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SatelliteSoilMoistureRetrieval
SatelliteSoilMoisture Retrieval
TechniquesandApplications
Editedby
PrashantK.Srivastava
NASAGoddardSpaceFlightCenter,USA andInstituteofEnvironmentandSustainableDevelopment, BanarasHinduUniversity,India
GeorgeP.Petropoulos
Geography&EarthSciences
AberystwythUniversity
Aberystwyth,SY233DB Wales,UK
YannH.Kerr
CESBIO
Toulouse,France
Elsevier
Radarweg29,POBox211,1000AEAmsterdam,Netherlands TheBoulevard,LangfordLane,Kidlington,OxfordOX51GB,UK 50HampshireStreet,5thFloor,Cambridge,MA02139,USA
Copyright © 2016ElsevierInc.Allrightsreserved.
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Thisbookandtheindividualcontributionscontainedinitareprotectedundercopyrightbythe Publisher(otherthanasmaybenotedherein).
Notices
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ISBN:978-0-12-803388-3
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Iwouldliketodedicatethisbooktomyparents,BishwambharNSrivastavaand NirmalaDevi,aswellastomybelovedwifeManikafortheircontinuous support
—PrashantK.Srivastava
Idedicatethisbooktomyparents,PanagiotisandEvgenia,fortheircontinuing loveandsupportinalltheendeavorsofmylife
—GeorgeP.Petropoulos
Iwouldliketodedicatethisbooktomywifeandchildrenfortheirpatienceand understandingaswellastomycolleaguesfortheirsignificantcontributions
—YannH.Kerr
ListofContributors
Numbersinparenthesisindicatethepagesonwhichtheauthors’contributionsbegin.
R.Akbar(187),MingHsiehDepartmentofElectricalEngineering,Universityof SouthernCalifornia,LosAngeles,CA
A.AlBitar(3,351),Centred’EtudesSpatialesdelaBiosphere,Toulouse,France
V.Anagnostopoulos(91),NationalTechnicalUniversityofAthens;InfoCosmosLtd, Athens,Greece
B.Barrett(209),UniversityCollegeCork(UCC),Cork,Ireland
A.Berg(47),UniversityofGuelph,Guelph,ON,Canada
N.Berni(231),CivilProtectionCentre,Foligno,Italy
L.Brocca(231,351),NationalResearchCouncil;ResearchInstituteforGeo-Hydrological Protection,NationalResearchCouncil,Perugia,Italy
D.Chaparro(249),UniversitatPolitecnicadeCatalunya,IEEC/UPC;Barcelona ExpertCenter,InstituteofMarineSciences,CSIC,Barcelona,Spain
L.Ciabatta(231),NationalResearchCouncil,Perugia,Italy
Q.Dai(289),NanjingNormalUniversity,Nanjing,China
N.Das(187),NASA/JetPropulsionLaboratory(JPL),Pasadena,CA
E.DeWitte(379),AirbusDefenceandSpaceLtd,Stevenage,UnitedKingdom
E.Dwyer(209),EurOcean—EuropeanCentreforInformationonMarineScienceand Technology,Lisbon,Portugal
D.Entekhabi( 187),DepartmentofCivilandEnvironmentalEngineering, MassachusettsInstituteofTechnology,Cambridge,MA
F.Gerard(379),CentreforEcology&Hydrology,Wallingford,UnitedKingdom
N.Ghilain(309),RoyalMeteorologicalInstituteofBelgium,Brussels,Belgium
H.Griffiths(91),DepartmentofGeography&EarthSciences,Ceredigion,Wales, UnitedKingdom
A.Gruber(209),ViennaUniversityofTechnology,Vienna,Austria
D.K.Gupta(159,333),IndianInstituteofTechnology(BHU),Varanasi,India
M.Gupta(29,271,333),NASAGoddardSpaceFlightCenter,Greenbelt,MD, UnitedStates
D.Han(289),UniversityofBristol,Bristol,UnitedKingdom
C.Hodges(91),GeoSmartDecisionsLtd,Llanidloes,Powys,UnitedKingdom
M.Holzman(73),ConsejoNacionaldeInvestigacionesCientı´ficasyTecnicas –InstitutodeHidrologı´adeLlanuras“Dr.EduardoJ.Usunoff”,Rep.Italia780,Azul, BuenosAires,Argentina
G.Ireland(91),DepartmentofGeography&EarthSciences,Ceredigion,Wales, UnitedKingdom
T.Islam(29,91,159,271,289,333),NASAJetPropulsionLaboratory;California InstituteofTechnology,Pasadena,CA,UnitedStates
J.C.Jimenez-Mun ˜ oz(135),UniversitatdeValencia,Valencia,Spain
