remote sensing in meteorology applications for snow yıldırım mete 110010231
TRANSCRIPT
Remote Sensing in Meteorology Applications for
Snow
Yıldırım METE 110010231
Topics in Remote Sensing of Snow
• Optics of Snow and Ice• Remote Sensing Principles• Applications • Operational Remote Sensing
FUNDAMENTALS OF REMOTE SENSING
A. Energy source
B. Atmospheric interactions
C. Target interactions
D. Sensor records energy
E. Transmission to receiving station
F. Interpretation
G. Application
The EM Spectrum10-1nm 1 nm 10-2m 10-1m 1 m 10 m 100 m 1 mm 1 cm 10 cm 1 m 102m
Gam
ma
Ray
s
X r
ays
Ultr
a-vi
olet
(UV
)
Vis
ible
(40
0 -
700n
m)
Nea
r In
frar
ed (
NIR
)
Infr
ared
(IR
)
Mic
row
aves
Wea
ther
rad
ar
Tel
evis
ion,
FM
rad
io
Sho
rt w
ave
radi
o
Vio
let
Blu
eG
ree
nY
ell
ow
Ora
ng
eR
ed
C = v, where c is speed of light, is wavelength (m),
And v is frequency (cycles per second, Hz)
C = v, where c is speed of light, is wavelength (m),
And v is frequency (cycles per second, Hz)
WAVELENGTHS WE CAN USE MOST EFFECTIVELY
Atmospheric absorptionand scattering
absorption
scattering
emission
RADIATION CHOICES
• Absorbed• Reflected• Transmitted
Properties of atmosphereand surface
• Conservation of energy: radiation at a given wavelength is either:– reflected — property of surface or medium is called
reflectance or albedo (0-1)– absorbed — property is absorptance or emissivity
(0-1)– transmitted — property is transmittance (0-1)
reflectance + absorptance + transmittance = 1(for a surface, transmittance = 0)
PIXELS: Minimum sampling area
One temperature brightness (Tb) value recorded per pixel
One temperature brightness (Tb) value recorded per pixel
EM Wavelengths for Snow
• Snow on the ground– Visible, near infrared, infrared– Microwave
• Falling snow– Long microwave, i.e., weather radar
• K ( = 1cm)• X ( = 3 cm)• C ( = 5 cm)• S ( = 10 cm)
Different Impacts in Different Regions of the Spectrum
Visible, near-infrared, and infrared
• Independent scattering
• Weak polarization
– Scalar radiative transfer
• Penetration near surface only
– ~½ m in blue, few mm in NIR and IR
• Small dielectric contrast between ice and water
Microwave and millimeter wavelength
• Extinction per unit volume
• Polarized signal
– Vector radiative transfer
• Large penetration in dry snow, many m
– Effects of microstructure and stratigraphy
– Small penetration in wet snow
• Large dielectric contrast between ice and water
Visible, Near IR, IR
Solar Radiation
Instrument records temperature brightness at certain wavelengths
Instrument records temperature brightness at certain wavelengths
Snow Spectral Reflectance
0
20
40
60
80
100
0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4
refl
ec
tan
ce
(%
)
0.05 mm0.2 mm0.5 mm1.0 mm
wavelength (m)
General reflectance curves
from Klein, Hall and Riggs, 1998: Hydrological Processes, 12, 1723 - 1744 with sources from Clark et al. (1993); Salisbury and D'Aria (1992, 1994); Salisbury et al. (1994)
Refractive Index of Light (m)
• m = n + ik• The “real” part is n• Spectral variation of n is
small• Little variation of n
between ice and liquid
Attenuation Coefficient
• Attenuation coefficient is the imaginary part of the index of refraction
• A measure of how likely a photon is to be absorbed
• Little difference between ice and liquid
• Varies over 7 orders of magnitude from 0.4 to 2.5 uM
ADVANCED VERY HIGH RESOLUTION RADIOMETER
(AVHRR)
