Passive Microwave Remote
Sensing
Lecture 11
Principals


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While dominate wavelength of Earth is 9.7 um (thermal), a
continuum of energy is emitted from Earth to the atmosphere.
In fact, the Earth emits a steady stream of microwave energy as
well, though it is relatively weak in intensity due to its long
wavelength.
The spatial resolution usually low (kms) since the weak signal.
A suit of radiometers can record it. They measure the
brightness temperature emitted from the terrain or the
atmospheric gasses, dusts. This is much like the thermal
infrared radiometer for temperature measurement as we
discussed before.
A matrix of brightness temperature values can then be used to
construct a passive microwave image.
To measure soil moisture, precipitation, ice water content, seasurface temperature, snow-ice temperature, and etc., based on
brightness temperature images.
Rayleigh-Jeans approximation of
Planck’s law
2hc 2
L( , T )  5 hc /(kT )
 (e
 1)
Thermal infrared domain (Planck’s law):
Microwave domain (Rayleigh-Jeans approximation):
2hc 2
L ( , T ) 
 (e
5
Let
We have
hc
kT
2hc 2

 1)
h
x
, and
kT
hv  kT
 (e
5
h
kT
2hc 2
2hc 2
2hc 2 2hc 2 kT 2ckT
 5 x
 5



5
h

 (e  1)  (1  x  1) 5
 h
4
 1)
kT
Recall
We have
x x2
e  1    1 x
1! 2!
x
v
c

,...  dv 
2
c

2
d
2 2ckT 2kT 2
| L(v, T )dv || L( , T )d |,...  L(v, T )  L( , T )  
 2 v
4
c
c

c
Unit is Wm-2Hz

For a Lambertian surface, the surface
brightness radiation B(v,T),
Unit is W•m
-2•Hz•sr
2kT 2
L(v, T )  B(v, T ),...  B (v, T )  2 v
c

The really useful simplification involves
emissivity and brightness temperature in
microwave range:
In comparison with thermal infrared:
(TB)4 = ελ (T)4
Some important passive
microwave radiometers
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Special Sensor Mirowave/Imager (SSM/I)
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It was onboard the Defense Meterorological
Satellite Program (DMSP) since 1987
It measure the microwave brightness
temperatures of atmosphere, ocean, and terrain at
19.35, 22.23, 37, and 85.5 GHz.
TRMM microwave imager (TMI)

It is based on SSM/I, and added one more
frequency of 10.7 GHz.
AMSR-E
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Advanced Microwave Scanning Radiometer – EOS
It observes atmospheric, land, oceanic, and cryospheric parameters,
including precipitation, sea surface temperatures, ice concentrations,
snow water equivalent, surface wetness, wind speed, atmospheric
cloud water, and water vapor.
At the AMSR-E low-frequency channels, the atmosphere is relatively
transparent, and the polarization and spectral characteristics of the
received microwave radiation are dominated by emission and
scattering at the Earth surface.
Over land, the emission and scattering depend primarily on the water
content of the soil, the surface roughness and topography, the surface
temperature, and the vegetation cover.
The surface brightness T (TB ) tend to increase with frequency due to
the absorptive effects of water in soil and vegetation that also
increase with frequency. However, as the frequency increase,
scattering effects from the surface and vegetation also increase,
acting as a factor to reduce the TB
AMSR-E
Najoku et al. 2005
Example1: Snow depth or snow
water equivalent (SWE)