D.Kalivas(91),AgriculturalUniversityofAthens,Athens,Greece
Y.H.Kerr(3),Centred’EtudesSpatialesdelaBiosphere,Toulouse,France
C.Mattar(135),UniversityofChile,Santiago,RM,Chile
A.Mialon(3),Centred’EtudesSpatialesdelaBiosphere,Toulouse,France
V.Mironov(169),KirenskyInstituteofPhysics,Krasnoyarsk,Russia
M.Moghaddam(187),MingHsiehDepartmentofElectricalEngineering,University ofSouthernCalifornia,LosAngeles,CA
T.Moramarco(231),NationalResearchCouncil,Perugia,Italy
J.Mun ˜ oz-Sabater(351),EuropeanCentreforMediumRangeWeatherForecasts, Reading,UnitedKingdom
V.Pandey(29),BanarasHinduUniversity,Banaras,India
A.Petrie(379),CentreforEcology&Hydrology,Wallingford,UnitedKingdom
G.P.Petropoulos(91,333),DepartmentofGeography&EarthSciences,Ceredigion, Wales,UnitedKingdom
M.Piles(109,249),UniversitatPolitecnicadeCatalunya,IEEC/UPC;Barcelona ExpertCenter,InstituteofMarineSciences,CSIC,Barcelona,Spain
F.Ponziani(231),CivilProtectionCentre,Foligno,Italy
R.Prasad(159,333),IndianInstituteofTechnology(BHU),Varanasi,India
C.Pratola(209),UniversityCollegeCork(UCC),Cork,Ireland
P.Rahimzadeh-Bajgiran(47),UniversityofMaine,Orono,ME,UnitedStates
R.Rivas(73),Comisio ´ ndeInvestigacionesCientı´ficasdelaprovinciadeBuenos Aires – InstitutodeHidrologı´adeLlanuras“Dr.EduardoJ.Usunoff”,Campus Universitario,Tandil,BuenosAires,Argentina
A.Santamarı´a-Artigas(135),UniversityofChile,Santiago,RM,Chile
I.Savin(169),KirenskyInstituteofPhysics,Krasnoyarsk,Russia
S.K.Singh(333), University ofAllahabad,Allahabad,India
N.Sa ´ nchez(109),UniversityofSalamanca/CIALE,Villamayor,Spain
J.A.Sobrino(135),UniversitatdeValencia,Valencia,Spain
ListofContributors xix
P.K.Srivastava(3,29,91,159,271,333),NASAGoddardSpaceFlightCenter, Greenbelt,MD,UnitedStates;BanarasHinduUniversity,Banaras,India
S.Suman(29),BanarasHinduUniversity,Banaras,India
E.Tebbs(379),King’sCollegeLondon,DepartmentofGeography,Strand,London, UnitedKingdom
M.Vall-llossera(249),UniversitatPolitecnicadeCatalunya,IEEC/UPC;Barcelona ExpertCenter,InstituteofMarineSciences,CSIC,Barcelona,Spain
W.Wagner(231),ViennaUniversityofTechnology,Vienna,Austria
W.Z.WanJaafar(333),UniversityofMalaya,KualaLumpur,Malaysia
J.-P.Wigneron(3),INRAISPA,Bordeaux,France
L.Zhuo(289),UniversityofBristol,Bristol,UnitedKingdom
AuthorBiographies
PrashantK.Srivastava ispresentlyworking inHydrologicalSciences,NASAGoddard SpaceFlightCenteronSMAPsatellitesoil moistureretrievalalgorithmdevelopment, instrumentation,andsimulationforvarious applications,andaffiliatedwithIESD,BanarasHinduUniversityasafaculty.Hereceived hisPhDdegreefromDepartmentofCivil Engineering,UniversityofBristol,Bristol, UK.Hisprimaryresearchfocusesonthe useofopticalandmicrowavesatellitesynergywithWeatherResearchandForecasting forhydrologicalapplications.Heisalsoa workinggrouppartnerwithNASAJPLon SMAPsoilmoisturecalibrationandvalidation.HehasbeenarecipientofseveralawardssuchasUniversityofMaryland Fellowship,USA;CommonwealthFellowship,UK;CSIR-UGC-JRF-NET (2005),CSIR-JRF-NET(2006),UniversityGrantCommission(UGC)-NET (2006),andMinistryofHumanResourceDevelopmentfellowshipsfromIndia. Hehas100+publicationsinpeer-reviewedjournals,published4bookswith reputedpublishinghousessuchasSpringer,TaylorandFrancis,andElsevier andpublishedseveralbookchapters.Heisalsoactingaseditoroffewjournals andiscurrentlyamemberofIndianSocietyofGeomatics,IndianSocietyof RemoteSensing,IndianAssociationofHydrologists(IAH),InternationalSocietyforAgrometeorology(INSAM),InternationalAssociationofHydrological Sciences(IAHS),andfewothers.
