radiative transfer theory at optical wavelengths applied...

UCL DEPARTMENT OF GEOGRAPHYUCL DEPARTMENT OF GEOGRAPHY

GEOGG141/ GEOG3051Principles & Practice of Remote Sensing (PPRS)Radiative Transfer Theory at optical wavelengths applied to vegetation canopies

Notes adapted from Prof. P. Lewis [email protected]

Dr. Mathias (Mat) DisneyUCL GeographyOffice: 113, Pearson BuildingTel: 7679 0592Email: [email protected]://www2.geog.ucl.ac.uk/~mdisney/teaching/GEOGG141/GEOGG141.html

UCL DEPARTMENT OF GEOGRAPHY

Aim

• Introduce RT approach as basis to understanding optical and microwave vegetation response

• enable use of models• enable access to literature


Scope

• Introduction to background theory– RT theory– Wave propagation and polarisation– Useful tools for developing RT

• Building blocks of a canopy scattering model– canopy architecture– scattering properties of leaves– soil properties


ReadingNotes for this lecturehttp://www2.geog.ucl.ac.uk/~mdisney/teaching/GEOGG141/rt_theory/rt_notes1.pdfhttp://www2.geog.ucl.ac.uk/~mdisney/teaching/GEOGG141/papers/disney_et_al_monte_carlo.pdfBooksJensen, J. (2007) Remote Sensing: an Earth Resources Perspective, 2nd ed., Chapter 11 (355-408), 1st

ed chapter 10.Liang, S. (2004) Quantitative Remote Sensing of Land Surfaces, Wiley, Chapter 3 (76-142).Monteith, J. L. and Unsworth, M. H. (1990) Principles of Environmental Physics, 2nd ed., ch 5 & 6.Disney, M. I. (2016) Remote sensing of vegetation: potentials, limitations, developments andapplications. Springer Series: Advances In Photosynthesis and Respiration, Springer, Berlin, pp289-331.ISBN: 978-94-017-7290-7. DOI: 10.1007/978-94-017-7291-4.PapersDisney, M. I. et al. (2000) Monte Carlo ray tracing in optical canopy reflectance modelling. RemoteSensing Reviews,18:163-196. http://www.tandfonline.com/doi/abs/10.1080/02757250009532389Price, J. (1990), On the information content of soil reflectance spectra RSE, 33, 113-121Walthall, C. L. et al. (1985) Simple equation to approximate the bidirectional reflectance from vegetativecanopies and bare soil surfaces, Applied Optics, 24(3), 383-387.


ReadingMiscYuan et al. (2017) Reexamination and further development of two-stream canopy radiative transfermodels for global land modeling, http://onlinelibrary.wiley.com/doi/10.1002/2016MS000773/fullMonte Carlo

FLIGHT: P.R.J. North (1996) Three-dimensional forest light interaction model using a Monte Carlo method, IEEE Trans. Geosci. Remote Sens., 34 (4) (1996), pp. 946–956.Librat (UCL): P. Lewis (1999) The Botanical Plant Modelling System, Agronomie: Agriculture and Environment Vol.19, No.3-4, pp.185-210, https://librat.wikispaces.com/Raytran: Govaerts & Verstraete (1998) Raytran: a Monte Carlo ray-tracing model to compute light scattering in three-dimensional heterogeneous media, IEEE TGRS, 36, 493-505, DOI: 10.1109/36.662732CanopyNilson, T. and Kuusk, A. (1989) A canopy reflectance model for the homogeneous plant canopy and itsinversion, RSE, 27, 157-167.W. Verhoef (1984) Light scattering by leaf layers with application to canopy reflectance modeling: TheSAIL model, Remote Sensing of Environment, 16 (1984), pp. 125-141B. Pinty et al. (2011) Exploiting the MODIS albedos with the Two-stream Inversion Package (JRC-TIP):J. Geophys. Res., 116, D09105, doi:10.1029/2010JD015372.LeafJacquemoud. & Baret (1990) PROSPECT: A model of leaf optical properties spectra, RSE, 34, 75-91.Feret, J-B. et al. (2008) PROSPECT-4 and 5: Advances in the leaf optical properties model separatingphotosynthetic pigments, RSE, 112, 3030-3043.


