UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk Radiative Transfer Theory at Optical wavelengths applied to vegetation canopies: part 1 UoL MSc Remote Sensing Dr Lewis plewis@geog.ucl.ac.uk
Aim of this section Introduce RT approach as basis to understanding optical and microwave vegetation response enable use of models enable access to literature
Scope of this section 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
Associated practical and reading Course notes for this lecture Reading list
Why build models? Assist data interpretation Study sensitivity 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
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 infinitessimal oriented scattering objects at low density canopy lies over soil surface (lower boundary) assume horizontal homogeneity applicable to many cases of vegetation
Building blocks for a canopy model Require descriptions of: canopy architecture leaf scattering soil scattering
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) the leaf normal orientation distribution function (dimensionless). 3. leaf size distribution (m)
Canopy Architecture Leaf area / number density LAI (one-sided) m2 leaf per m3 LAI
Canopy Architecture Leaf Angle Distribution
Leaf Angle Distribution Archetype Distributions: · planophile · erectophile · spherical · plagiophile · extremophile
Leaf Angle Distribution Archetype Distributions:
Leaf Dimension RT theory: infinitessimal 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 height also, leaf thickness effects on reflectance /transmittance
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).
Scattering properties of leaves Leaf surface properties and internal structure optical Specular from surface Smooth (waxy) surface - strong peak hairs, spines - more diffused
Scattering properties of leaves Leaf surface properties and internal structure optical Diffused from scattering at internal air-cell wall interfaces Depends on refractive index: varies: 1.5@400 nm 1.3@2500nm Depends on total area of cell wall interfaces
Scattering properties of leaves Leaf surface properties and internal structure optical More complex structure (or thickness): - more scattering - lower transmittance - more diffuse
Scattering properties of leaves Leaf biochemstry
Scattering properties of leaves Leaf biochemstry
Scattering properties of leaves Leaf biochemstry
Scattering properties of leaves Leaf biochemstry
Scattering properties of leaves Leaf water
Scattering properties of leaves 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
Scattering properties of leaves 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 these wavelengths.
Scattering properties of leaves Optical Models flowering plants: PROSPECT
Scattering properties of leaves Optical Models flowering plants: PROSPECT
Scattering properties of leaves 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 soil type/texture soil surface roughness.
soil moisture content Optical effect essentially proportional across all wavelengths enhanced in water absorption bands
soil texture/type Optical relatively little variation in spectral properties Price (1985): 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 iron dominated
Soil roughness effects Simple models: as only a boundary condition, can sometimes use simple models e.g. Lambertian e.g. trigonometric (Walthall et al., 1985)
Soil roughness effects Rough roughness: optical surface scattering clods, rough ploughing use Geometric Optics model (Cierniewski) projections/shadowing from protrusions
Soil roughness effects Rough roughness: optical surface scattering Note backscatter reflectance peak (‘hotspot’) minimal shadowing backscatter peak width increases with increasing roughness
Soil 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 Canopy model building blocks 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