[vegetation and remote sensing] vegetation
TRANSCRIPT
-
7/29/2019 [Vegetation and Remote Sensing] Vegetation
1/10
Botanical Institute, BB209 H2002
Vegetation
Vegetation and Remote Sensing
Botanical Institute, BB209 - H2002
Vegetation
Leaf-radiation interference
Factors affecting reflectance Spectral signature
Vegetation indices
Leaf Area Index
Global vegetation monitoring
Botanical Institute, BB209 -H2002
Vegetation and RS
Inter- and intra-annual global vegetation monitoring on a periodic basis
Global biogeochemical, climate and hydrological modeling
Net primary production and carbon balance
Anthropogenic and climate change detection
Agricultural activities (plant stress, harvest yields, precisionagriculture)
Famine early warning systems
Drought studies
Landscape disturbance (volcanic, fire scars, etc.)
Land cover and land cover change products
Biophysical estimates of vegetation parameters (% cover, LAI,fAPAR)
Public health issues (rift valley fever, mosquito producing rice fields)
Ability to map the presence, amount, type, condition etc. ofvegetation
Botanical Institute, BB209 - H2002
The plant leaf
Vegetation interferes with
sunlight in several ways
in areas of high vegetation
density the leaf is the most
characteristic and influential
component of this
interference
highly specialised structure
adapted to photosynthetic
activity
Botanical Institute, BB209 -H2002
The Plant Leaf
four different layers upper and lower epidermis
stomatalcells, secures gasexchange (CO2, O2)
largely transparent to incidentPhotosynthetically ActiveRadiation (PAR; 0.4-0.7m).
a layer of elongatedparenchymatic cells
chloroplasts do the solar energyabsorption
a layer of spongy mesophylliccells
large air filled volumespredominate between cells
hydrated mesophyll cellscontribute water tophotosynthesis
Schematic cross section of typicalcitrus
leaf (after Harris1987)
Botanical Institute, BB209 - H2002
Leaf reflectance
The function (photosynthesis)
and structure of the leaf
generate a special spectral
signature
Chlorophyll absorption
Leaf reflectance
-
7/29/2019 [Vegetation and Remote Sensing] Vegetation
2/10
Botanical Institute, BB209 -H2002
Leaf reflectance
Three zones in leaf reflectance spectrum
1. PAR, high absorption (sub-regions a-c)
very high leaf absorption (pigments of chlorophyll a and b &
caretenoids in the chloroplasts)
Red wavelengths (0,62-0,70 m) strongest contrast to soil reflection
due to high chlorophyll absorption.
high scatter of the PAR give pigments multiple chances to absorb the active
wavelengths
High scatter is due mainly to
differences in the refractive index
between the air spaces(1.0),
hydrated cells (1.4), and the irregular
facets of the exteriors of cells
Botanical Institute, BB209 - H2002
Leaf reflectance
2. near-IR (0,74-1,1 m)
reflectance very high/ absorption minimal
scattering amplifies the spectral reflectance, especially for dense
canopies.
0,79-0,90 m avoids atmospheric water vapour absorption
most appropriate for monitoring vegetation
reflectance can reach fifty per cent on the IR plateau
level of IR plateau depends on the internal structure of the leaf.
The level increases with the number of layers of cells, their size
and the orientation of cell walls (Guyot and Riom 1988)
3. mid-IR ( 1.3-2.5 m)
high absorption due to the liquid water of the mesophyllic cells.
Botanical Institute, BB209 -H2002
Leaf reflectance
soil reflectance
visible and near-IR:increases steadily
over wavelengths;
mid-IR:oscillates like, but above
reflectance from vegetation.
best regions to obtain vegetation
information separately from background
information
Red (LOW) and the near-IR(HIGH)
(0,79-0,90m)
closely connected to chlorophyll density
and green leaf density respectively
(Tucker and Sellers 1986).
RED NIR
Botanical Institute, BB209 - H2002
RGB color composite
A multi-spectral,optical satellite imageis usually displayed asa false colourcomposite of threelayers
Blue layer: greenchannel
green layer: redchannel
red layer: IRchannel
this combination ofhigh values in the redlayer and low valuesin the green layergives vegetation a redcolour.
SPOT XS, july 1986
Botanical Institute, BB209 -H2002
Vegetation indices
quantitative measurements indicating vigour ofvegetation
Better sensitivity than ind. Spectral bands for detectionof biomass
Ideal VI: the index should be particularly sensitive to
vegetative covers, insensitive to soil brightness,insensitive to soil color, little affected by atmosphericeffects, environmental effects and solar illuminationgeometry and sensor viewing conditions (Jackson etal., 1983)
I.e. Other factors than leaf reflectance are ofimportance!
