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4D modeling of canopy architecture for improved characterization of state and

functionning

F. Baret

INRA-CSE Avignon

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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

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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

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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

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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

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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

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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

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1

11

1

1

1

1

1

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1

1

1

1

1

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2

2

2

2

2

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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

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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

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Regularities in Chlorophyll gradients

0

2

4

6

8

10

12

14

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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)

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From canopy architecture … to reflectance

Parcinopy

Multispectral version now available(M. Chelle, V. Rancier)

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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

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Vegetation contribution (so)

so = f(leaf,leaf,P(LAI,ALA,S,D,,sv))Parameters 'P' are spectral invariants

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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

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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

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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, …