VEGEMIX - hu-berlin.de
Transcript of VEGEMIX - hu-berlin.de
28/09/2012
VEGEMIX
HU Berlin, 27.09.2012
TEMPORAL HYPERSPECTRAL UNMIXING FOR VEGETATION MONITORING
Ben Somers
3rd EnMAP Summer School
28/09/2012 2 © 2011, VITO NV
Ben Somers
M.Sc. Nature Conservation and Forestry (bio-science engineer)
PhD student & Post-doc researcher KULeuven(2006-2010)
PhD in remote sensing: “Hyperspectral unmixing for plant production system monitoring”
Research fellow @ VITO, Flemish Institute for Technological Research
Research Interests
design of processing tools for hyperspectral remote sensing
specific focus on spectral mixture analysis
application in precision farming and (forest) ecology
28/09/2012 3 © 2011, VITO NV
VITO, Flemish Institute for Technological Research
Autonomous public research company
“GREEN TECHNOLOGY” Technological solutions
For industrial applications & government policy
800 staff in eight different research groups – ENERGY – ENVIRONMENT – INDUSTRY
Remote Sensing group (TAP)
80 staff (about 40 researchers)
TECHNOLOGY–GEODATA image processing centre – APPLICATIONS
28/09/2012 4 © 2011, VITO NV
VITO’s Remote Sensing Applications Unit Legend
Not classified
Water
Shadow
No Vegetation (inside the dike)
Vegetation (inside the dike)
Paved (outside the dike)
Bare ground (outside the dike)
Mud flat Dry sand Wet sand Water saturated sediment Wet silty sand MFB low concentration MFB moderate concentration MFB high concentration
Brackish water vegetation Aster tripolium Elymus athericus Phragmites australis Scirpus maritimus Spartina townsendii Brackisch grassland
Sweet water vegetation Scirpus maritimus Pionier Brushwood Scrub Forest Phragmites australis
Bank vegetation Fallopia japonica Bank grassland Urtica dioica Rubus fruticosus
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VEGEMIX
Outline
3rd EnMAP Summer School HU Berlin, 27.09.2012
Satelite imagery & vegetation dynamics monitoring?
Mixed vegetation systems?
RS & mixed vegetation?
Multi-temporal hyperspectral mixture analysis?
Spectral Mixture Analysis?
Endmember Variability?
Temporal Unmixing?
Application – multi-temporal unmixing step-by-step
28/09/2012 6 © 2011, VITO NV
satellite Imagery & vegetation dynamics monitoring?
spatial & temporal dynamics
in the condition of vegetation
3rd EnMAP Summer School HU Berlin, 27.09.2012
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mixed vegetation systems?
Savannas
Agricultural fields
Forests
3rd EnMAP Summer School HU Berlin, 27.09.2012
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savannas
agricultural fields
forests
mixed vegetation systems?
3rd EnMAP Summer School HU Berlin, 27.09.2012
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spectral similarity Lolium sp.
Citrus sinensis Somers et al., 2009,TGRS
RS & mixed vegetation?
3rd EnMAP Summer School HU Berlin, 27.09.2012
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spectral similarity!
white oak
virginia pine
Yellow poplar
Van Aardt & Wynne, 2001, PEARS
3rd EnMAP Summer School HU Berlin, 27.09.2012
RS & mixed vegetation?
28/09/2012
spectral similarity!
Hyperspectral remote sensing!
RS & mixed vegetation?
3rd EnMAP Summer School HU Berlin, 27.09.2012
28/09/2012
spectral similarity!
RS in mixed vegetation systems?
Hyperspectral remote sensing!
RS & mixed vegetation?
October 2010 Research Programme for Earth Observation “STEREO II” 3rd EnMAP Summer School HU Berlin, 27.09.2012
28/09/2012
October 2010 Research Programme for Earth Observation “STEREO II”
spectral similarity
Temporal remote sensing!
y2008,d299 y2008,d331 y2008,d347 y2008,d315
3rd EnMAP Summer School HU Berlin, 27.09.2012
Plant phenology!
RS in mixed vegetation systems? RS & mixed vegetation?
28/09/2012
October 2010 Research Programme for Earth Observation “STEREO II”
spectral similarity!
white oak
virginia pine
Yellow poplar
Van Aardt & Wynne, 2001, PEARS
RS in mixed vegetation systems? RS & mixed vegetation?
October 2010 Research Programme for Earth Observation “STEREO II” 3rd EnMAP Summer School HU Berlin, 27.09.2012
28/09/2012
spectral mixture problem!
RS in mixed vegetation systems? RS & mixed vegetation?
October 2010 Research Programme for Earth Observation “STEREO II” October 2010 Research Programme for Earth Observation “STEREO II” 3rd EnMAP Summer School HU Berlin, 27.09.2012
28/09/2012
November 2011 Research Programme for Earth Observation “STEREO II”
spectral mixture problem!
RS in mixed vegetation systems? RS & mixed vegetation?
