Microwave Remote Sensing of
Snowpack
Do-Hyuk “DK” Kang
Postdoctoral Fellow
Northern Hydrometeorology Group (NHG)
Environmental Science and Engineering
University of Northern BC
February 5th 2013
Northern Hydrometeorology Group, UNBC
Discovery and Acceleration Fund
Outline
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Fundamentals of remote sensing
Satellites and sensors
Application of remote sensing
Remote sensing of snow in the Cariboo
Mountains of BC (Jinjun Tong)
 Microwave Remote Sensing
 Results (DK and Déry)
 Remote Sensing is a technology for
sampling electromagnetic radiation to
acquire and interpret non-immediate
geospatial data from which to extract
information about features, objects, and
classes on the Earth's land surface, oceans,
and atmosphere (and, where applicable, on
the exteriors of other bodies in the solar
system, or, in the broadest framework,
celestial bodies such as stars and galaxies).
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Energy Source or Illumination
(A)
Radiation and the Atmosphere
(B)
Interaction with the Target (C)
Recording of Energy by the
Sensor (D)
Transmission, Reception, and
Processing (E)
Interpretation and Analysis (F)
Application (G)
Electromagnetic Radiation
Interactions with the Atmosphere
Scattering
Absorbing
Those areas of the spectrum which are not
severely influenced by atmospheric absorption
and thus, are useful to remote sensors, are
called atmospheric windows
Target Interactions