Why build models?• Assist data interpretation

• calculate RS signal as fn. of biophysical variables

• Study sensitivity• to biophysical variables or system parameters

• Interpolation or Extrapolation• fill the gaps / extend observations

• Inversion• estimate biophysical parameters from RS

• Aid experimental design• plan experiments

• Benchmarking & cal/val (RAMI etc)


Radiative Transfer Theory

• Applicability– heuristic treatment

• consider energy balance across elemental volume– assume:

• no correlation between fields– addition of power not fields

• no diffraction/interference in RT– can be in scattering

– develop common (simple) case here


Radiative Transfer Theory

• Case considered:– horizontally infinite but vertically finite plane

parallel medium (air) embedded with infinitessimaloriented scattering objects at low density

– canopy lies over soil surface (lower boundary)– assume horizontal homogeneity

• applicable to many cases of vegetation• But…..?


Building blocks for a canopy model

• Require descriptions of:– canopy architecture– leaf scattering– soil scattering


Soil

H

z

Canopy

Canopy Architecture• 1-D: Functions of depth from the top of the canopy (z).


Canopy Architecture

• 1-D: Functions of depth from the top of the canopy (z).

1. Vertical leaf area density (m2/m3)2. the leaf normal orientation distribution function

(dimensionless).3. leaf size distribution (m)

( )zul


Canopy Architecture

• Leaf area / number density– (one-sided) m2 leaf per m3( )zu

l

( )dzzuL

Hz

z

l∫=

=

=0

LAI


Ωl

x

z

y

θl

φl

Inclination to vertical

azimuth

Leaf normal vector

Canopy Architecture

• Leaf Angle Distribution

( ) 12

≡ΩΩ∫ +lll dg

π


• Archetype Distributions:• planophile ¾

• erectophile ¾

• spherical ¾

• plagiophile ¾

• extremophile ¾

Leaf Angle Distribution

( ) lllg ϑϑ 2cos3=

( ) lllg ϑϑ 2sin

2

3

=

( ) 1=llg ϑ

( ) lllg ϑϑ 2sin8

15 2

=

( ) lllg ϑϑ 2cos7

15 2

=


• Archetype Distributions:

Leaf Angle Distribution

0.0

0.5

1.0

1.5

2.0

2.5

3.0

0 10 20 30 40 50 60 70 80 90

g_

l(th

eta

_l)

leaf zenith angle / degrees

spherical planophile erectophile

plagiophile extremophile


• RT theory: infinitesimal scatterers– without modifications (dealt with later)

• In optical, leaf size affects canopy scattering in retroreflection direction– ‘roughness’ term: ratio of leaf linear dimension to canopy

heightalso, leaf thickness effects on reflectance /transmittance

Leaf Dimension


Canopy element and soil spectral properties

• Scattering properties of leaves– scattering affected by:

• Leaf surface properties and internal structure; • leaf biochemistry; • leaf size (essentially thickness, for a given LAI).

Excellent review here:http://www.photobiology.info/Jacq_Ustin.html


Scattering properties of leaves

• Leaf surface properties and internal structure

Dicotyledon leaf structure

opticalSpecular

from surface

Smooth (waxy) surface- strong peak

hairs, spines- more diffused





opticalDiffused

from scattering at internal air-cell wall interfaces

Depends on total areaof cell wall interfaces

Depends on refractive index:varies: 1.5@400 nm

1.3@2500nm





optical

More complex structure (or thickness):- more scattering- lower transmittance- more diffuse



• Leaf biochemstry


Scattering properties of leaves• Leaf biochemstry

Feret, Jacquemoud et al. (2008) PROSPECT-4 and 5: Advances in the leaf optical properties model separating photosynthetic pigments, RSE, 112, 3030-3043.

UCL DEPARTMENT OF GEOGRAPHYScattering properties of leaves

• Leaf water

Feret, Jacquemoud et al. (2008) PROSPECT-4 and 5: Advances in the leaf optical properties model separating photosynthetic pigments, RSE, 112, 3030-3043.