October 2010 Research Programme for Earth Observation “STEREO II” October 2010 Research Programme for Earth Observation “STEREO II” 3rd EnMAP Summer School HU Berlin, 27.09.2012
28/09/2012
spectral mixture problem!
sub-pixel tree cover maps
Spectral Mixture Analysis!
November 2011 Research Programme for Earth Observation “STEREO II” October 2010 Research Programme for Earth Observation “STEREO II” October 2010 Research Programme for Earth Observation “STEREO II” 3rd EnMAP Summer School HU Berlin, 27.09.2012
RS in mixed vegetation systems? RS & mixed vegetation?
28/09/2012
spectral similarity & spectral mixture problem!
white oak virginia pine
Yellow poplar
Van Aardt & Wynne, 2001, PEARS
RS in mixed vegetation systems? RS & mixed vegetation?
November 2011 Research Programme for Earth Observation “STEREO II” October 2010 Research Programme for Earth Observation “STEREO II” October 2010 Research Programme for Earth Observation “STEREO II” 3rd EnMAP Summer School HU Berlin, 27.09.2012
28/09/2012
Multi-temporal hyperspectral mixture analysis?
Spectral Mixture Analysis processing chain
SPECTRAL MIXTURE MODELING “How to describe my mixed signal?”
SPECTRAL ENDMEMBER
EXTRACTION
“What are the spectral characteristics of building blocks?”
SPECTRAL MIXTURE ANALYSIS “Estimation of spatial extent of different building blocks!”
November 2011 Research Programme for Earth Observation “STEREO II” October 2010 Research Programme for Earth Observation “STEREO II” October 2010 Research Programme for Earth Observation “STEREO II” 3rd EnMAP Summer School HU Berlin, 27.09.2012
28/09/2012
Multi-temporal hyperspectral mixture analysis?
November 2011 Research Programme for Earth Observation “STEREO II” October 2010 Research Programme for Earth Observation “STEREO II” October 2010 Research Programme for Earth Observation “STEREO II” 3rd EnMAP Summer School HU Berlin, 27.09.2012
SPECTRAL MIXTURE MODELING “How to describe my mixed signal?”
28/09/2012
Multi-temporal hyperspectral mixture analysis?
November 2011 Research Programme for Earth Observation “STEREO II” October 2010 Research Programme for Earth Observation “STEREO II” October 2010 Research Programme for Earth Observation “STEREO II” 3rd EnMAP Summer School HU Berlin, 27.09.2012
SPECTRAL MIXTURE MODELING “How to describe my mixed signal?”
No significant amount of multiple scattering
ij
n
1j=
ij E+)F *(R=R ∑isatellite,
Rveg
Rsoil
Fsoil
Fveg
Linear Mixture Modeling
28/09/2012
Multi-temporal hyperspectral mixture analysis?
November 2011 Research Programme for Earth Observation “STEREO II” October 2010 Research Programme for Earth Observation “STEREO II” October 2010 Research Programme for Earth Observation “STEREO II” 3rd EnMAP Summer School HU Berlin, 27.09.2012
SPECTRAL MIXTURE MODELING “How to describe my mixed signal?”
Rsatellite,i = Ri,vegetation * Fvegetation+ Ri,soil * Fsoil + Ei
* 0.80 = * 0.20 +
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Multi-temporal hyperspectral mixture analysis?
November 2011 Research Programme for Earth Observation “STEREO II” October 2010 Research Programme for Earth Observation “STEREO II” October 2010 Research Programme for Earth Observation “STEREO II” 3rd EnMAP Summer School HU Berlin, 27.09.2012
SPECTRAL MIXTURE MODELING “How to describe my mixed signal?”
In natural scenes a single photon often interacts with more than one material,
MULTIPLE SCATTERING: e.g. in microscopic mixture of mineral particles found
in soils
cib,ia, bib,aia,isatellite, F *R *RF *R F *R =R F)-(1 *R+ F *R =R ib,ia,isatellite,
A B
Ra
Ra*Rb
B
A
Ra*Rb²
c ib,ia, bib,aia,isatellite, F *²R *RF *R F *R =R
COMPLEX MODELS!!!
DIFFICULT TO ACCOUNT FOR NON-LINEARITY!!!
28/09/2012
October 2010 Research Programme for Earth Observation “STEREO II”
SPECTRAL MIXTURE MODELING “How to describe my mixed signal?”
Image pixel size
Rsatellite = Rtree1 *%tree1 + Rtree2
*%tree2 + Rinteraction * %interaction + … ?
Soil?
Other possible interaction pathways?
LINEAR vs NONLINEAR!?!
November 2011 Research Programme for Earth Observation “STEREO II” October 2010 Research Programme for Earth Observation “STEREO II” October 2010 Research Programme for Earth Observation “STEREO II” 3rd EnMAP Summer School HU Berlin, 27.09.2012
Multi-temporal hyperspectral mixture analysis?
28/09/2012
October 2010 Research Programme for Earth Observation “STEREO II”
SPECTRAL MIXTURE MODELING “How to describe my mixed signal?”
Image pixel size
November 2011 Research Programme for Earth Observation “STEREO II” October 2010 Research Programme for Earth Observation “STEREO II” October 2010 Research Programme for Earth Observation “STEREO II” 3rd EnMAP Summer School HU Berlin, 27.09.2012
Multi-temporal hyperspectral mixture analysis?