Absorption (A) occurs when radiation (energy) is absorbed into the
target while transmission (T) occurs when radiation passes through a
target. Reflection (R) occurs when radiation "bounces" off the target
and is redirected.
 water and vegetation may reflect somewhat
similarly in the visible wavelengths but are
almost always separable in the infrared.
Passive vs. Active Remote Sensing
Passive Sensing
Active Sensing
Satellites and Sensors
 In order for a sensor to collect and record energy
reflected or emitted from a target or surface, it must
reside on a stable platform removed from the target or
surface being observed. Platforms for remote sensors
may be situated on the ground, on an aircraft or
balloon (or some other platform within the Earth's
atmosphere), or on a spacecraft or satellite outside of
the Earth's atmosphere. Although ground-based and
aircraft platforms may be used, satellites provide a
great deal of the remote sensing imagery commonly
used today.
Satellite Orbits
Geostationary orbits
Near-polar orbit
Ascending vs Descending
Weather Satellites/Sensors
 TIROS-1(launched in 1960 by the United States)
 GOES (Geostationary Operational Environmental Satellite)
-GOES-1 (launched 1975), GOES-8 (launched 1994)
 Advanced Very High Resolution Radiometer(NOAA AVHRR)(sun-
synchronous, near-polar orbits)
 FengYun-1, FengYun-2, FengYun-3, FengYun-4 (China)
 GMS (Japan)
 Meteosat (European)
Land Observation Satellites/Sensors
 Landsat (Landsat-1 was launched by NASA in 1972, near-polar,
sun-synchronous orbits).
-Return Beam Vidicon (RBV), MultiSpectral Scanner (MSS), Thematic Mapper (TM)
 SPOT(SPOT-1 was launched by France in 1986, sun-synchronous,
near-polar orbits)
-Twin high resolution visible (HRV)
 Multispectral Electro-optical Imaging Scanner(MEIS II)
Compact Airborne Spectrographic Imager(CASI)(airborne
sensors)(Canada)
 Canadian RADARSAT I and II
- (Active Microwave Remote Sensing)
Data Reception, Transmission, and Processing
In Canada, CCRS operates two ground receiving stations one at Cantley, Québec (GSS), just outside of Ottawa, and
another one at Prince Albert, Saskatchewan (PASS)
Quiz
The Quesnel
River Basin (QRB)
in the Cariboo
Mountains
 It is one of 13 main
sub-basins in the
Fraser River Basin,
one of the world's
most productive
salmon river
systems.
 Snow plays a vital
role in the energy
and water budgets
of these basins.
Evaluation of MODIS data
MODIS
Ground
Snow
Snow
No snow
a
b
No snow
c
d
Accuracy 
ad
abcd
Accuracy of different MODIS snow data
Stations
Elevation,
m
MOD10A1, %
MOD10A2, %
SF, %
Horsefly Lake/Gruhs Lake
777
88.31
88.92
91.49
Barkerville
1265
85.95
86.69
87.89
Boss Mountain Mine
1460
71.14
81.25
82.72
Yanks Peak East
1670
62.17
73.85
74.15
Snow cover fraction (%)
Results
The spatially filtered snow cover fraction (SCF) for different elevation
bands (top) and aspects with slopes > 15o (bottom), 2000-2007.
The mean elevational dependence of snow cover fraction (SCF) for the months of February
to July, 2000-2007.
Snow cover duration (days)
SCD (days)
The annual snow cover
duration (x3 days) in the
QRB based on spatially
filtered (SF) MODIS snow
(Snow melt season)
products, 2001-2007.
140
120
100
80
60
40
20
0
400
800
1200 1600 2000 2400 2800
140
120
100
80
60 Mean snow cover durations
40
(SCD)
for 10-mseason)
elevation
(Snow accumulation
20
0 bands from the MOD10A2 (+)
400 800 1200 1600 2000 2400 2800
360
300
240
180
120
60
0
400
& SF (□) products, 20012007.
(Entire year)
800
1200 1600 2000 2400 2800
Elevation (m)
r = 0.96
d(SCD)/dz =
11.6 days (100 m)-1
Scatter plot between average air temperature and SCF50% (top) and scatter plot between
SCF50% & R50% during spring for the QRB, 2000-2007 (bottom).
Quiz
Snow Microwave Sensors
 SMMR (scanning
multichannel microwave radiometer)
- It measured dual-polarized microwave radiances, at
6.63, 10.69, 18.0, 21.0, and 37.0 GHz, from the Earth's
atmosphere and surface.
 SSM/I (special
sensor microwave/imager)
-The instrument measures surface/atmospheric
microwave brightness temperature (TBs) at 19.35, 22.235,
37.0 and 85.5 GHz.
 AMSR-E ( Advanced Microwave Scanning Radiometer-EOS).
-12 channels and 6 frequencies ranging from 6.9 to
89.0 GHz. H-pol. and V-pol.
Energy Flux VS Intensity
 Energy flux is defined by the energy flow
with a given area [W/m2]
 Intensity is defined by the energy flow per a
given area, a given frequency, and a given
solid angle [W/m2 Hz Steradian ] – a
physically imaginary term but important for
the interpretation in Remote Sensing
Fraser River  Snow Dominant Watershed
1 mm grids, Salminen et al. 2009
Quiz
Passive vs. Active Sensing
Frolov and Marchert 1999, Hallikainen et al. 1986, TGRS
Key Words
Brightness Temperature
a
Absorption Coeffi.
Scattering Coeffi.
Ts
n
''
Matzler and Wiesmann 1999
Tb
pec
b

'
Real Permittivity

''
Imaginary
Permittivity
 s  s freq
LWC
Devonec and Barros 2002
Kang et al.
2012
Accepted in IEEE
Willis et al. 2012 RS and Env
Schanda and Matzler
1981
Derksen et al. 2012 RS env
Derksen et al. 2005, Chang et al. 1987
Time series (left) and scatter plots (right) of the observed & retrieved SWE from algorithms
using different AMSR-E channel combinations at Yanks Peak East from 2003-2005.
Conclusions
 Use Remote Sensing to cover global scale
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monitoring of snowpack
Visible and Microwave Remote Sensing of
Snowpack
Reflectance and Microwave Radiometry
Antenna Response Model VS Radiometry
observation
Wave signatures VS Snow physical properties