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Microwave Remote Sensing of Snowpack

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Title: Microwave Remote Sensing of Snowpack


1
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

Discovery and Acceleration Fund
2
Outline
  • 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 DĂ©ry)

3
  • 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).

4
  • 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)

5
Electromagnetic Radiation
6
Interactions with the Atmosphere
Scattering
Absorbing
7
  • Those areas of the spectrum which are not
    severely influenced by atmospheric absorption and
    thus, are useful to remote sensors, are called
    atmospheric windows

8
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.

9
  • water and vegetation may reflect somewhat
    similarly in the visible wavelengths but are
    almost always separable in the infrared.

10
Passive vs. Active Remote Sensing
Passive Sensing
Active Sensing
11
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.

12
Satellite Orbits
Geostationary orbits
Near-polar orbit
Ascending vs Descending
13
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)

14
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)

15
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)
16
Quiz
17
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.

18
Evaluation of MODIS data
MODIS
Snow No snow
Snow a b
No snow c d
Ground
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
19
Results
Snow cover fraction ()
The spatially filtered snow cover fraction (SCF)
for different elevation bands (top) and aspects
with slopes gt 15o (bottom), 2000-2007.
20
The mean elevational dependence of snow cover
fraction (SCF) for the months of February to
July, 2000-2007.
21
The annual snow cover duration (x3 days) in the
QRB based on spatially filtered (SF) MODIS snow
products, 2001-2007.
Mean snow cover durations (SCD) for 10-m
elevation bands from the MOD10A2 () SF (?)
products, 2001-2007.
SCD (days)
r 0.96 d(SCD)/dz 11.6 days (100 m)-1
22
Scatter plot between average air temperature and
SCF50 (top) and scatter plot between SCF50
R50 during spring for the QRB, 2000-2007
(bottom).
23
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24
Quiz
25
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.

26
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

27
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28
Fraser River ? Snow Dominant Watershed
29
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30
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31
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32
1 mm grids, Salminen et al. 2009
33
Quiz
34
Passive vs. Active Sensing
35
Frolov and Marchert 1999, Hallikainen et al.
1986, TGRS
36
Key Words
Tb
Brightness Temperature
Real Permittivity
Absorption Coeffi.
Imaginary Permittivity
Scattering Coeffi.
Tb
Ts
pec
LWC
freq
Matzler and Wiesmann 1999
Devonec and Barros 2002
37
Kang et al. 2012 Accepted in IEEE
Willis et al. 2012 RS and Env
Schanda and Matzler 1981
38
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39
Derksen et al. 2012 RS env
40
Derksen et al. 2005, Chang et al. 1987
41
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.
42
Conclusions
  • Use Remote Sensing to cover global scale
    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
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