15 m
3 m
0
.5 m
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Spectral Mixture Analysis processing chain
SPECTRAL MIXTURE MODELING
SPECTRAL ENDMEMBER
EXTRACTION
“What are the spectral characteristics of building blocks?”
SPECTRAL MIXTURE ANALYSIS “Estimation of spatial extent of different building blocks!”
Rsatellite = Rtree1 *%tree1 + Rtree2
*%tree2 + Rinteraction * %interaction + …
Multi-temporal hyperspectral mixture analysis?
October 2010 Research Programme for Earth Observation “STEREO II” November 2011 Research Programme for Earth Observation “STEREO II” October 2010 Research Programme for Earth Observation “STEREO II” October 2010 Research Programme for Earth Observation “STEREO II” 3rd EnMAP Summer School HU Berlin, 27.09.2012
28/09/2012 SPECTRAL ENDMEMBER EXTRACTION “What are the spectral characteristics of building blocks?”
“extraction of reflectance of pure components or endmembers”
SPECTRAL MIXTURE MODELING
Rsatellite = Rtree1 *%tree1 + Rtree2
*%tree2
Multi-temporal hyperspectral mixture analysis?
October 2010 Research Programme for Earth Observation “STEREO II” November 2011 Research Programme for Earth Observation “STEREO II” October 2010 Research Programme for Earth Observation “STEREO II” October 2010 Research Programme for Earth Observation “STEREO II” 3rd EnMAP Summer School HU Berlin, 27.09.2012
28/09/2012
SPECTRAL ENDMEMBER EXTRACTION “What are the spectral characteristics of building blocks?”
CONSTRAINED LEAST SQUARE ESTIMATION!!!
Rsatellite,1 = R1,vegetation * Fvegetation+ R1,soil * Fsoil + E1
Rsatellite,2 = R2,vegetation * Fvegetation+ R2,soil * Fsoil + E2
Rsatellite,3 = R3,vegetation * Fvegetation+ R3,soil * Fsoil + E3
Rsatellite,4 = R4,vegetation * Fvegetation+ R4,soil * Fsoil + E4 {
min( (Ri,vegetation * Fvegetation+ Ri,soil * Fsoil - Rsatellite,i)²) = min( ) m
i 1
)²(1
i
m
i
E
Multi-temporal hyperspectral mixture analysis?
October 2010 Research Programme for Earth Observation “STEREO II” November 2011 Research Programme for Earth Observation “STEREO II” October 2010 Research Programme for Earth Observation “STEREO II” October 2010 Research Programme for Earth Observation “STEREO II” 3rd EnMAP Summer School HU Berlin, 27.09.2012
? ?
28/09/2012
SPECTRAL ENDMEMBER EXTRACTION “What are the spectral characteristics of building blocks?”
Multi-temporal hyperspectral mixture analysis?
October 2010 Research Programme for Earth Observation “STEREO II” November 2011 Research Programme for Earth Observation “STEREO II” October 2010 Research Programme for Earth Observation “STEREO II” October 2010 Research Programme for Earth Observation “STEREO II” 3rd EnMAP Summer School HU Berlin, 27.09.2012
? ?
1. LABO/FIELD MEASUREMENTS
2. SPECTRAL LIBRARIES
3. SPECTRAL MODELING
4. IMAGE BASED ENDMEMBERS
28/09/2012
SPECTRAL ENDMEMBER EXTRACTION “What are the spectral characteristics of building blocks?”
Multi-temporal hyperspectral mixture analysis?
October 2010 Research Programme for Earth Observation “STEREO II” November 2011 Research Programme for Earth Observation “STEREO II” October 2010 Research Programme for Earth Observation “STEREO II” October 2010 Research Programme for Earth Observation “STEREO II” 3rd EnMAP Summer School HU Berlin, 27.09.2012
1. LABO/FIELD MEASUREMENTS Soils Query
Name Plots Cla
ss SubClass ParticleSize
Sampl
eNo
XSt
art
XSt
op
White gypsum dune sand. View
Plot
Enti
sol
Torripsam
ment
see additional
information
0015 0.4 14.0
112
Dark brown interior moist clay
loam
View
Plot
Aridi
sol
Salorthid see additional
information
79P15
30
0.4 14.0
112
Light yellowish brown interior dry
gravelly loam
View
Plot
Aridi
sol
Calciorthi
d
see additional
information
79P15
36
0.4 14.0
112
Brown to dark brown silt loam View
Plot
Enti
sol
Ustifluven
t
see additional
information
82P22
30
0.4 14.0
112
2. SPECTRAL LIBRARIES
3. SPECTRAL MODELING
28/09/2012
SPECTRAL ENDMEMBER EXTRACTION “What are the spectral characteristics of building blocks?”
Multi-temporal hyperspectral mixture analysis?
