PASSIVE MICROWAVE TECHNIQUES FOR HYDROLOGICAL APPLICATIONS

by : P. Ferrazzoli Tor Vergata University Roma, Italy

ferrazzoli@disp.uniroma2.it

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