- Microwave Remote Sensing Group
The Potential of Cosmo-Skymed SAR
Images in Mapping Snow Cover and
Snow Water Equivalent
M. Brogioni1, S. Pettinato1, E. Santi1, S. Paloscia1,
P. Pampaloni1, E. Palchetti1, J. Shi2,3, C. Xiong1,2,
1Institute
of Applied Physics - IFAC-CNR, Firenze, Italy
for Remote Sensing Applications, Beijing, China
3University of California, Santa Barbara (CA), USA
2Institute
IGARSS 2011, July 23-29, Vancouver, Canada
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- Microwave Remote Sensing Group
Outline
 Motivations
 The ASI Cosmo-Skymed mission and data
 Model investigations
 Experimental Results
 Retrieval of Snow cover and Snow Water Equivalent
IGARSS 2011, July 23-29, Vancouver, Canada
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- Microwave Remote Sensing Group
Introduction
Several experiments have documented the ability of Cband SAR in mapping the extent of wet snow. But the
high transmissivity of dry snow cover at this frequency
makes difficult to detect it.
The study aims at evaluating the potential of X-band
COSMO-Skymed SAR in generating snow cover maps
and estimating snow water equivalent
IGARSS 2011, July 23-29, Vancouver, Canada
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- Microwave Remote Sensing Group
The ASI/Cosmo-Skymed mission
4 medium-size satellites, equipped with an
X-band SAR HH, VV, HV, VH pol
sun-synchronous orbit at ~620km height
Full constellation
revisit time : 12 h
- 1 Spotlight mode, for metric resolutions over small images
- 2 Stripmap modes, for metric resolutions over tenth of km images;
one mode is polarimetric with images acquired in two polarizations
- 2 ScanSAR for medium to coarse (100 m) resolution over large swath
IGARSS 2011, July 23-29, Vancouver, Canada
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Example of COSMO-Skymed data
Temporal variation of backscattering on alpine regions
CSK® © ASI
2, July
Himage,
HH,
 = 26.5°Canada
IGARSSCSK
2011,
23-29,
Vancouver,
- Microwave Remote Sensing Group
Model Investigation: Snow backscattering model
e
0
AIR
e
e
z=0
S
SNOW
0
z=-d
e
GROUND
2
 Snow as a single layer of identical
scatterers
 Flat air-snow interface
 Rough snow –soil interface
Multiple scattering effects
Snow volume
scattering
Surface scattering
DMRT-QCA
(Tsang et al., 2007)
Mie Scattering
Stickyness
AIEM
(Chen et al., 2004)
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IGARSS 2011, July 23-29, Vancouver, Canada
- Microwave Remote Sensing Group
The surface scattering: The AIEM model
 o qp ( S )   k qp ( S )   kcqp ( S )   c qp ( S )
The normalized scattering coefficient is composed of three terms:
Kirchhoff, cross and the complementary one.
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IGARSS 2011, July 23-29, Vancouver, Canada
- Microwave Remote Sensing Group
Volume scattering: The DMRT/QCA Model
(Tsang et al. 2007)


2



d I  ,  , z 
cos
 ke  I  ,  , z    d ' sin  '  d ' P  ,  ; ' ,  '  I  ' ,  ' , z 
dz
0
0
2

2
 d
0
0
0
0   I1i 
 I1s   P11  
I   0
 I 


P

0
0
2
s
22


   2i 
U12 s   0
0
P33   P34   U12i 

 
 

0
P43   P44    V12 i 
 V12 s   0
f11    
i
1
1  R  k K r
i
1
f 22    
1  R  k K r
 nn  1T
N max
2n  1
n1
(M )
n
 nn  1T
N max
n1
2n  1

'
sin 
 
2
'

 d P , ;    ,  I    ,  , z 
'

'
'