October 2010 Research Programme for Earth Observation “STEREO II” November 2011 Research Programme for Earth Observation “STEREO II” October 2010 Research Programme for Earth Observation “STEREO II” October 2010 Research Programme for Earth Observation “STEREO II” 3rd EnMAP Summer School HU Berlin, 27.09.2012
3. IMAGE BASED ENDMEMBERS
28/09/2012
SPECTRAL ENDMEMBER EXTRACTION “What are the spectral characteristics of building blocks?”
Multi-temporal hyperspectral mixture analysis?
October 2010 November 2011
Research Programme for Earth Observation “STEREO II”
October 2010 October 2010 3rd EnMAP Summer School HU Berlin, 27.09.2012
3. IMAGE BASED ENDMEMBERS
N-FINDR purity pixel Index orthogonal subspace projection
& vertex component analysis
Automatic morphological
endmember extraction
First step of the SSEE algorithm. A) Original data.
B) Subset data after spatial partitioning. C) Set of
representative SVD vectors used to describe
spectral variance.
spatial spectral EM extraction endmember bundles
Boardman et al., 1995 Winter., 1999
Nascimento & Bioucas Dias, 2005
Plaza et al., 2002
Rogge et al., 2007 Bateson et al., 2000
28/09/2012
SPECTRAL ENDMEMBER EXTRACTION “What are the spectral characteristics of building blocks?”
Multi-temporal hyperspectral mixture analysis?
October 2010 November 2011
Research Programme for Earth Observation “STEREO II”
October 2010 October 2010 3rd EnMAP Summer School HU Berlin, 27.09.2012
3. IMAGE BASED ENDMEMBERS
Simplex Fitting Method (a 2 waveband example)
- Plot the mixed pixels in n-dimensional
waveband-space
- Fit the minimum volume containing the
data (SIMPLEX)
-Endmembers = VERTEXPOINTS
Band 1
B
a
n
d
2
28/09/2012
October 2010 Research Programme for Earth Observation “STEREO II”
Spectral Mixture Analysis processing chain
SPECTRAL MIXTURE MODELING
SPECTRAL ENDMEMBER
EXTRACTION
“What are the spectral characteristics of building blocks?”
SPECTRAL MIXTURE ANALYSIS “Estimation of spatial extent of different building blocks!”
Rsatellite = Rtree1 *%tree1 + Rtree2
*%tree2 + Rinteraction * %interaction + …
Multi-temporal hyperspectral mixture analysis?
October 2010 November 2011
Research Programme for Earth Observation “STEREO II”
October 2010 October 2010 3rd EnMAP Summer School HU Berlin, 27.09.2012
28/09/2012
SPECTRAL ENDMEMBER EXTRACTION
x
SPECTRAL MIXTURE MODELING
Rsatellite = Rtree1 *%tree1 + Rtree2
*%tree2 + Rinteraction * %interaction + …
x
SPECTRAL MIXTURE ANALYSIS
“Estimation of spatial extent of different building blocks!”
min(Rsatellite - Rtree1 *%tree1 + Rtree2
*%tree2 + Rinteraction * %interaction + …)
October 2010 Research Programme for Earth Observation “STEREO II” October 2010 November 2011
Research Programme for Earth Observation “STEREO II”
October 2010 October 2010 3rd EnMAP Summer School HU Berlin, 27.09.2012
Multi-temporal hyperspectral mixture analysis?
28/09/2012
OPTIMIZATION (e.g., Least squares)
60% of pixel is covered by trees 40% of pixel is covered by soil
= * % tree + * % soil
50% of pixel covered by trees 50% of pixel is covered by soil
ENDMEMBER VARIABILITY
October 2010 November 2011
Research Programme for Earth Observation “STEREO II”
October 2010 October 2010 3rd EnMAP Summer School HU Berlin, 27.09.2012
Multi-temporal hyperspectral mixture analysis?
28/09/2012
multi-temporal spectral mixture analysis
white
oak virginia
pine
Yellow
poplar
ENDMEMBER VARIABILITY
and associated
ENDMEMBER SIMILARITY PROBLEM
Multi-temporal hyperspectral mixture analysis?
October 2010 Research Programme for Earth Observation “STEREO II” October 2010 November 2011
Research Programme for Earth Observation “STEREO II”
October 2010 October 2010 3rd EnMAP Summer School HU Berlin, 27.09.2012
28/09/2012
ENDMEMBER VARIABILITY
INTER class variability
variability between classes
INTRA class variability
variability within EM class
October 2010 Research Programme for Earth Observation “STEREO II” October 2010 November 2011
Research Programme for Earth Observation “STEREO II”
October 2010 October 2010 3rd EnMAP Summer School HU Berlin, 27.09.2012
multi-temporal spectral mixture analysis Multi-temporal hyperspectral mixture analysis?
28/09/2012
SPECTRAL ENDMEMBER EXTRACTION
x
SPECTRAL MIXTURE MODELING
Rsatellite = Rtree1 *%tree1 + Rtree2
*%tree2 + Rinteraction * %interaction + …
x
SPECTRAL MIXTURE ANALYSIS
“Estimation of spatial extent of different building blocks!”
min(Rsatellite - Rtree1 *%tree1 + Rtree2
*%tree2 + Rinteraction * %interaction + …)
endmember variability
October 2010 Research Programme for Earth Observation “STEREO II” October 2010 November 2011
Research Programme for Earth Observation “STEREO II”
October 2010 October 2010 3rd EnMAP Summer School HU Berlin, 27.09.2012
multi-temporal spectral mixture analysis Multi-temporal hyperspectral mixture analysis?