GeorgeP.Petropoulos isaseniorlecturerin RemoteSensing&GISatAberystwythUniversity,UK.Hecompletedhisgraduatestudies(MSc,PhD)attheUniversityofLondonin 2008,specializinginEarthObservation(EO) Modelling.HisPhDwasfocusingspecifically intheretrievalsofenergyfluxesandsoil moisturefromthesynergyofopticalEOdata withsimulationprocessmodels.
Petropoulos’researchfocusesonexploitingEOdataaloneorsynergisticallywithland surfaceprocessmodelsforcomputingkey statevariablesoftheEarth’senergyandwater budget,includingenergyfluxesandsoilsurfacemoisture.Heisalsoconductingresearch ontheapplicationofremotesensingtechnologytolandcovermappingandits changesoccurredfromeitheranthropogenicactivitiesorgeohazards(mainly floods,wildfires,frost).Inthisframework,hecontributestothedevelopment ofopensourcesoftwaretoolsinEOmodellinganddevelopsandimplements all-inclusivebenchmarkingapproachestoeitherEOoperationalalgorithms/ productsorsurfaceprocessmodels,includingadvancedsensitivityanalysis.
PetropoulosservesasaCouncilmemberoftheRemoteSensing&PhotogrammetricSociety(RSPSoC),EditorialBoardmemberonseveralinternational peer-reviewedscientificjournalsinEOandenvironmentalmodelling,andas areviewerforvariousfundingbodies(includingtheEuropeanCommission). Heiseditor/co-editorof2books,author/co-authorof +50 peer-reviewedjournal articlesandof +90 internationalconferences.Hehasdevelopedfruitfulcollaborationswithkeyscientistsinhisareaofspecializationglobally,andhisresearch worksofarhasreceivedinternationalrecognitionviaseveralnoteworthyawards hehasobtained.
YannH.Kerr receivedtheengineering degreefromEcoleNationaleSuperieurede l’Aeronautiqueetdel’Espace,theMScdegree inelectronicsandelectricalengineeringfrom GlasgowUniversity,Glasgow,Scotland,UK, andthePhDdegreeinAstrophysiqueGeophysiqueetTechniquesSpatiales,Universite PaulSabatier,Toulouse,France.Affiliatedto theFrenchspaceagency(CNES)since1980, hejoinedLERTSin1985;forwhichhewas directorin1993–94.Hespent19monthsat JPL,Pasadena,in1987–88.HehasbeenworkingatCESBIOsince1995asdeputydirector (1995–99)anddirector(2007–16).
Hisfieldsofinterestareinthetheoryand techniquesformicrowaveandthermalinfraredremotesensingoftheEarth, withemphasisonhydrology,waterresourcesmanagement,andvegetation monitoring.
