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IDENTIFICATION OF SNOWIDENTIFICATION OF SNOWUSING SAR POLARIMETRYUSING SAR POLARIMETRY

TECHNIQUESTECHNIQUES

G. SinghG. Singh a, c,a, c, *,*, Y. YamaguchiY. Yamaguchi bb, S.E. Park, S.E. Park aa and G.and G. VenkataramanVenkataramancc

aa Graduate School of Science and Technology, Niigata University, JapanGraduate School of Science and Technology, Niigata University, Japan

bb Department of Information Engineering, Niigata University, JapanDepartment of Information Engineering, Niigata University, Japancc CSRE, Indian Institute of Technology Bombay ,IndiaCSRE, Indian Institute of Technology Bombay ,India

*E*E--mail:mail: g.singh@wave.ie.niigatag.singh@wave.ie.niigata--u.ac.jpu.ac.jp

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Outline Introduction

Objectives

Data Used

Study Area

SAR Data Analysis of Snow Cover Area

Summary and Conclusions

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Introduction

Why is snow study important?Why is snow study important?

Snow Cover Area (SCA) extent 40%Snow Cover Area (SCA) extent 40%

area of land in NH (in Jan. month)area of land in NH (in Jan. month)

max. freshwatermax. freshwater

SCASCA 4% (in August )4% (in August ) (Rees,2005)(Rees,2005)

Can be used for various applicationsCan be used for various applications

e.g. Climate change studye.g. Climate change study

Snow hydrological studySnow hydrological study

Avalanche studyAvalanche study

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ObjectivesObjectives

SAR Polarimetric Analysis of snow coverSAR Polarimetric Analysis of snow cover

areaarea Identification of suitable parameters for

discriminating the snow pack

Comparison of incoherent target decompositiontheorems for snow classification

To be integrated decomposition parameters fordiscriminating snow cover: Radar snow indexdevelopment

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SAR Data UsedSAR Data Used

ENVISATENVISAT--ASAR(CASAR(C--band)band)

(HH/VV(HH/VV PolPol))

ALOSALOS--PALSAR (LPALSAR (L--band),band),

(Quad Pol)

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Study AreaStudy Area

Part of Himalayan snow covered terrainPart of Himalayan snow covered terrain

GangotriGangotri--BadrinathBadrinath regionregion

(due to availability of full(due to availability of full polarimetricpolarimetric data fromdata from

JAXA )JAXA )

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Advanced Visible and Near Infrared RadiometerAdvanced Visible and Near Infrared Radiometer--22

(AVNIR(AVNIR--2) Image over Badrinath area2) Image over Badrinath area

Satopanth Glacier(Uttrakhand, India)

Chirbatia

Glacier (Tibet)

06-05-2007

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SAR data analysis of Snow Cover

Area-Single polarization based-Multi polarization based

-Quad Polarization based

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Single polarization measurements

Rott et al. (1988)

Shi et al. (1994)

Nagler and Rott (2000) RaoRao et.al. (2006)et.al. (2006)

Rott, H., Matzler, N., Strobi, D., Bruzzi, S., and Lenhart, K., 1988. Study on SAR land applications for snow and glacier

monitoring. Contact Report 6618/85/F/FL(SC), ESA.Shi, J., Dozier, J., and Rott, H., 1994. Snow mapping in alpine regions with synthetic aperture radar. IEEE Transactions

on Geoscience and Remote Sensing, 32 152158.

Nagler, T., and Rott, H., 2000. Retrieval of wet snow by means of multitemporal SAR data. IEEE Transactions onGeoscience and Remote Sensing, 38, 754765.

Rao, Y.S., Venkataraman, G., and Singh, G., 2006. ENVISAT-ASAR data analysis for snow cover mapping overGangotri region. Proceedings of SPIE, 6410, 59-66. (doi:10.1117/12.693845).