28/09/2012
October 2010 Research Programme for Earth Observation “STEREO II”
multi-temporal spectral mixture analysis
iterative mixture
analysis cycles
endmember variability
MESMA, Roberts et al., RSE, 1998
0.45
0.49
multi-temporal spectral mixture analysis Multi-temporal hyperspectral mixture analysis?
October 2010 Research Programme for Earth Observation “STEREO II” October 2010 November 2011
Research Programme for Earth Observation “STEREO II”
October 2010 October 2010 3rd EnMAP Summer School HU Berlin, 27.09.2012
28/09/2012
October 2010 Research Programme for Earth Observation “STEREO II”
multi-temporal spectral mixture analysis
SPECTRAL EM EXTRACTION
iterative mixture analysis cycles endmember variability
%tree =0.4
RMSE = 0.05
%tree =0.48
RMSE = 0.03
multi-temporal spectral mixture analysis Multi-temporal hyperspectral mixture analysis?
October 2010 Research Programme for Earth Observation “STEREO II” October 2010 November 2011
Research Programme for Earth Observation “STEREO II”
October 2010 October 2010 3rd EnMAP Summer School HU Berlin, 27.09.2012
28/09/2012
October 2010 Research Programme for Earth Observation “STEREO II”
multi-temporal spectral mixture analysis
SPECTRAL EM EXTRACTION
iterative mixture analysis cycles endmember variability
%tree =0.6
RMSE = 0.07
%tree =0.51
RMSE = 0.02
multi-temporal spectral mixture analysis Multi-temporal hyperspectral mixture analysis?
October 2010 Research Programme for Earth Observation “STEREO II” October 2010 November 2011
Research Programme for Earth Observation “STEREO II”
October 2010 October 2010 3rd EnMAP Summer School HU Berlin, 27.09.2012
28/09/2012
October 2010 Research Programme for Earth Observation “STEREO II”
multi-temporal spectral mixture analysis
SPECTRAL EM EXTRACTION
iterative mixture analysis cycles endmember variability
MESMA %tree =0.51
%tree =0.72
RMSE = 0.05
%tree =0.58
RMSE = 0.04
MESMA %tree = ?
multi-temporal spectral mixture analysis Multi-temporal hyperspectral mixture analysis?
October 2010 Research Programme for Earth Observation “STEREO II” October 2010 November 2011
Research Programme for Earth Observation “STEREO II”
October 2010 October 2010 3rd EnMAP Summer School HU Berlin, 27.09.2012
28/09/2012
October 2010 Research Programme for Earth Observation “STEREO II”
multi-temporal spectral mixture analysis
iterative mixture
analysis cycles
endmember variability
MESMA, Roberts et al., RSE, 1998
0.45
0.49
most widely used but
computationally complex (HS?)
multi-temporal spectral mixture analysis Multi-temporal hyperspectral mixture analysis?
28/09/2012
October 2010 Research Programme for Earth Observation “STEREO II”
multi-temporal spectral mixture analysis
iterative mixture
analysis cycles
endmember variability
MESMA, Roberts et al., RSE, 1998
spectral feature selection Asner & Lobell, RSE, 2000;Somers et al., IJRS, 2010
multi-temporal spectral mixture analysis Multi-temporal hyperspectral mixture analysis?
28/09/2012
October 2010 Research Programme for Earth Observation “STEREO II”
multi-temporal spectral mixture analysis
SPECTRAL EM EXTRACTION
spectral feature selection endmember variability
INTER class variability INTRA class variability
“A careful selection of wavelengths, robust
against spectral variability, could significantly
improve subpixel quantification of fractional
material cover, while the problem of CPU
complexity typical of iterative cycles could be
circumvented.” Asner & Lobell, RSE, 2000
multi-temporal spectral mixture analysis Multi-temporal hyperspectral mixture analysis?
28/09/2012
October 2010 Research Programme for Earth Observation “STEREO II”
multi-temporal spectral mixture analysis
SPECTRAL EM EXTRACTION
spectral feature selection endmember variability
Instability index criterion
selection of wavebands robust
against spectral variability
Somers et al., IJRS, 2010
multi-temporal spectral mixture analysis Multi-temporal hyperspectral mixture analysis?
October 2010 Research Programme for Earth Observation “STEREO II” October 2010 November 2011
Research Programme for Earth Observation “STEREO II”
October 2010 October 2010 3rd EnMAP Summer School HU Berlin, 27.09.2012
28/09/2012
October 2010 Research Programme for Earth Observation “STEREO II”
multi-temporal spectral mixture analysis
SPECTRAL EM EXTRACTION
spectral feature selection endmember variability
Somers et al., IJRS, 2010
ISI based feature ordening
Number of spectral features
dISI [-]
q dISI,i = ISI i+1-ISIi
DISI
accuracy
Number of spectral features
DISI [-] DISI,i = ∑(q-ISIi)
ISI~feature stability
max(DISI)~ number of features
multi-temporal spectral mixture analysis Multi-temporal hyperspectral mixture analysis?