• 2,400 km swath• Orbits earth 14 times per day, 833 km height• 1 kilometer pixel size• Spectral range
– Band 1: 0.58-0.68 uM– Band 2: 0.72-1.00 uM– Band 3: 3.55-3.93 uM– Band 4: 10.5-11.5 uM
Snow Measurement
• Satellite Hydrology Program
WAVELENGTH (microns)
WAVELENGTH (microns)AVHRR
GOES
0.0 1.0 4.02.0 3.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0
0.0 1.0 4.02.0 3.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0
AVHRR and GOES Imaging Channels
Snow Measurement• Remote Sensing of Snow Cover
0.0 0.5 1.0 1.5 2.0 2.5 3.0
WAVELENGTH (microns)
0.0
0.2
0.4
0.6
0.8
1.0
AVHRR Ch. 2AVHRR Ch. 1
GOESCh. 1
r = 0.05 mmr = 0.2 mmr = 0.5 mmr = 1.0 mm
Snow Grain Radius (r)
OpticallyThick
Clouds
1.6 micron
0.0 0.5 1.0 1.5 2.0 2.5 3.0
WAVELENGTH (microns)
0.0
0.2
0.4
0.6
0.8
1.0
AVHRR Ch. 2AVHRR Ch. 1
GOESCh. 1
r = 0.05 mmr = 0.2 mmr = 0.5 mmr = 1.0 mm
Snow Grain Radius (r)
OpticallyThick
Clouds
1.6 micron(NOAA 16)
Snow Measurement• NOAA-15 1.6 Micron Channel
Mapping of snow extent
• Subpixel problem– “Snow mapping” should estimate fraction of pixel
covered
• Cloud cover– Visible/near-infrared sensors cannot see through
clouds– Active microwave can, at resolution consistent
with topography
• Assuming linear mixing, the spectrum of a pixel is the area-weighted average of the spectra of the “end-members”
• For all wavelengths ,
• Solve for fn
Analysis of Mixed PixelsAnalysis of Mixed Pixels
R r fn nn
N
1
Subpixel Resolution Snow Mapping from AVHRR
Subpixel Resolution Snow Mapping from AVHRR
May 26, 1995
(AVHRR has 1.1 km spatial resolution, 5 spectral bands)
AVHRR Fractional SCA Algorithm
1
2
3
4
5
AVHRR (HRPT FORMAT)Pre-Processed at UCSB[NOAA-12,14,16]
Snow Map Algorithm Output: Mixed clouds, high reflective bare ground, and Sub-pixel snow cover
AVHRR Bands
Geographic Mask
Thermal Mask
Masked Fractional SCA Map
Composite Cloud Mask
Build Cloud Masks using several
spectral-based tests
Execute Atmospheric Corrections,
Conversion to engineering units
Execute Sub-pixel snow cover algorithm
using reflectance Bands 1,2,3
Application of Cloud, Thermal, and Geographic masks to raw
AVTREE output
Build Thermal Mask
Scene Evaluation: Degree of Cloud Cover
over Study Basins
Landsat Thematic Mapper (TM)
• 30 m spatial resolution
• 185 km FOV• Spectral resolution
1. 0.45-0.52 μm2. 0.52-0.60 μm3. 0.63-0.69 μm4. 0.76-0.90 μm5. 1.55-1.75 μm6. 10.4-12.5 μm7. 2.08-2.35 μm
• 16 day repeat pass
Subpixel Resolution Snow Mapping from Landsat Thematic Mapper
Subpixel Resolution Snow Mapping from Landsat Thematic Mapper
Sept 2, 1993(snow in cirques only)
Feb 9, 1994(after big winter storm)
Apr 14, 1994(snow line 2400-3000 m)
(Rosenthal & Dozier, Water Resour. Res., 1996)
Discrimination between Snow and Glacier Ice, Ötztal Alps
Discrimination between Snow and Glacier Ice, Ötztal Alps
Landsat TM, Aug 24, 1989 snow ice rock/veg
AVIRIS CONCEPT
• 224 different detectors• 380-2500 nm range• 10 nm wavelength• 20-meter pixel size• Flight line 11-km wide• Flies on ER-2• Forerunner of MODIS
AVIRIS spectraAVIRIS spectra
0
20
40
60
80
100
0.3 0.8 1.3 1.8 2.3wavelength (m)
refl
ec
tan
ce
(%
)
snow
vegetation
rock
Spectra of Mixed PixelsSpectra of Mixed Pixels
0
20
40
60
80
100
0.3 0.8 1.3 1.8 2.3wavelength (m)
refl
ec
tan
ce
(%
)
snow
vegetation
rock
equal snow-veg-rock
80% snow, 10% veg, 10% rock
20% snow, 50% veg, 30% rock
Subpixel Resolution Snow Mapping from AVIRIS
Subpixel Resolution Snow Mapping from AVIRIS
