T0 Infrared
T0 T1 T2
Level of canopy architecture details required for reflectance simulation
7/16
Leaf area time course
Time of leaf of order n:• Apparition : n*DTc• Disparition : n*DTc+DTs
Variables required:•N_max•S_max•To•DTc•DTs
DT
s
Leaf area
DT
s
Leaf area 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
11
1
1
1
1
1
1
1
1
1
1
1
1
1
2
2
2
2
2
2
2
2
2
22
2
2
2
2
2
2
relative leaf order
rela
tive
leaf
are
aL
eaf
area
Leaf order0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
11
1
1
1
1
1
1
1
1
1
1
1
1
1
2
2
2
2
2
2
2
2
2
22
2
2
2
2
2
2
relative leaf order
rela
tive
leaf
are
aL
eaf
area
Leaf order
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Other architecture characteristics
Canopy–Plant density–Distance between rows–Row azimuth
-1-0.5
00.5
1
-1
-0.5
0
0.5
10
0.5
1
1.5
2
2.5
3
Plant–Leaf insertion height–Leaf shape/curvature–Leaf azimuth–Leaf zenith
0 2 4 6 8 10 12 14 16 180
0.5
1
1.5
2
2.5
Leaf order
Leaf
inse
rtio
n he
ight
Leaf order
Lea
f in
sert
ion
hei
gh
t
9/16
Properties of the 4D maize model
• Limited number of variables/parameters:– N_max– S_max– To– DTc– DTs– H_max– Density– Leaf inclination
• Dynamics well described• Improvements
– Leaf curvature (easy)– Better senescence including keeping senescent leaves– Variability between plants (size, position, …)– Flowers/ears– Vertical gradients in chlorophyll
10/16
Regularities in Chlorophyll gradients
0
2
4
6
8
10
12
14
16
18
20
0 10 20 30 40 50 60 70
Chlorophyll content (µg/cm²)
Leaf
Ord
er
26-juin
23-juil
16-sept
0
2
4
6
8
10
12
14
16
18
20
0 20 40 60 80 100
Chlorophyll content (µg/cm²)
Le
af
Ord
er
14-juin
21-juin
28-juin
05-juil
12-juil
19-juil
26-juil
08-août
22-août
29-août
Distribution verticale du contenu en chlorophylle mesurée à partir de l’instrument SPAD502
1999 2001
2
max
2
maxmax 148.0611.2011.2)(
x
x
x
xCabxCab
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 10
0.2
0.4
0.6
0.8
1
1.2
1.4
relative leaf order
norm
aliz
ed c
hlor
ophy
ll co
nten
t (C
ab/C
abm
ax)
11/16
From canopy architecture … to reflectance
0
0.1
0.2
0.3
0.4
-90 -45 0 45 90
Zenith view angle (°)
Sing
le s
catt
erin
g R
efle
ctan
ce
SAIL, h=0.3SAIL, h=0.1SAIL, h=0.01PARCINOPYSAIL, h=0.0
Parcinopy
Multispectral version now available(M. Chelle, V. Rancier)
12/16
Decomposing radiative transfer
ss =assoo.so =fso =d+edd =c/(a.Rs+b.Rs)sd =bdo =g /(a.Rs+b.Rs)
n(level,way,direction,inter_sol,inter_veget)=number of photons (radiance)level: b=bottom; t=topway: - = downward; + = upwarddirection: s=sun direction; v=view direction;h=hemispheric
interaction order (inter_sol, inter_veget):0: no interaction1: 1 interaction only1: one or more interactions
Terms required
Rc=so+ssoo.Rs +((ss.Rs+sd.Rs).do+(sd+ss.Rs.dd).Rs.oo)/(1-Rs.*dd)
Black soilterm
Soil interaction term
4 fluxesapproximation
13/16
Vegetation contribution (so)
so = f(leaf,leaf,P(LAI,ALA,S,D,,sv))Parameters 'P' are spectral invariants
14/16
Approach
[LAI,ALA,S,D,]Distribution of input variables
Constructionof the 3D
architecture[sv]
Sun/viewconfiguration
PARCINOPY
RT components
[l, l]leaf reflectance
& Transmittance
Building a parametric model
Parametric modelP(LAI,ALA,S,D,,sv, l, l)
[s]Soil reflectance
Canopyreflectance
15/16
CONCLUSION• A more mechanistic/realistic approach is proposed
– Based on a ‘simple’ description of canopy architecture to use fewer variables
– No need for continuous description (discrete is enough)– Needs sensitivity analysis to evaluate the influence of the
variation of N_max, H_max, …– Needs full (or at least parametric for the spectral aspect)
parametric model to be implemented to compute the reflectance fields
– Needs coupling to canopy functioning models
16/16
Coupling between structure and function models
4D Architecture
Model
LAI
Reflectance
T
Stress (H2O, N)
Initialization
Work in progress for exploitation within an assimilation scheme, …