October 2010 Research Programme for Earth Observation “STEREO II” October 2010 November 2011
Research Programme for Earth Observation “STEREO II”
October 2010 October 2010 3rd EnMAP Summer School HU Berlin, 27.09.2012
28/09/2012
October 2010 Research Programme for Earth Observation “STEREO II”
multi-temporal spectral mixture analysis
spectral feature selection endmember variability
Somers et al., IJRS, 2010
1250 most stable wavebands selected!
multi-temporal spectral mixture analysis Multi-temporal hyperspectral mixture analysis?
October 2010 Research Programme for Earth Observation “STEREO II” October 2010 November 2011
Research Programme for Earth Observation “STEREO II”
October 2010 October 2010 3rd EnMAP Summer School HU Berlin, 27.09.2012
28/09/2012
October 2010 Research Programme for Earth Observation “STEREO II”
multi-temporal spectral mixture analysis
spectral feature selection endmember variability
Somers et al., IJRS, 2010
50 most stable wavebands selected!
multi-temporal spectral mixture analysis Multi-temporal hyperspectral mixture analysis?
October 2010 Research Programme for Earth Observation “STEREO II” October 2010 November 2011
Research Programme for Earth Observation “STEREO II”
October 2010 October 2010 3rd EnMAP Summer School HU Berlin, 27.09.2012
28/09/2012
October 2010 Research Programme for Earth Observation “STEREO II”
multi-temporal spectral mixture analysis
iterative mixture
analysis cycles
endmember variability
MESMA, Roberts et al., RSE, 1998
spectral feature selection Asner & Lobell, RSE, 2000;Somers et al., IJRS, 2010
multi-temporal spectral mixture analysis Multi-temporal hyperspectral mixture analysis?
October 2010 Research Programme for Earth Observation “STEREO II” October 2010 November 2011
Research Programme for Earth Observation “STEREO II”
October 2010 October 2010 3rd EnMAP Summer School HU Berlin, 27.09.2012
28/09/2012
October 2010 Research Programme for Earth Observation “STEREO II”
multi-temporal spectral mixture analysis
iterative mixture
analysis cycles
MESMA, Roberts et al., RSE, 1998
Asner & Lobell, RSE, 2000;Somers et al., IJRS, 2010
endmember variability spectral feature selection
spectral transformations Zhang et al., TGRS, 2004; Rivard et al., TGRS, 2008
multi-temporal spectral mixture analysis Multi-temporal hyperspectral mixture analysis?
October 2010 Research Programme for Earth Observation “STEREO II” October 2010 November 2011
Research Programme for Earth Observation “STEREO II”
October 2010 October 2010 3rd EnMAP Summer School HU Berlin, 27.09.2012
28/09/2012
October 2010 Research Programme for Earth Observation “STEREO II”
multi-temporal spectral mixture analysis
spectral transformations endmember variability
INTER class variability INTRA class variability
𝐼𝑆𝐼𝑖 =∆within ,𝑖
∆between ,𝑖=
1.96(𝜎1,𝑖 + 𝜎2,𝑖)
𝑅mean ,1,𝑖 − 𝑅mean ,2,𝑖
tied reflectance
Asner & Lobell, RSE, 2000 Zhang et al., TGRS, 2004
derivative spectra
wavelet transforms
Rivard et al., TGRS, 2008
normalized spectra
Wu, RSE, 2004
multi-temporal spectral mixture analysis Multi-temporal hyperspectral mixture analysis?
October 2010 Research Programme for Earth Observation “STEREO II” October 2010 November 2011
Research Programme for Earth Observation “STEREO II”
October 2010 October 2010 3rd EnMAP Summer School HU Berlin, 27.09.2012
28/09/2012
October 2010 Research Programme for Earth Observation “STEREO II”
multi-temporal spectral mixture analysis
iterative mixture
analysis cycles
MESMA, Roberts et al., RSE, 1998
Asner & Lobell, RSE, 2000;Somers et al., IJRS, 2010
endmember variability spectral feature selection
spectral transformations Zhang et al., TGRS, 2004; Rivard et al., TGRS, 2008
multi-temporal spectral mixture analysis Multi-temporal hyperspectral mixture analysis?
October 2010 Research Programme for Earth Observation “STEREO II” October 2010 November 2011
Research Programme for Earth Observation “STEREO II”
October 2010 October 2010 3rd EnMAP Summer School HU Berlin, 27.09.2012
28/09/2012
October 2010 Research Programme for Earth Observation “STEREO II”
multi-temporal spectral mixture analysis
iterative mixture
analysis cycles
MESMA, Roberts et al., RSE, 1998
spectral transformations Zhang et al., TGRS, 2004; Rivard et al., TGRS, 2008
endmember variability spectral feature selection
Asner & Lobell, RSE, 2000;Somers et al., IJRS, 2010
data integration Somers et al., IJRS, 2010
multi-temporal spectral mixture analysis Multi-temporal hyperspectral mixture analysis?