Biological domain/internal
Physical domain/external
RED
NIR
SAVI
Botanical Institute, BB209 - H2002
Biological domain
several other parameters can changevegetation canopy reflectance even ifthe leaf hemispherical reflectanceremains constant, or vice versa(Colwell, 1974)
Optical properties of vegetation Indivdual level
Species level
Physiognomy and phenology
Temporal changes
Water content, age, mineral deficiency,parasitic attacks,
Vegetation parameter
VI
Vegetation parameter
VI
-
7/29/2019 [Vegetation and Remote Sensing] Vegetation
3/10
Botanical Institute, BB209 -H2002
Vegetation canopy reflectance
Leaf vs. Canopy
Layers of leaves; size, orientation, shape,
coverage of ground surface shadowing
within layers and canopy Shadowing reduces reflectance, reduction
relatively lower in NIR than RED
Related to transmittance!
1. Leaf hemispherical transmittance:
correlated to hemispherical reflectance of
leaves
Red is positively correlated
IR is negatively correlated
red
NIR
trans
Refl
Botanical Institute, BB209 - H2002
Vegetation canopy reflectance
2. Leaf area and orientation
A change
smaller leaves or
more vertical orientation of the leaves
might increase Red and decrease near-IR reflectance,
making vegetation approach the soil reflectance curve.
These parameters are important at the individual level.
Botanical Institute, BB209 -H2002
Vegetation canopy reflectance
3. Hemispherical reflectance and transmittance of
supporting structures (stalk, trunks, limbs,
petioles):
Guyot and Riom (1988) have studied the reflectance
of bark on spruce. The reflectance increases
progressively from visible to mid-IR and resembles
soil reflectance. When the density (of needles) is low,
the effect of bark reflectance is particularly sensitive
in the near-IR and mid-IR (Guyot and Riom 1988).
Botanical Institute, BB209 - H2002
Vegetation canopy reflectance
The red shift
Maturation induced change
of the chlorophyll absorption
edge toward longer
wavelengths
Red transition zone
Complex causes: conc.
of chlorophyll change in
molecular structure
absorption bands added
Botanical Institute, BB209 -H2002
Vegetation canopy reflectance
Senescence
Deterioration of cell walls in the mesophyll tissuedecline in NIR reflectance
Accompanying increase in visible reflectance decline in
abundance and effectiveness of chlorophyll
Botanical Institute, BB209 - H2002
Physical domain/external
Atmosphere Uniform surface and atmosphere
without clouds
NIR darkening of bright surface
Scattering and water vapor absorption(20%)
RED brightening dark surface
Added path radiance
Same effect as turbidity!
Critical surface reflectance (radiancevs. Optical thickness)
Aerosol scattering (0.04-0.20 unitdecrease in NDVI), water vapor (0.04-0.08) and Rayleigh scattering (0.02-0.04)
-
7/29/2019 [Vegetation and Remote Sensing] Vegetation
4/10
Botanical Institute, BB209 -H2002
Background Effective background reflectance:
Its importance increases as coverage becomes thinner; aridity, agriculture,LAI below 2
Difficult to extract vegetation information for coverages below 30%
(hutchinson, 1989) resolution! Brightness
shadowing, texture, material, wetness
Soi l line
Color
Width of soil line
The effect is local
Botanical Institute, BB209 - H2002
Angular effects
Three angles are important for the registered reflectance
effects are inter-related
solar zenith angle: angle between the direction of incidentsunlight and the vertical line from nadir to zenith
look angle: angle between the sensor and the vertical line fromnadir to zenith
azimuth angle: anglebetweenthe planes definedby solar zenith and lookangle
Botanical Institute, BB209 -H2002
Angular effects
The solar zenith angle changes daily and
seasonally.
point of insensitivity:
When vegetation coverage rises beyond a certain
threshold, the reflectance is saturated and thus
insensitive to a further increase in coverage
varies with the solar zenith- and look-angles
look-angle 0 (nadir viewing) & increasing zenith
angle: the point of insensitivity is at a lesser
coverage (the same reflectance is registered for
vegetation coverages that it was possible to
distinguish with a smaller zenith angle).
The same trend is seen if the solar zenith angle is
kept constant and the look angle increases
a
b
Botanical Institute, BB209 - H2002
Angular effects
The sensitivity of the IR band isgreater than that of the Red band.
effects of the azimuth and look-angles has to be consideredtogether:
azimuth is 90 (b), a change in look-angle gives a symmetrical spectralresponse around the nadir axis.However, the symmetry is differentfor visible and IR wavelengths.
azimuth is 180 (c), looking up-sun,gives a lower reflectance than whenlooking down-sun, i.e. when theazimuth is 0 (a) (Colwell 1974,Guyot andRiom1988)
a
b
c
Botanical Institute, BB209 -H2002
Vegetation canopy reflectance
pixel size
High spatial resolution better reflects the
diversity of the environment monitored, while
increasing the pixel size better catches thehomogeneity of the environment. Observed
variability is reduced as the pixel size increases.