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No correct classification is possible for foreshortening

/layover/shadow region

Some snow free area are misclassified as snow

covered, which may be caused by wet soil

Nagler and Rott (2000)

RaoRao et.al.et.al. (2006)(2006)

Total snow covered area are not possible to classifyTotal snow covered area are not possible to classify

Rott et al. (1988)

Shi et al. (1994)

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Repeat Pass Ratio Method for Snow discriminationRepeat Pass Ratio Method for Snow discrimination

(a) Snow map using ENVISAT-ASAR (19-05-2007)(b) to (g) snow map using

ALOS-PALSAR (12-05-2007)

(a) (VV) (b) VV (c) HH (d) HV (e) VH (f) HH/VH (g) HH/VV

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Problem with single Pol. SAR data forsnow mapping

AVNIR-2 (06-05-07) Snow Map (ASAR) Snow Map (PALSAR)

VVVV

19-05-07 12-05-07

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Problem with multiPol. SAR data forsnow mapping

AVNIR-2 (06-05-07) Snow Map (PALSAR) (HH/HV)

12-05-07

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PALSAR DataPALSAR Data

DecompositionDecomposition

ClassificationsClassifications

Polarimetric SignaturePolarimetric Signature

based PF values /based PF values /

EigenvaluesEigenvalues based PFbased PF

imageimage

Need for quad pol data capability analysis to discriminate snow

The coherent decomposition:The coherent decomposition:

(no change in target with time e.g. man made target)(no change in target with time e.g. man made target)

Incoherent decomposition:Incoherent decomposition:(distributed target, movement in target, natural targets)(distributed target, movement in target, natural targets)

--EigenvaluesEigenvalues Based (e.g. H/A/Alpha)Based (e.g. H/A/Alpha)

--Model Based (e.g.Model Based (e.g. Freeman,YamaguchiFreeman,Yamaguchi))

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H/A/Alpha Freeman Yamaguchi

A H

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1Snow (Cyan)

2.Rock (yellow)

3.DCG (Gold)

4.Vegetation/Forest

(Green)

5.Unidentified/

Layover (Black)

6.Settlements/

Double

bounce(Red)

H/A/Alpha Wishart supervised classified image

1.Snow (Cyan)

2.Rock (Gold)

3.DCG (Yellow)

4.Vegetation/Forest

(Green)

5. Unidentified/

Layover (Black)

6. Settlements/

Double bounce

(Red)

Yamaguchi model based Wishart supervised classified image

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Snow RockDebris Covered

Glacier (DCG)Settlement Vegetation Layover

Snow 95.26 0.00 0.43 0.00 0.00 4.31

Rock 0.25 78.07 14.42 0.00 3.33 3.93

DCG 1.19 5.82 81.70 0.00 6.77 4.51

Settlement 0.00 2.42 0.97 92.97 3.15 0.48

Vegetation 0.00 6.10 18.09 0.00 75.81 0.00

Layover 0.00 16.69 10.69 0.00 0.00 72.62H/A/ Wishart

supervised classified

Snow Rock DCG Settlement Vegetation Layover

Snow 98.55 0.33 0.36 0.00 0.43 0.32

Rock 5.26 79.25 0.00 1.45 14.04 0.00

DCG 0.00 0.00 86.58 0.00 2.24 11.18

Settlement 0.00 8.75 0.00 89.96 1.28 0.00

Vegetation 0.00 12.60 5.91 0.00 81.14 0.35

Layover 0.00 0.00 4.14 0.00 0.00 95.86

Modified 4-component -Wishart

supervised classified

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PolarimetricPolarimetric Signature andSignature and

Fractional Polarization ValueFractional Polarization Value Co-polarized and cross polarized polarimetricsignatures (3-D graphical)have been represented

by the synthesized backscatter response from

snow, rock, vegetation and other features. Fractional polarization (F),

minmax

minmax)(

PP

PPFonPolarizatiFractional

!

Where maximum (Where maximum (PmaxPmax) and minimum () and minimum (PminPmin) intensity value of the co) intensity value of the co--polarizationpolarization

or crossor cross--polarization components of the radar signalpolarization components of the radar signal

FFgives the polarization purity of return signalgives the polarization purity of return signal (Snow(Snow 85% (Co85% (Co--pol.), 93% (Xpol.), 93% (X--pol.);pol.);

VegetationVegetation 59%(Co59%(Co--polpol); Debris covered glacier); Debris covered glacier33% (co33% (co--pol.) etc.pol.) etc.))