(Painter et al., Remote Sens. Environ., 1998)
GRAIN SIZE FROM SPACE
EOS Terra MODIS
•Image Earth’s surface every 1 to 2 days
•36 spectral bands covering VIS, NIR, thermal
•1 km spatial resolution (29 bands)
•500 m spatial resolution (5 bands)
•250 m spatial resolution (2 bands)
•2330 km swath
Snow Water EquivalentSnow Water Equivalent
• SWE is usually more relevant than SCA, especially for alpine terrain
• Gamma radiation is successful over flat terrain
• Passive and active microwave are used• Density, wetness, layers, etc. and vegetation
affect radar signal, making problem more difficult
SWE from Gamma
• There is a natural emission of Gamma from the soil (water and soil matrix)
• Measurement of Gamma to estimate soil moisture
• Difference in winter Gamma measurement and pre-snow measurement – extinction of Gamma yields SWE
• PROBLEM: currently only Airborne measurements (NOAA-NOHRSC)
Snow Measurement• Airborne Snow Survey Program
Natural Gamma Sources
238U Series, 232Th Series, 40K SeriesSoil
Snow
Atmosphere
Radon Daughtersin Atmosphere
Cosmic Rays
Uncollided
Gamma RadiationAbsorbed by Waterin the Snow Pack
Gamma Radiationreaches
Detector in Aircraft
Scattering
Natural Gamma Sources
238U Series, 232Th Series, 40K SeriesSoil
Snow
Atmosphere
Radon Daughtersin Atmosphere
Cosmic Rays
Uncollided
Gamma RadiationAbsorbed by Waterin the Snow Pack
Gamma Radiationreaches
Detector in Aircraft
Scattering
Snow Measurement
• Airborne SWE Measurement Theory– Airborne SWE measurements are made using
the following relationship:
SW EA
C
C
M
Mg cm
1 1 0 0 1 11
1 0 0 1 110
0
2ln ln.
.
Where:
C and C0 = Uncollided terrestrial gamma count rates over snow and dry, snow-free soil,
M and M0 = Percent soil moisture over snow and dry, snow-free soil,
A = Radiation attenuation coefficient in water, (cm2/g)
Snow Measurement
• Airborne SWE: Accuracy and Bias
Airborne measurements include ice and standing water that ground measurements generally miss.
RMS Agricultural Areas: 0.81 cmRMS Forested Areas: 2.31 cm
Airborne Snow Survey Products
Microwave Wavelengths
Frequency Variation for Dielectric Function and Extinction Properties
• Variation in dielectric properties of ice and water at microwave wavelengths
• Different albedo and penetration depth for wet vs. dry snow, varying with microwave wavelength
• NOTE: typically satellite microwave radiation defined by its frequency (and not wavelength)
Dielectric Properties of Snow
Material Dielectric Constant
Air 1.0
Ice 3.2
Quartz 4.3
Water 80
• Propagation and absorption of microwaves and radar in snow are a function of their dielectric constant
• Instrumentation: Denoth Meter, Finnish Snow Fork, TDR
• e = m2 and also has a real and an imaginary component
Modeling electromagnetic scattering and absorption
Soil
(1) (2) (3) (4) (5) (6)
Snow
Volume Scattering
• Volume scattering is the multiple “bounces” radar may take inside the medium
• Volume scattering may decrease or increase image brightness
• In snow, volume scattering is a function of density
SURFACE ROUGHNESS
• Refers to the average height variations of the surface (snow) relative to a smooth plane
• Generally on the order of cms
• Varies with wavelength and incidence angle
SURFACE ROUGHNESS
• A surface is “smooth” if surface height variations small relative to wavelength
• Smooth surface much of energy goes away from sensor, appears dark
• Rough surface has a lot of back scatter, appears lighter