HewasanEOSprincipalinvestigator(interdisciplinaryinvestigations),and PIandprecursoroftheuseoftheSCAToverland.In1989,hestartedtoworkon theinterferometricconceptappliedtopassivemicrowaveearthobservationand wassubsequentlythescienceleadontheMIRASforESA.Heisamemberof theSMAPScienceTeam.In1997,hefirstproposedthenaturaloutcomeofthe previousMIRASworkwithwhatwastobecometheSMOSMissionselectedby ESAin1999withhimastheSMOSmissionlead-investigatorandchairofthe ScienceAdvisoryGroup.HehasorganizedalltheSMOSworkshopsandwas guesteditorontwoIEEEandoneRSEspecialissues.Heisalsoworkingonthe SMOS-Nextconcept.HereceivedtheWorldMeteorologicalOrganization 1stprize(NorbertGerbier),theUSDASecretary’steamawardforexcellence (SalsaProgram),theGRSScertificateofrecognitionforleadershipindevelopmentofthefirstsyntheticaperturemicrowaveradiometerinspaceandsuccess oftheSMOSmission,andtheESAteamaward.
Preface
Informationonourplanet’ssoilmoistureisindispensabletoanumberofpracticalapplicationsrelatedtofoodsecurity,society,andecosystems.Itplaysan importantroleintheEarth’swatercycle;itisakeyvariableinthewaterand energyexchangesthatoccurattheland-surface/atmosphereinterfaceandconditionstheevolutionofweatherandclimateovercontinentalregions.Therefore,globally,themonitoringofthesoilmoisturehasdevelopedintoavery importantandurgentresearchdirection,especiallytowardswaterresource management,irrigationscheduling,improvedweatherforecasts,natural hazardsmitigationanalysis,predictionsofagriculturalproductivity,crop insurance,climatepredictions,ecologicalhealthandservices,improvedtrafficability,groundwaterrecharge,waterqualityandquantity,etc.Inthiscontext, thereisagrowingneedofmonitoringandunderstandingthesoilmoisture retrievaltechniquesanditsapplications.Thiscanbeofcrucialimportance,particularlytoregionsonwhichtheamountofwateravailableislimited.
Thisbookismotivatedbythedesiretosolvetheproblemofsoilmoisture retrievalsinacosteffectiveandtimelyway.ThelaunchofadvancedEarthObservation(EO)satellitesinoptical/IRandmicrowavedomainhasthepotentialto reshapethesoilmoistureretrievalsystemandcanbeusedtomonitorsoilmoisture regularly,accurately,andinrealtime.Thesesatellites/instrumentsprovidenecessarydatathatcanmakeupforthelackofon-the-groundmonitoringofsoilmoisture aroundtheworldandbecauseofsubstantialimportanceofsoilmoisturebothESA andNASAhavelaunchedfullydedicatedsoilmoisturesatellitesknownasSMOS andSMAP,respectively,toprovideabetterestimatesoilmoistureovertheglobe.
Afterthelaunchofmanysophisticatedsatellites(suchasSSM,AMSRE/2, SMOS,ASCAT,Aquarius,SMAP,Landsatseries,MODIS,andmanyothers),soil moistureretrievaltechniqueshavegainedconsiderablemomentumamongthe earthandenvironmentalsciencecommunitiesforsolvingandunderstandingvariouscomplexproblems.Inthisessence,acomprehensivebookisneededdevoted toputtingtogetheracollectionoftherecentdevelopmentsandrigorousapplicationsofthesoilmoisturefromoptical/infraredandmicrowavesatellites.Inorder tounderstandtheretrievalsystemandapplications,thebookisdesignedto advancethescientificunderstanding,development,andapplicationofsoilmoistureretrievaltechniques,anditsapplicationsforvariousenvironmentalproblems. Thisbookwillpromotethesynergisticandmultidisciplinaryactivitiesamongscientists.Therefore,wewouldconsiderthisamustreadbookthatpromotesthe
synergisticandmultidisciplinaryactivitiesamongscientistsandusersworkingin thefieldofhydrometeorologicalsciencesandotherrelateddisciplines.
Thebookbecomespossiblebecauseofextensiveandvaluablecontributions frominterdisciplinaryexpertsfromallovertheworldinthefieldofsoilmoistureretrievalsandapplications.Inordertosimplifythesoilmoistureretrieval techniquesandapplicationsformostofthestudentsandresearchers,thisbook focusedonthreeworkingmethodologies, viz,theory,abstraction,andapplicationsastheyarefundamentaltoallresearchprograms.Thebookhas beendividedintofivesections.SectionIcontainsIntroduction,SectionII detailstheOpticalandInfraredTechniquesandSynergiesBetweenThem, SectionIIIprovidesseveralmethodologiesforMicrowaveSoilMoisture RetrievalwhileSectionsIVandVdealwithAdvanceApplicationofSoil MoistureandFutureChallengesinSoilMoistureRetrievalandApplications.