Botanical Institute, BB209 - H2002
Spectral signature
Greeness and openess of vegetation high VI
Internal variation hetereogenity of veg type
Age, height, density etc.
-
7/29/2019 [Vegetation and Remote Sensing] Vegetation
5/10
Botanical Institute, BB209 - H2002 Botanical Institute, BB209 - H2002
Vegetation indices, VI
VI highlight vegetation
Integrative functions ofcanopy, structural (%cover, LAI, LAD) and
physiological (pigments,photosynthesis) parameters
Red IR scatterdiagram tasseled cap; high IRand low Red
VI = mathematicalcombination of these
bandsThe tasseled cap of the IR-red data-
space (data are extracted from a
mid-summer MSS data-set from
Western Norway)
Water
Vegetation
Soil line
Botanical Institute, BB209 -H2002
R-NIR Feature Space
Sudan
MSS-1
09/29/72
path 183
row 48
Botanical Institute, BB209 - H2002
R-NIR Feature Space
Egypt
MSS-2
04/14/79
path 186
row 43
Botanical Institute, BB209 -H2002
Vegetation indices
Agricultural crops observed
throughout growing seasonWide range of land surface cover
types, Landsat TM
High vegetation cover, lowest red and highest IR; RED sensitivity
Botanical Institute, BB209 - H2002
Vegetation indices
Several VI exists
Amplify vegetation by normalising data/
topographic effects
Amount of data reduced Categorisation different schemes
Difference indices
Ratio indices
Orthogonal indices
Complex combinations
First generation (Bannari et al. 1995)
second generation (Bannari et al. 1995)
-
7/29/2019 [Vegetation and Remote Sensing] Vegetation
6/10
Botanical Institute, BB209 -H2002
Vegetation indices
Difference indices = IR Red;vegetation high positive values
Ratio indices = IR/Red Variations on this simple ratio
Adding constants, squaring, squareroot etc. to normalise (positivevalues, 0-1)
All produce lines radiating outfrom an origo; equal value on thisline
+ Normalisation good (varyingsoil and irradiance conditions)
- overestimation over dark soil
Botanical Institute, BB209 - H2002
Vegetation indices
Orthogonal indices
Soil line; soil/background
plots on single line Vegetation emerges
orthogonally
Axis of variation by
Linear regression
PCA
Gram-Schmidt
orthogonalisation
1. Axis = soil line
(IR=aR+b)
2. Axis = vegetation cover
Botanical Institute, BB209 -H2002
First generation VI
Botanical Institute, BB209 - H2002
First generation VI
Botanical Institute, BB209 -H2002
Vegetation indices
Linear combinations
Not considering - Exterior factorsor soil-vegetation interactions
Designed for specific sensors and applications
Interpretation distinct differences between ratio and orthogonal
indices
BUT small differences seen betweenstudies applying one or another
VI!
Perry and Lautenschlager (1984)
Discussing 48 diff. VIs
functional equivalence
Botanical Institute, BB209 - H2002
IR
RVi=
Vegetation indices
IR
Red
-
7/29/2019 [Vegetation and Remote Sensing] Vegetation
7/10
Botanical Institute, BB209 -H2002
Second generation VI
Based on knowledge of physical phenomena
Interaction between EM radiation, atmosphere,
vegetative cover and soil background
Generally based on reflectance values, corrected
for sensor calibration and atmospheric effects
NDVI most widely used, reference for
evaluating new indices
Botanical Institute, BB209 - H2002
Second generation VI
Botanical Institute, BB209 -H2002
PVI
-50,00
0,00
50,00
100,00
150,00
200,00
250,00
300,00
350,00
400,00
0 50 100 150 200 250 300
Serie1
Soil line y=ax+b
A and b from regression
non-vegetation file/interpretation of scatterdiagram
Botanical Institute, BB209 - H2002
PVI - model
PVI=(NIR-aR-b)/
(SQRT(a**2+1))
Botanical Institute, BB209 -H2002
PVI
Botanical Institute, BB209 - H2002
Vegetation isolines
Pairs of RED and NIR
representing equal amounts of a particular vegetation parameter
changing the optical properties of the background
fixed Leaf Area Index (LAI ) and Leaf Angle Distribution (LAD)
constant external conditions Represent the true behavior of a constant vegetation
condition against a wide range of canopy background
conditions
Vegetation Index invariant to background:
vegetation isolines = vegetation index isolines!