The microwave brightness
temperature emitted from a
snow cover is related to the
snow mass which can be
represented by the
combined snow density
and depth, or the SWE (a
hydrological quantity that
is obtained from the
product of snow depth and
density).
∆Tb = Tb19V-Tb37V
Large grains tend to scatter
microwave radiation more
than smaller grains
Volume fraction (%)
= snow density/900
From fresh snow to packsnow,
the snow density increase from
<100 kg m-3 to between 200400 kg m-3
Kelly et al. 2003
Example 1
3. Study Area (1)
Impact of snow density (4)-mean SD
AMSR-E vs ground mean snow depth
AMSER-E vs ground mean snow depth
30
30
y = 0.81x + 0.25
R2 = 0.74
RMSD=4.6 cm
EB= -17%
20
25
AMSR-E (cm)
AMSR-E (cm)
25
15
20
15
10
10
5
5
y = 0.97x + 1.45
R2 = 0.90
RMSD=3.0 cm
EB =11%
0
0
0
5
10
15
20
25
30
Ground snow depth (cm)
Snow density = 0.4 g/cm3 or 400 kg m-3
0
5
10
15
20
25
Ground snow depth (cm)
Multi-snow density
Wang, Xie, and Liang 2006
30
Results: AMSR-E vs ground- SD at
individual stations (snow density = 0.4 g/cm3)
50
50
Zhaoshu
Caijiahu
y = 0.82x + 1.46
R2 = 0.65
40
40
30
30
20
20
10
y = 1.28x - 3.20
R2 = 0.52
10
0
0
0
10
50
20
30
40
50
Qinhe
0
10
20
25
40
20
30
15
20
10
10
30
50
jinhe
y = 0.78x + 1.65
R2 = 0.40
5
y = 0.69x + 4.06
R2 = 0.40
40
0
0
0
10
20
30
40
50
0
5
10
15
20
25
Results: AMSR-E vs ground- SD at
individual stations (snow density = 0.4 g/cm3)
50
40
30
Baitashan
y = 0.55x + 2.58
R2 = 0.74
Tuoli
y = 0.42x + 3.15
R2 = 0.56
25
20
30
15
20
10
5
10
0
0
0
0
10
20
50
30
40
40
40
30
30
20
10
10
0
0
20
15
20
25
30
30
40
y = 0.94x - 0.75
R2 = 0.50
Fuhai
20
y = 1.64x - 6.84
R2 = 0.65
10
10
50
Qitai
0
5
50
50
0
10
20
30
40
50
Results: Annual change of SWE in
YWR
Annual Change of SWE (cm) in YRW
60
Mean SWE (cm)
50
40
30
20
10
0
6
8
10
12
2
02-03
4
6
8
10
12
2
4
6
8
10
03-04
12
04-05
Hydrologic Year
2
4
6
8
10
12
05-06
2
4
Example 2
Antarctic sea ice
Footprint size
Level 2 data
58 km
37 km
21 km
11 km
5 km
Footprint size
AMSR Bootstrap/
Ice temperature
58 km
37 km
21 km
11 km
5 km
Footprint size
AMSR Bootstrap/
Ice temperature
58 km
Bootstrap
37 km
21 km
11 km
5 km
Footprint size
AMSR Bootstrap/
Ice temperature
58 km
Bootstrap
NASA Team 2/
Snow depth
37 km
21 km
11 km
5 km
AMSR-E derived sea ice concentrations
Ice Concentration/area
Based on SMMRSSM/I
(http://nsidc.org)
23
Compare AMSR-E ice concentration
and NIC ice edge
24
Cicek et al. 2009
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Idea:
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Snow cover
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Radiation from the
ground is scattered by
the snow cover.
The more snow the
more scattering.
Scattering efficiency is
frequency dependent.
hs = c (T37GHz-T19GHz)
Difficulties:

(From C.L. Parkinson, Earth from above,1997)
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Different terrain forms
(e.g., tundra,
mountains, plains);
different ice properties
(FY/MY icel, ridges)
Scattering varies with
snow physical
properties (e.g., grain
size, density, wetness)
Monthly snow depth data are derived from satellite passive microwave data
A: Weddell Sea
7/86 - 9/86
(Wadhams et al., 1986)
B: East Antarctic
10/88 - 12/88
(Allison et al., 1993)
C: Weddell Sea
9/89 - 10/89
(Eicken et al., 19994)
D: East Antartic
11/91
(Worby and Massom, 1991)
E: Weddell Sea
6/92 - 7/92
(Drinkwater and Haas, 1994)
F: East Antarctic
10/92 - 11/92
(Worby and Massom, 1995)
G: East Antarctic
3/93 - 5/93
(Worby and Massom, 1995)
H: Bellingshausen
8/93 - 9/93
(Worby et al., 1996)
I: Amundsen
9/94 - 10/94
(Sturm et al., 1998)
J: East Antarctic
9/94 - 10/94
(Jeffries et al., 1995)
K: Ross Sea
5/95 - 6/95
(Sturm et al.,1998)
L: Ross Sea/Bellingshausen 8/95-9/95
(Sturm et al., 1998)
Inter-annual variability of September snow depth
(on a pixel-by-pixel basis)
Example 3
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Radio-frequency interference
contaminate the 6.9 and 10.7
GHz channels
Radio-frequency interference (RFI) includes the cable television
relay, auxiliary broadcasting, mobile. RFI is several orders of
magnitude higher than natural thermal emissions and is often
directional and can be either continuous or intermittent.
Radio-frequency interference (RFI) is an increasingly serious
problem for passive and active microwave sensing of the Earth.
The 6.9 GHz contamination is mostly in USA, Japan, and the Middle
East.
The 10.7 GHz contamination is mostly in England, Italy, and Japan
RFI contamination compromise the science objectives of sensors
that use 6.9 and 10.7 GHz (corresponding to the C-band and X-band
in active microwave sensing) over land.
radio-frequency interference (RFI)
index (RI)
Li et al. 2004
6.9 GHz contamination
Najoku et al. 2005