Chapter1 inIntroductionsectionwrittenbyKerrandteamreviewsvarious meansofmeasuringsoilmoisture,satellitemissions,retrievalsystem,andpossiblepitfalls. Chapter2 bySrivastavaetal.furnishesabriefdescriptionofavailabledatasetsforterrestrialsoilmoistureestimation.TheSectionIIofthebook containschaptersrelatedtooptical/IRmethods. Chapter3 ofthissectionby Rahimzadeh-BajgiranandBergprovidesabriefhistoryandconceptofoptical/ TIRmodelsforsoilmoistureestimationwithcasestudyofCanadianPrairies. Chapter4 byHolzmanandRivasdealswiththeestimationofsoilmoisture usingtemperaturevegetationdrynessindex.In Chapter5,Petropoulosetal. interestinglydescribedthesoilmoistureestimationusingthe“triangle” approachusingtemperatureandvegetationindexfeaturespace.Asfinerresolutiondatasetareimportantforhydrologicalcommunity, Chapter6 byPilesand Sanchezprovidedareviewofseveralapproachesforsoilmoisturedownscaling usingthesemiempiricalmodelanditsvalidationinDuerobasin. Chapter7 of thissectionwrittenbyMattaretal.providedanoverviewofthedifferentmicrowavesoilmoistureretrievalmodelwiththeirtheoriesandapplications.
SectionIIIofthebookmadeavailableanoverviewofmethodologiesfor microwavesoilmoistureretrieval. Chapter8 providedbyGuptaetal.briefly describeddiversenonparametricmodelsfortheretrievalofsoilmoistureby usingbistaticscatterometerdatasets.In Chapter9,MironovandSavinprovided theusefulnessofdielectricmodelformicrowavesoilmoistureretrievalwhile Akbaretal.in Chapter10 providedtheactiveandpassivesynergyforsoilmoistureretrievalanddiscussthemeritsofactiveandpassivesystemsinspatialresolutionenhancement. Chapter11 byBarrettetal.summarizedtheperformance ofdifferentsoilmoistureproductswithseasonalandtemporalanalysis.
SectionIVofthisbookdealswithchaptersrelatedwiththeadvancedapplicationsofsoilmoisture. Chapter12 ofthissectionbyBroccaetal.provided anoverviewofPRESSCAearlywarningsystemforlandslideriskprediction usingsatellitesoilmoistureinformation.In Chapter13,Chaparroetal.presentedtheroleofsoilmoistureinwildfirepreventionusingthesoilmoisture fromSMOSandSMAPsatellites.In Chapter14,Guptaetal.demonstrated theroleofsoilmoistureforestimationofsoilhydraulicparametersforan
improvedagriculturalwatermanagement.Zhuoetal.,in Chapter15,presented theimportanceofsatellitesoilmoistureinrainfallrunoffmodelingforaneffectivedischargeprediction. Chapter16 providedbyGhilainpresentedtheusefulnessofsatellitesoilmoistureassimilationforimprovingtheevapotranspiration onadailyandsub-dailyscale.Hefurtherexplainedthegainandlossofaccuracyinchoosinganewsourceforsoilmoistureinputandprovidedthevalidationoftheprototypebycomparisonwithinsituobservations. Chapter17 writtenbySrivastavaetal.furnishedtheuseofmicrowavesoilmoisturefrom SMOSforsoilmoisturedeficitestimationatacatchmentlevelanddepictedthe relationofsoilmoisturewiththehydrologicalmodelbasedproducts.
SectionVdealswiththechaptersrelatedwithfuturechallengesinsoil moistureretrievalandapplications. Chapter18 inthissectionbyMunozSabateretal.offeredadetailedoverviewofsoilmoisturefrommicrowave remotesensingandpointedoutvariousobstaclesintheproductionofsoilmoistureretrievalsanditsapplications.Atlast, Chapter19 writtenbyTebbsetal. suppliedadiscussionontheemergingandpotentialfutureapplicationsof satellite-basedsoilmoistureproductsandpointedoutthecurrentlimitations ofsoilmoistureapplicationsanddevelopmentsrequiredincomingdecades.