• Leaf biochemstry– pigments: chlorophyll a and b, a-carotene, and

xanthophyll • absorb in blue (& red for chlorophyll)

– absorbed radiation converted into:• heat energy, flourescence or carbohydrates through

photosynthesis



• Leaf biochemstry– Leaf water is major consituent of leaf fresh weight,

• around 66% averaged over a large number of leaf types– other constituents ‘dry matter’

• cellulose, lignin, protein, starch and minerals– Absorptance constituents increases with concentration

• reducing leaf reflectance and transmittance at thesewavelengths.



• Optical Models– flowering plants: PROSPECT – a generalised

plate model

Figure from: http://teledetection.ipgp.jussieu.fr/opticleaf/models.htm & see for more detail on various approaches to leaf optical properties modelling

Jacquemoud. S. and Baret, F. (1990) PROSPECT: A model of leaf optical properties spectra, RSE, 34, 75-91.



• Optical Models– flowering plants: PROSPECT – extension of plate

model to N layers

http://teledetection.ipgp.jussieu.fr/opticleaf/models.htm



• leaf dimensions– optical

• increase leaf area for constant number of leaves -increase LAI

• increase leaf thickness - decrease transmittance(increase reflectance)


Scattering properties of soils

• Optical and microwave affected by:– soil moisture content

– Wetter soils are darker (optical); have lower dielectric(microwave)

– soil type/texture– soil surface roughness

– shadowing (optical)– coherent scattering (microwave)


soil moisture content• Optical

– effect essentially proportional across all wavelengths• enhanced in water absorption bands

UCL DEPARTMENT OF GEOGRAPHY soil texture/type

• Optical– relatively little variation in spectral

properties– Price (1990):

• PCA on large soil database - 99.6%of variation in 4 PCs

– Stoner & Baumgardner (1982)defined 5 main soil types:

• organic dominated• minimally altered• iron affected• organic dominated• iron dominated

Price, J. (1990), On the information content of soil reflectance spectra RSE, 33, 113-121.


Soil roughness effects

• Affects directional properties of reflectance (opticalparticularly)

• Simple models:– as only a boundary condition, can sometimes use simple

models• e.g. Lambertian• e.g. trigonometric (Walthall et al., 1985; Nilson and Kuusk 1990)

where θv,i are the view and illumination (sun) zenith angles; ϕ is relativeazimuth angle (ϕi - ϕv).

ρsoil = po θ2+θ 2v( )+ p1θ 2θ 2 cosφ + p3

UCL DEPARTMENT OF GEOGRAPHY Soil roughness effects

• Rough roughness:– optical surface scattering

• clods, rough ploughing– use Geometric Optics model (Cierniewski)– projections/shadowing from protrusions

UCL DEPARTMENT OF GEOGRAPHYSoil roughness effects

• Rough roughness:– optical surface scattering

• Note backscatter reflectance peak (‘hotspot’)• minimal shadowing• backscatter peak width increases with increasing roughness

UCL DEPARTMENT OF GEOGRAPHYSoil roughness effects

• Rough roughness:– volumetric scattering

• consider scattering from ‘body’ of soil– particulate medium– use RT theory (Hapke - optical)– modified for surface effects (at different scales of roughness)


Summary

• Introduction– Examined rationale for modelling– discussion of RT theory– Scattering from leaves

• Canopy model building blocks– canopy architecture: area/number, angle, size– leaf scattering: spectral & structural– soil scattering: roughness, type, water


RAMI: Radiative Transfer Model Intercomparison

• Use detailed 3D models to provide– Known solution– Benchmark other, simpler models– Test new algorithms– Provide ‘test’ datasets for calibration and validation of

EO products• RAMI – 4 phases since ~2000

• Pinty, Widlowski, Disney, Gobron et al multiple papers• Multiple models, ISO model checking


RAMI: Radiative Transfer Model Intercomparison

• http://rami-benchmark.jrc.ec.europa.eu/HTML/

radiative transfer theory at optical wavelengths applied...

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