PASSIVE MICROWAVE TECHNIQUES FOR HYDROLOGICAL APPLICATIONS by : P. Ferrazzoli Tor Vergata University Roma, Italy [email protected]
Jan 23, 2016
PASSIVE MICROWAVE TECHNIQUES FOR HYDROLOGICAL APPLICATIONS
by : P. Ferrazzoli Tor Vergata University Roma, Italy
CLASSIFICATION OF REMOTE SENSING INSTRUMENTS
Based on physical processes
CLASSIFICATION OF REMOTE SENSING INSTRUMENTS: Summary
Active Passive
Optical/UV Lidar RadiometerMicrowave Radar Radiometer
PASSIVE SYSTEMS: the emission process
Background: every surface, at T>0 K, emits electromagnetic power
PASSIVE SYSTEMS: the emission process at microwaves
Brightness:
Black body brightness:
Brightness temperature (definition):
Microwave emissivity:
kT
hc
kT
hc
1exp
),,,(),,,( TIdf
dTfI
4
2),(
ckTTB
2
22),(),(
c
TkfTB
df
dTfB
2
2
2
),,,(),,,(
kf
cTfITfTB
T
TfT
TfB
TfIfe B ),,,(
),(
),,,(),,(
PASSIVE SYSTEMS: the emission process Reciprocity
Reflectivity: R(f, θ,φ)= Pr / Pi
(reflectance)
Absorbivity: A(f, θ,φ) = Pa / Pi = 1- R(f, θ,φ)(absorbance)
Kirchhoff (reciprocity) law: e(f, θ,φ) = A(f, θ,φ)
Pi
Pa
Pr
R
rr
rrEVV
R
r
rEHH
fqe
fqe
2
2
22
2
2
22
sincos
sincos11
sincos
sincos11
Horizontal polarization
Vertical polarization
'''rrr j depends on volumetric soil moisture (SM)
Rf is a roughness factor
SOILSImportant for applications: εr is stongly influenced by moisture.
Real and imaginary parts of soil permittivity as a function of volumetric soil moisture content (SMC) at 1.4 GHz (L band)Measured values
(by Ulaby, Moore, Fung, 82)
GENERAL PROPERTIES OF EMISSIONFROM NATURAL MEDIA
Emissivity of flat surfaces vs. angle (computations)(by Ulaby, Moore, Fung, 82)
Increasing moisture,
ε increases,Reflectivity increases,Emissivity decreases
BARE SOILS
Emissivity vs. angle, L band (1.4 GHz) Ground based measurements (by Ulaby, Moore, Fung, 82)
moistureConstant roughness,Moisture variations
BARE SOILSEmissivity vs. angle, L band (1.4 GHz) Ground based measurements (by Ulaby, Moore, Fung, 82)
Constant moisture,Roughness variations
roughness
e1 = (1-) [1- exp(- σev h sec)] e2 = (1-) [1- exp(- σev h sec)] exp(- σev h sec) rs e3 = es exp(- σev h sec)
: vegetation “albedo” τ = σev h (“optical depth”)es : soil emissivity rs : soil reflectivity (rs =1 – es)
VEGETATION COVERED SOILSe3 e1 e2
e=e1+e2+e3
RECENT MICROWAVE INSTRUMENTS
Spaceborne radiometric systems launch bands (GHz)AMSR-E 2002 6.9, 10.6, 18,21,37, 89 SMOS 2009 1.4
SMOSLaunch: 2009
Spatial resolution: 35-50 km (suitable to studies at global scale)
Rivisit time: 3 days
Goal in soil moisture retrieval accuracy: 4%
To improve spatial resolution:
Interpherometric technique:69 small antennas located on 3 long arms
“The BIG Y”
For each pixel:Simultaneous measurements at V and H polarization, 20°< θ <60°
Estimating soil moisture in the root zone is important: •short- and medium-term meteorological modelling, •hydrological modelling, •monitoring of plant growth, •forecasting of hazardous events such as floods.
By ESA SMOS site http://www.esa.int/esaLP/LPsmos.html
The soil-vegetation-atmosphere transfer (SVAT) schemes used in meteorology and hydrology are designed to describe the basic evaporation processes at the surface, the water partitioning between vegetation transpiration, drainage, surface runoff and soil moisture variations.
At present, soil moisture maps are simulated and forecasts are generatedby modelsObjective of SMOS: maps improvement, maps update
By ESA SMOS site http://www.esa.int/esaLP/LPsmos.html
The retrieval process
-Initial estimate of SM and Leaf Area Index LAI (ECMWF and ECOCLIMAP data bases)- Models for τ(LAI) and eS (SM)-For each angle () and polarization: TB = TS(1-) [1- exp(- τ sec)] [1+exp(- τ sec) (1-es)] +TS es exp(- τ sec)
-Compare initial simulations with measurements-Start an iterative process-Adjust SM in order to obtain the minimum rms difference between simulations and measurements.
Tests:
Multitemporal over single sitesGlobal in selected dates
World map of retrieved Optical depth
World map of retrieved Soil moisture
AMSR-EConical scanning. Local incidence angle: 55°
Application: flood monitoring
Test area: Sundarbans delta
Polarization Index:
Polarization Index:
Increases with soil moisture, decreases with vegetation height
Sensitive to floodingBest frequencies: C and X band
PI maps
Multitemporal PI trends in 2005, all bands
PI vs. Day of Year
Measured water level
Multitemporal PI trends in all years, X band
PI vs. Day of Year
Measured water level
Correlation PI vs. water level
References
• F.T. Ulaby, R.K. Moore, A.K. Fung, “Microwave Remote Sensing. Active and Passive, Vol. II” Addison Wesley, Reading (USA), 1982
• F.T. Ulaby, R.K. Moore, A.K. Fung, “Microwave Remote Sensing. Active and Passive, Vol. III” Artech House, Dedham (USA), 1986
• ESA Living Planet Programme – SMOS http://www.esa.int/esaLP/LPsmos.html