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Three factors determine canopy
reflectance
1. Spectral scattering/absorbing properties of canopy
components. (leaves, stems, flowers, fruit, soil, etc.)
2. Canopy architecture. (above-ground biomass; leaf area index;
arrangement of foliage in x,y,z,θ,φ space – for example, are all leaves
vertical and located in one layer – or perhaps they are arranged in
space like the area on a sphere; etc.)
- Directions of illumination and view. (Is the sun the only
significant source – or does aerosol- or Rayleigh-scattered light
provide hemispherical illumination; is direction of view toward the hot
spot or nadir or …)
Three factors determine canopy
reflectance
- Canopy architecture. ( above-ground biomass ;
leaf area index ; arrangement of foliage in x,y,z,θ,φ space –
for example, are all leaves vertical and located in one layer
- or perhaps they are arranged in space like the area on a
sphere; etc.)
Chlorophyll and Carbon Assimilation
Amount of chlorophyll in canopy
Potential carbonassimilation bycanopy
(Concentration x phytomass )
“The big picture”
Chlorophyll Concentrations
chlorophyll concentration
Red or blue wavelengthradiance, reflectance
Wavelength, nm
reflectance(%)
very high leaf area
very low leaf area
sunlit soil
First, notice that Canopy Reflectance varies with Leaf
Area…
On moderately bright soil:
- In visible canopy reflectance decreases as leaf area per unit ground area (LAI) increases
- In NIR canopy reflectance increases as LAI increases
Question: How to calculate LAI and FPAR,
fraction of PAR intercepted by canopy?
Conclusion: LAI is a function of reflectance and vice-versa.
Case Study 5: Red and NIR Reflectance by
Canopy Density
NIR reflectance(%)
Total leaf area*meter of canopy
2 )
0 10000 20000 30000 40000 50000 60000
NIR reflectance(%)
red reflectance (%)
Total leaf area*meter of canopy
-1 (cm2)
0 10000 20000 30000 40000 50000 60000
red reflectance (%)
Correlation coefficient between canopy
reflectance and canopy leaf area
is negative in visible and positive in NIR
wavelength
Correlation Coefficient
-1.
Correlation positive
Correlation negative
Correlation = 0.0 at
approximately λ = 0.71μm
wavelength
reflectance(%)
very high leaf area
very low leaf area
sunlit soil
But notice…
Let’s model this effect in the visible using
a single scattering model…
- Assume spherical leaf angle distribution.
(Leaf area distributed like area on a sphere)
- Decrease of sunlight irradiance with depth z into
canopy follows Beers absorption law:
where LAD is leaf area density (the leaf area per
cubic meter of the canopy), I is the irradiance at
the top of the canopy and c1 is a ‘fudge factor.’
- Assume leaves are Lambertian with reflectance ρ.
- The radiance of a ∆z layer is
)
cos
1 * *
( ) exp(
i
c LAD z
Irradiancez I
θ
= −
]* [ cos
[
(,,)[ ]*[
r
zLAD
radiancezrrleafareainz
θ
θ φ
∆
∆ = ∆
Estimating the size of the absorption well
wavelength
400 600 800 1000 1200
reflectance(%)
density 1
density 2
density 3
density 4
density 5
density 6
sunlit soil
What are Vegetation Indices?
Vegetation Indices
Vegetation indices (VI) are combinations of spectral
measurements in different wavelengths as recorded by a
radiometric sensor. They aid in the analysis of multispectral
image information by shrinking multidimensional data into a
single value. Huete (1994) defined vegetation indices as:
“ dimensonless, radiometric measures usually involving a
ratio and/or linear combination of the red and near-infrared
(NIR) portions of the spectrum. VI’ s may be computed
from digital counts, at satellite radiances, apparent
reflectances, land-leaving radiances, or surface
reflectances and require no additional ancillary
information other than the measurements
themselves…What VI s specifically measure remains
unclear. They serve as indicators of relative growth and/or
vigor of green vegetation, and are diagnostic of various
biophysical vegetation parameters”.
Vegetation Indices
Vegetation indices (VI’s) can be broken up
into two basic categories:
Ratio based indices – VI’s based on the ratio of two or
more radiance, reflectance, or DN values (or linear
combinations thereof).
Difference indices – VI’s based on the difference
between the spectral response of vegetation and the
soil background.
Common Ratio Indices
Simple Ratio Index (SR) = NIR/R
Normalized Difference Vegetation Index (NDVI) =
NIR R
NIR R
−
Sensor
Shadow Sunlit Background
Red flux radiation
NIR flux radiation
Composite Canopy Reflectance
Leaf area Density
Composite Canopy Reflectance
0% veg. Cover; LAI = 0
100% veg. Cover; 1
leaf layer; LAI =
50% veg. Cover; 2 leaf
layers; LAI = 1
pixel
33% veg. cover; 3
leaf layers; LAI = 1
Are the reflectances of these 3 pixels the same?
1 m
of leaf area
Composite Canopy Reflectance
Vegetation Index
LAI, LAD
This region of the curve is dominated by a
change in percent vegetation cover
In this region, there is complete
vegetation cover and differences are
due to increasing canopy density-
Additive Reflectance (multiple
scattering)
100% vegetation cover
Recent VIs to remember...
- There are a Gazillion VIs in the literature...
- I’ve proposed one...ignore it - and most others in the literature.
Right now, the important VIs to know are:
- SAVI, Soil Adjusted VI
- ARVI, Atmospherically Resistant VI
- SARVI, Soil & Atmospherically Resistant VI
- EVI, Enhanced VI