October 2010 Research Programme for Earth Observation “STEREO II” October 2010 November 2011
Research Programme for Earth Observation “STEREO II”
October 2010 October 2010 3rd EnMAP Summer School HU Berlin, 27.09.2012
28/09/2012
October 2010 Research Programme for Earth Observation “STEREO II”
data integration endmember variability
“It is hypothesized that the subtle spectral
differences among plant species can be more
readily defined in a hyperdimensional feature
space”
Somers et al., TGRS, 2009
&
SPECTRAL EM EXTRACTION
original reflectance transformed reflectance
multi-temporal spectral mixture analysis Multi-temporal hyperspectral mixture analysis?
October 2010 Research Programme for Earth Observation “STEREO II” October 2010 November 2011
Research Programme for Earth Observation “STEREO II”
October 2010 October 2010 3rd EnMAP Summer School HU Berlin, 27.09.2012
28/09/2012
October 2010 Research Programme for Earth Observation “STEREO II”
data integration endmember variability
instability index
ISI criterion
Somers et al., TGRS, 2009
multi-temporal spectral mixture analysis Multi-temporal hyperspectral mixture analysis?
October 2010 Research Programme for Earth Observation “STEREO II” October 2010 November 2011
Research Programme for Earth Observation “STEREO II”
October 2010 October 2010 3rd EnMAP Summer School HU Berlin, 27.09.2012
28/09/2012
data integration endmember variability
ISI criterion
Somers et al., TGRS, 2009
multi-temporal spectral mixture analysis Multi-temporal hyperspectral mixture analysis?
October 2010 Research Programme for Earth Observation “STEREO II” October 2010 November 2011
Research Programme for Earth Observation “STEREO II”
October 2010 October 2010 3rd EnMAP Summer School HU Berlin, 27.09.2012
28/09/2012
iterative mixture
analysis cycles
MESMA, Roberts et al., RSE, 1998
spectral transformations Zhang et al., TGRS, 2004; Rivard et al., TGRS, 2008
endmember variability spectral feature selection
Asner & Lobell, RSE, 2000;Somers et al., IJRS, 2010
data integration Somers et al., IJRS, 2010
multi-temporal spectral mixture analysis Multi-temporal hyperspectral mixture analysis?
October 2010 Research Programme for Earth Observation “STEREO II” October 2010 November 2011
Research Programme for Earth Observation “STEREO II”
October 2010 October 2010 3rd EnMAP Summer School HU Berlin, 27.09.2012
28/09/2012
multi-temporal spectral mixture analysis
iterative mixture
analysis cycles
MESMA, Roberts et al., RSE, 1998
spectral feature selection Asner & Lobell, RSE, 2000;Somers et al., IJRS, 2010 Somers et al., IJRS, 2010
endmember variability data integration
spectral transformations Zhang et al., TGRS, 2004; Rivard et al., TGRS, 2008
temporal unmixing Lobell & Asner, RSE, 20004;
Singh & Glenn, IJRS, 2009
multi-temporal spectral mixture analysis Multi-temporal hyperspectral mixture analysis?
October 2010 Research Programme for Earth Observation “STEREO II” October 2010 November 2011
Research Programme for Earth Observation “STEREO II”
October 2010 October 2010 3rd EnMAP Summer School HU Berlin, 27.09.2012
28/09/2012
multi-temporal spectral mixture analysis
temporal unmixing endmember variability
y2008,d299 y2008,d331 y2008,d347 y2008,d315
SPECTRAL EM EXTRACTION
SPECTRAL MIXTURE ANALYSIS
multi-temporal spectral mixture analysis Multi-temporal hyperspectral mixture analysis?
October 2010 Research Programme for Earth Observation “STEREO II” October 2010 November 2011
Research Programme for Earth Observation “STEREO II”
October 2010 October 2010 3rd EnMAP Summer School HU Berlin, 27.09.2012
28/09/2012
multi-temporal spectral mixture analysis
temporal unmixing endmember variability
multi-temporal spectral mixture analysis Multi-temporal hyperspectral mixture analysis?
October 2010 Research Programme for Earth Observation “STEREO II” October 2010 November 2011
Research Programme for Earth Observation “STEREO II”
October 2010 October 2010 3rd EnMAP Summer School HU Berlin, 27.09.2012
Jan Mar Jul Aug Sep Oct
28/09/2012
multi-temporal spectral mixture analysis
temporal unmixing endmember variability
multi-temporal spectral mixture analysis Multi-temporal hyperspectral mixture analysis?
October 2010 Research Programme for Earth Observation “STEREO II” October 2010 November 2011
Research Programme for Earth Observation “STEREO II”
October 2010 October 2010 3rd EnMAP Summer School HU Berlin, 27.09.2012
Jan Mar Jul Aug Sep Oct
SPECTRAL EM EXTRACTION
28/09/2012
multi-temporal spectral mixture analysis
temporal unmixing endmember variability
multi-temporal spectral mixture analysis Multi-temporal hyperspectral mixture analysis?