'
'
0
P33   P44 
P11    f11   q  
2
P22    f 22   q 
2


P33   Re f11  f  q
P34    Im f11  f 22*  q
*
22

P43   P34 


X n( M ) n cos    Tn( N ) X n( N ) n cos  
(M )
n

X n( M ) n cos    Tn( N ) X n( N ) n cos  
IGARSS 2011, July 23-29, Vancouver, Canada
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- Microwave Remote Sensing Group
Model Simulations
(DMRT – QCA model)
Frequency (GHz)
5.3, 9.6, 17.2
Polarization
VV, HH, HV
Incidence angle (deg)
20 - 50
Density (Kg/m3)
200 - 500
Grain radius (mm)
0.1 - 1.5
Snow depth (cm)
20 - 300
Soil
smooth
Data chosen to account for the different type of snow cover on the Alps
IGARSS 2011, July 23-29, Vancouver, Canada
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- Microwave Remote Sensing Group
Model Simulations
Extinction and Penetration depth
Density
Crystal
radius
(mm)
Radius
0.5
0.9
1.3
Frequency
Band
C
X
Ku
C
X
Ku
C
X
Ku
Penetration depth (1/ke)
(m)
250 Kg/m3
66.8
9.5
1.2
18.8
2.3
0.33
7.4
0.99
0.15
350 Kg/m3
81.9
17.5
2.5
39.3
5.31
0.67
17.8
2.16
0.29
IGARSS 2011, July 23-29, Vancouver, Canada
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- Microwave Remote Sensing Group
Sensitivity of backscattering to grain radius
IGARSS 2011, July 23-29, Vancouver, Canada
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- Microwave Remote Sensing Group
Model Simulations: Sensitivity to SWE
Crystal radius: 0.1 mm – Incidence angle: 35°
SWE
Backscattering (dB)
SWE
Density 150-400
5.3 GHz
Total scattering
9.6 GHz
SWE
Soil contribution
Backscattering (dB)
Snow contribution
17.2
GHz Canada
IGARSS 2011, July 23-29,
Vancouver,
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- Microwave Remote Sensing Group
Model Simulations: Sensitivity to SWE
Crystal radius: 0.3 mm – Incidence angle: 35°
5.3 GHz
SWE (mm)
Backscattering (dB)
Backscattering (dB)
SWE (mm)
9.6 GHz
Total scattering
SWE (mm)
Soil contribution
Backscattering (dB)
Snow contribution
17.2 GHz Canada
IGARSS 2011, July 23-29, Vancouver,
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- Microwave Remote Sensing Group
Model Simulations: Sensitivity to SWE
Crystal radius: 0.5 mm – Incidence angle: 35°
SWE (mm)
Backscattering (dB)
Backscattering (dB)
SWE (mm)
5.3 GHz
Total scattering
9.6 GHz
SWE (mm)
Soil contribution
Backscattering (dB)
Snow contribution
GHz Canada
IGARSS 2011, July 23-29,17.2
Vancouver,
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- Microwave Remote Sensing Group
5.3 GHz
Model Simulations
9.6 GHz
17.2 GHz
Backscattering
Sensitivity to SWE
IGARSS 2011, July 23-29, Vancouver, Canada
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- Microwave Remote Sensing Group
Experimental sensitivity to Snow Depth:Temporal trends
Wet
snow
D SWE
IGARSS 2011, July 23-29, Vancouver,
DepthCanada
Hoar
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Generation of snow cover maps
and Retrieval of SWE
17
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- Microwave Remote Sensing Group
Principle of the algorithm
clear sky
dry/wet snow
clouds
?
snow cover
Optic
SAR
snow cover + SWE
wet snow
clear
cloudy
wet snow
Threshold
dry snow
ANN
SWE
Ref. Image
DEM + air
temperature
IGARSS 2011, July 23-29, Vancouver, Canada
for high SWE
values
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- Microwave Remote Sensing Group
Validation of SWE Algorithm with experimental
X-band data
Date
08/03/2009
27/05/2009
14/07/2009
22/01/2010
26/03/2010
29/03/2010
02/09/2010
Sensor
CSK2
CSK2
CSK2
CSK2
CSK2
CSK1
CSK1
Sensor mode
STR_HIMAGE
STR_HIMAGE
STR_HIMAGE
STR_HIMAGE
STR_PINGPONG
STR_PINGPONG
STR_PINGPONG
Polarization