[Singh et al., 2008][Singh et al., 2008]

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NO

YES

Generate PF value image

ALOS PALSAR Quad Polarization SLC Data

Multi-Looked (61) in (Azimuth Range)

and make Coherency Matrix (T3)

(HVVH)

Generate Eigenvalues Image (1, 2, 3)

PF0.5 & 3

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RSIRSI

EigenvalueEigenvalue basedbased polarizationpolarization fractionfraction

imageimage showsshows thatthat thethe snowsnow covercover areaarea hashas

highhigh polarizationpolarization fractionfraction valuevalue asas

comparedcompared toto otherother targetstargets

ItIt isis foundfound thatthat thethe lowerlower centralcentral partpart of of

imageimage showsshows highhigh PFPF valuevalue butbut thisthis partpart ofof

imageimage isis snowsnow freefree andand itit isis coveredcovered bybylayoverlayover affectedaffected areaarea duedue toto lowlow incidentincident

angleangle ofof ALOSALOS--PALSARPALSAR ((2323..5500)) andand highhigh

topographytopography ofof HimalayaHimalaya

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PF (Cyan >0.5 & Black

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ThereThere isis needneed toto exploreexplore supportingsupportingparametersparameters toto discriminatediscriminate snowsnow covercover

properlyproperly

EntropyEntropy (H),(H), anisotropyanisotropy (A),(A), scatteringscattering

mechanismmechanism angleangle (alpha),(alpha), ((11--H)H) andand HH ((11--

A),A), LunenburgLunenburg anisotropy,anisotropy, Radar Radar

VegetationVegetation IndexIndex (RVI)(RVI) havehave beenbeen studiedstudied

toto findfind outout whichwhich oneone cancan supportsupport thethe

resultsresults ofof snowsnow discriminationdiscrimination obtainedobtained

throughthrough polarizationpolarization fractionfraction

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AllAll ofof thesethese parametersparameters areare alsoalso capablecapable

ofof discriminatingdiscriminating snowsnow fromfrom otherother targetstargets

butbut dodo notnot havehave aa proper proper rangerange toto

suppresssuppress layoverlayover affectedaffected snowsnow freefree areaarea

fromfrom snowsnow

NormalizedNormalized 33 havehave widewide rangerange fromfrom 00 toto

11,, whichwhich isis ableable toto separateseparate thethe

topographictopographic distortiondistortion affectedaffected areaarea andand

otherother featuresfeatures

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Normalized 3

Cyan 0.015

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(a) (b) (c)

(a)H/A/Alpha classified (b) 4-component classified(c) RSI based Snow map

Problem with single/dualPol SAR data forsnow mapping - solvedby quadPol

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Summary and ConclusionsSummary and Conclusions

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Repeat Pass Ratio Method forRepeat Pass Ratio Method for

Snow discriminationSnow discrimination ItIt hashas beenbeen observedobserved thatthat snowsnow areaarea atat thetheaccumulationaccumulation regionregion ofof thethe glacierglacier (top(top

rightright sideside ofof thethe image)image) waswas classifiedclassified asas

snowsnow--freefree areaarea

VariousVarious combinationscombinations ofof polarizationspolarizations areare

exploredexplored andand foundfound thatthat allall combinationscombinations

withwith samesame polarizationpolarization areare suitablesuitable forfor wetwetsnowsnow mappingmapping onlyonly

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Single Pass MultiSingle Pass Multi--polarizationpolarization

Ratio MethodRatio Method

TheThe combinationcombination HH/HVHH/HV ratioratio imagesimages ofof

PALSARPALSAR givegive moremore informationinformation aboutabout totaltotalsnowsnow covercover

CoCo--polarizedpolarized HH/VVHH/VV ratioratio isis notnot aa goodgooddiscriminatordiscriminator forfor snowsnow classificationclassification

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Fully polarimetric SAR based methodFully polarimetric SAR based method

Using Wishart classifier,ALOS-PALSAR data have been

classified into major distinct classes viz., snow cover,

vegetation, debris covered glacier, rock and

layover/unidentified areas.

The user accuracy of snow classes is higher than otherclasses. Hence full polarimetric ALOS-PALSAR data is

useful for snow cover monitoring.

Furthermore, it was observed that user accuracy of snowis slightly better in four component decomposition based

classification as compared to H/A/Alpha based

classification .

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The PF value for snow is high as compared to other

features, which indicates that the return signal is

polarized or can be said that L- band ALOS PALSAR

data is capable of discriminating snow from other

targets. Based on the eigenvalues calculated,

polarization fraction image also shows that the snow

cover area has high polarisation fraction value as

compared to other target.

Finally, a novel Radar Snow Index is introduced by

integrating the decomposed parameters.

RSI does not require any training sample and

topographic information for snow discrimination from

other targets.