October 2010 Research Programme for Earth Observation “STEREO II” October 2010 November 2011
Research Programme for Earth Observation “STEREO II”
October 2010 October 2010 3rd EnMAP Summer School HU Berlin, 27.09.2012
SPECTRAL EM EXTRACTION
28/09/2012
multi-temporal spectral mixture analysis
temporal unmixing endmember variability
multi-temporal spectral mixture analysis Multi-temporal hyperspectral mixture analysis?
October 2010 Research Programme for Earth Observation “STEREO II” October 2010 November 2011
Research Programme for Earth Observation “STEREO II”
October 2010 October 2010 3rd EnMAP Summer School HU Berlin, 27.09.2012
SPECTRAL EM EXTRACTION
28/09/2012
multi-temporal spectral mixture analysis
temporal unmixing endmember variability
multi-temporal spectral mixture analysis Multi-temporal hyperspectral mixture analysis?
October 2010 Research Programme for Earth Observation “STEREO II” October 2010 November 2011
Research Programme for Earth Observation “STEREO II”
October 2010 October 2010 3rd EnMAP Summer School HU Berlin, 27.09.2012
temporal image stack
SPECTRAL MIXTURE ANALYSIS
Rsatellite,1, t1 = R1,t1,tree1 * Ftree1+ R1,t1,tree2 * Ftree2 + E1
Rsatellite,1,t2 = R1,t2,tree1 * Ftree1+ R1,t2,tree2 * Ftree2 + E2
Rsatellite,2, t1 = R2,t1, tree1 * Ftree1+ R2,t1, tree2 * Ftree2+ E3
Rsatellite,2, t2 = R2,t2, tree1 * Ftree1+ R2,t2, tree2 * Ftree2 + E3
28/09/2012
multi-temporal spectral mixture analysis
temporal unmixing endmember variability
multi-temporal spectral mixture analysis Multi-temporal hyperspectral mixture analysis?
October 2010 Research Programme for Earth Observation “STEREO II” October 2010 November 2011
Research Programme for Earth Observation “STEREO II”
October 2010 October 2010 3rd EnMAP Summer School HU Berlin, 27.09.2012
temporal image stack
SPECTRAL MIXTURE ANALYSIS
Rsatellite,1, t1 = R1,t1,tree1 * Ftree1+ R1,t1,tree2 * Ftree2 + E1
Rsatellite,1,t2 = R1,t2,tree1 * Ftree1+ R1,t2,tree2 * Ftree2 + E2
Rsatellite,2, t1 = R2,t1, tree1 * Ftree1+ R2,t1, tree2 * Ftree2+ E3
Rsatellite,2, t2 = R2,t2, tree1 * Ftree1+ R2,t2, tree2 * Ftree2 + E3
HYPOTHESIS: no change in cover fraction
during the considered time frame!!!!
(acceptable in many applications if time frame
is adapted to specific boundary conditions)
28/09/2012
multi-temporal spectral mixture analysis
temporal unmixing endmember variability
multi-temporal spectral mixture analysis Multi-temporal hyperspectral mixture analysis?
October 2010 Research Programme for Earth Observation “STEREO II” October 2010 November 2011
Research Programme for Earth Observation “STEREO II”
October 2010 October 2010 3rd EnMAP Summer School HU Berlin, 27.09.2012
ENDMEMBER VARIABILITY REDUCTION!
28/09/2012
multi-temporal spectral mixture analysis
white
oak virginia
pine
Yellow
poplar
ENDMEMBER VARIABILITY
and associated
ENDMEMBER SIMILARITY PROBLEM
Multi-temporal hyperspectral mixture analysis?
October 2010 Research Programme for Earth Observation “STEREO II” October 2010 November 2011
Research Programme for Earth Observation “STEREO II”
October 2010 October 2010 3rd EnMAP Summer School HU Berlin, 27.09.2012
28/09/2012
multi-temporal spectral mixture analysis
iterative mixture
analysis cycles
MESMA, Roberts et al., RSE, 1998
spectral feature selection Asner & Lobell, RSE, 2000;Somers et al., IJRS, 2010 Somers et al., IJRS, 2010
endmember variability data integration
spectral transformations Zhang et al., TGRS, 2004; Rivard et al., TGRS, 2008
temporal unmixing Lobell & Asner, RSE, 20004;
Singh & Glenn, IJRS, 2009
multi-temporal spectral mixture analysis Multi-temporal hyperspectral mixture analysis?
October 2010 Research Programme for Earth Observation “STEREO II” October 2010 November 2011
Research Programme for Earth Observation “STEREO II”
October 2010 October 2010 3rd EnMAP Summer School HU Berlin, 27.09.2012
28/09/2012
multi-temporal spectral mixture analysis multi-temporal spectral mixture analysis Thank You! Questions?
October 2010 Research Programme for Earth Observation “STEREO II” October 2010 November 2011
Research Programme for Earth Observation “STEREO II”
October 2010 October 2010 3rd EnMAP Summer School HU Berlin, 27.09.2012
SPECTRAL
SPACE
TIME