HH
HH
HH
HH
VV/VH
VV/VH
VV/VH
IGARSS 2011, July 23-29, Vancouver, Canada
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- Microwave Remote Sensing Group
First verification of SWE Algorithm with exper. data
22/01/2010
Single
polarization
08/03/2009
SWE SWE
SWE SWE
(200
(300 SWE NN
(200
(300 SWE NN
Kg/m3) Kg/m3)
Kg/m3) Kg/m3)
27/05/2009
SWE
SWE
(200
(300
SWE NN
Kg/m3) Kg/m3)
Monti Ornella
272
408
270
500
750
masked
194
291 wet snow
Col dei Baldi
268
402
350
574
861
544
90
135 wet snow
Pradazzo
192
288
280
306
459
400 no data no data
Ravales
280
420
masked
488
732
Cherz
200
300
290
240
360
Dual polarization
(co & cross )
26/03/2010
SWE
SWE
(200 Kg/m3) (300 Kg/m3)
masked
260
390
270 no data no data
29/03/2010
SWE
SWE
SWE NN (200 Kg/m3) (300 Kg/m3)
masked
-
SWE NN
Monti Ornella
304
456
380
332
498
438
Col dei Baldi
296
444
390
294
441
masked
Cima Pradazzo
204
306
masked
198
297
masked
Ravales
304
456
378
332
498
480
Cherz
270
405
masked
230
345
masked
IGARSS 2011, July 23-29, Vancouver, Canada
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- Microwave Remote Sensing Group
Example of Snow Cover Area
40
Km
SWE
January 22, 2010
IGARSS 2011, July 23-29, Vancouver, Canada
March 29, 2011
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Summary and conclusions
 The sensitivity of ASI/Cosmo-Skymed X-band SAR to snow cover and
SWE has been investigated by using experimental results and model
simulations.
 An algorithm to generate snow cover maps by combining optical and
SAR data has been developed and validated
 It has been found that X-band data can contribute to the retrieval of
SWE for snow depth higher than about 40-50 cm and relative high
crystal size .
 More investigations and data validations are needed to demonstrate
the full potential of Cosmo-Skymed SAR in snow detection
Aknowledgment
This work has been funded by the Italian Space Agency (ASI) under
the COSMO-Skymed project 1720
IGARSS 2011, July 23-29, Vancouver, Canada
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- Microwave Remote Sensing Group
IGARSS 2011, July 23-29, Vancouver, Canada
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Model simulations
Sensitivity of X band backscattering to snow density
Snow depth : 1 m -
Grain radius : 0.5 mm
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IGARSS 2011, July 23-29, Vancouver, Canada
- Microwave Remote Sensing Group
IGARSS 2011, July 23-29, Vancouver, Canada
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- Microwave Remote Sensing Group
Model investigations : Snow-pack scattering

^
Z
AIR
•Depth
z=0
z=-d
z=-d
•Density
•Size/shape of
crystals
1
2
• Liquid water
contet
SNOW
z=-d
N-2
z=-d
N-1
z=-d
•Height St Dev
• Correlation
length
N
• Autocorrelation
function
GROUND
IGARSS 2011, July 23-29, Vancouver, Canada
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- Microwave Remote Sensing Group
Test of SWE Algorithm with simulated data
10000 input values randomly varied:
5000 for training - 5000 for test
Snow depth =10 - 150 cm
Density = 200-300 kg/m3
Grain radius = 0.1 – 1.0 mm
Incidence angle = 20°-70°
Single polarization (RMSE=~ 32 mm)
600
y = 0.9495x + 11.107
R2 = 0.9342
500
SWE calcolato (mm)
400
300
200
100
0
0
100
200
300
400
500
600
SWE m isurato (m m )
Dual polarization (RMSE=~ 25 mm)
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IGARSS 2011, July 23-29, Vancouver, Canada
- Microwave Remote Sensing Group
Generation of dry/wet snow cover maps
04/05/2009
100 km
SAR
wet snow
04/05/2009
SAR + MODIS
MODIS
snow cover
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