-
7/29/2019 [Vegetation and Remote Sensing] Vegetation
8/10
Botanical Institute, BB209 -H2002
Vegetation isolines
Plot of the vegetation
points with the SAIL
model (marks) for variousLAI and soil reflectance
and the NDVI isolines
(dotted lines). (Huete el al,
1999)
Botanical Institute, BB209 - H2002
Vegetation isolines
Vegetation isolineequations
Simulations (SAIL) canhelp understanding optical
properties of vegetationand to develop better/moreresistant VIs
Background/soilreflectance (red) 0.05, 0.2and 0.35: increasing
brightness
Vegetation isolines do notinclude soil reflectance!
NDVI SAVI
Botanical Institute, BB209 -H2002
Leaf Area Index, LAI
Amount of foliage per unit ground surface area / one halfthe total green leaf area per unit ground area (1.28 2) Optical instruments response
A driving biophysical variable
Input to models; hydrological, ecological, climate
Varies with plant/tree species, mean annual temperature,length of season, water supply and stock age
Range 0 16, maximum reached in evergreen forests atwestern coast of USA
Quantification directly/indirectly in field
Indirectly relationship to surface reflectance and therefore SVI
Botanical Institute, BB209 - H2002
Indirect LAI estimation
Deterministic or stochastic canopy radiation models Homogenous canopies
Empirical spectral vegetation indices (SVI) RED, NIR, MIR/SWIR (TM3, 4, 5)
RED and MIR; strong inverse curvilinear relationship (absorption -pigments and water content)
Botanical Institute, BB209 -H2002
NIR low LAI inverserelationship, high LAI
positive relationship (veg.Cover + shadowing)
SVI LAI relation Understory and background
influences
Saturation of SVI at LAI 3-5:vegetation with LAI > 3-5occupy 1/3 of terrestrial landsurface!
Indirect LAI estimation
Botanical Institute, BB209 - H2002
LAI - SVI
Several SVIs related to LAI
Red/NIR combinations (NDVI, SR, SAVI)
Turner et al. 1999
Atmospheric and topographic correction
Optimal relation depends on vegetation type and density
Huete et al. 1997
NDVI faPAR
SARVI LAI
Brown et al. Xxxx
SAVI < SR
Chen and Cihlar, 1996
NDVI ~ SR background problems
-
7/29/2019 [Vegetation and Remote Sensing] Vegetation
9/10
Botanical Institute, BB209 -H2002
LAI SVI
SVIs including MIR band
Similar reflectance across backgrounds
Larger sensitivity to LAI
Including MIR performs better than equivalent SVIs without
MIR (Boyd et al. 2000, Brown et al. 2000, Nemani et al. 1993,
Spanner et al. 1990)
Texture stronger relation!
Botanical Institute, BB209 - H2002
LAI
Botanical Institute, BB209 -H2002
Global vegetation monitoring
AVHRR (NASA) daily global coverage
Global Area Coverage
4km resolution
transmitted daily
Local Area Coverage
Full resolution 1,1km at nadir
Selectedregions (receiving station)
Global Vegetation Index, since 1982!
From GAC, 7 days composites of highest values (clouds, atmosphere)
NDVI, 15 km resolution
Botanical Institute, BB209 - H2002
Global vegetation monitoring
AVHRR applications
Observe major ecological zones and seasonal changes
Crop phenology and agricultural practices in the Nile Delta (tucker
et al. 1984)
Desertification
Long term trends (onset of spring etc.)
Botanical Institute, BB209 -H2002
Global vegetation monitoring
MODIS
The Moderate Resolution Imaging Spectroradiometer instrument
Terra platform December 18th, 1999
(wide spectral range, moderate spatial reso lution (250m 1km)
and near daily global coverage
The second MODIS is planned for launch o n the Aqua platform in April 2002
Botanical Institute, BB209 - H2002
MODIS VI
How are global ecosystems changing?
What changes are occurring in global land cover andland use, and what are their causes?
How do ecosystems respond to and affect globalenvironmental change and the carbon cycle?
Products: NDVI, Normalized Difference VI. Continuity index
that will extend 20 years of AVHRR
EVI, Enhanced Vegetation index takes advantages of MODIS radiometric characteristics,
corrected surface reflectance.
expected to give improved sensitivity in high biomass regionsand improved vegetation monitoring through a de-coupling ofthe canopy background signal and a reduction in atmosphereinfluences.
-
7/29/2019 [Vegetation and Remote Sensing] Vegetation
10/10
Botanical Institute, BB209 -H2002
April 2001
September 2000
December 2000
0 63
MODIS Leaf Area Index
LAI is defined as the one sided green leaf area per unit
ground area in broadleaf canopies and as the projected
needle leaf area in coniferous canopies.
Botanical Institute, BB209 - H2002
April 2001
September 2000
December 2000
0 0.90.5
MODIS faPAR
faPAR is defined as the fraction of incident photosynthetically
active radiation (0.4 - 0.7 m) absorbed by the vegetation
canopy.