Webelievethatthebookwouldbereadbythepeoplewithacommoninterestin geo-spatialtechniques,remotesensing,sustainablewaterresourcedevelopment, applicationsandotherdiversebackgroundswithinearthandenvironmentaland hydrologicalsciencesfield.Wedohopethisbookwouldbebeneficialfortheacademician,scientists,environmentalists,meteorologists,environmentalconsultants,computingexpertsworkingintheareaofwaterresources.
ACKNOWLEDGMENTS
Editorswouldliketothankallthecontributingauthorsandanonymous reviewersfortheirtime,talents,andenergiesandforadherencetoastricttimelineandthestaffatAcademicPress,Elsevierfortheirpatienceandthroughout support.Editorsarealsogratefultothepublisherforthecollaborationinaccomplishingthepreparationofthisbook.
ABOUTTHECOVER
SophisticatedSoilMoistureandOceanSalinity(orSMOS)satelliteshownon thecoverisprovidedbyCESBIO/MIRA.
PrashantK.Srivastava Maryland,UnitedStates
GeorgeP.Petropoulos Wales,UnitedKingdom
SoilMoisturefromSpace: TechniquesandLimitations
Y.H.Kerr*,J.-P.Wigneron †,A.AlBitar*,A.Mialon* andP.K.Srivastava‡,§ *Centred’EtudesSpatialesdelaBiosphere,Toulouse,France, †INRAISPA,Bordeaux,France, ‡NASAGoddardSpaceFlightCenter,Greenbelt,MD,UnitedStates, §BanarasHinduUniversity, Banaras,India
1INTRODUCTION
Soilmoistureiscertainlyanimportantfactorforeverythinglinkedtolifeon Earth.Withoutwaterlifedisappears,andwithtoomuchwater(e.g.,floods) nonaquaticlifemaybeseverelyaffected.Sothefirstuseof“soilmoisture” istoenablevegetationgrowthandimpactweatherthroughtheheatandmass exchangesatthesurface/atmosphereinterface(Srivastavaetal.,2013c).This “soilmoisture”correspondstowaterinboththesurfaceandtherootzoneor vadosearea.Inamore“scientific”andhydrologicapproach,soilmoisture, inotherwords,waterstoredinthesoil,playsmanyroles.Surfacesoilmoisture controlsthepartitioningofrainfallintorunoffandinfiltrationandthusimpacts theamassingofwater.Goodinfiltrationusuallymeansreplenishingthewater table,whilerunoffmaymeanbothexportationofvaluablewatertootherareas oreventothesea,anddegradationoftopsoilthrougherosion.Also,whensaturated,soilmaytransformheavyrainfallsintofloods.Surfacesoilmoistureis thusofgreatinterestforimprovingtheforecastingskillsofrun-offmodels whichaimatfloodriskpredictionand/orwaterresourcesmanagement (Entekhabietal.,1999).Furtherconsistentestimatesofsoilmoisturefromagriculturalfieldsarerequiredforefficientirrigationmanagementandscheduling (Glennetal.,2011;Loriteetal.,2012;Srivastavaetal.,2013b).
Surfacesoilmoistureisalsoimportantasitcontrolssoilevaporationand vegetationtranspirationandthustheheatandmasstransfersbetweentheearth andtheatmosphere(vandenHurketal.,2002).Itisconsequentlyveryusefulin weatherforecastmodelsthroughglobalcirculationmodels(Entekhabietal., 1996).Ithasbeenshown,forinstance,thatincludingactualsoilmoisture insteadofsimplyusingseasurfacetemperaturemayimproverainforecastsvery significantly,especiallyincasesofextremeevents(Entekhabietal.,1996; SatelliteSoilMoistureRetrieval. http://dx.doi.org/10.1016/B978-0-12-803388-3.00001-2 Copyright © 2016ElsevierInc.Allrightsreserved. 3
vandenHurketal.,2012).Finally,continuousmonitoringofsoilmoistureona largescaleandoverlongperiodsoftimegivesasignificantinsightintoclimate changes(Srivastavaetal.,2015).
Butsoilmoistureisaveryvaguetermanditisimportanttodefineit.The mostcommonunderstandingofthetermis“thetotalamountofwaterinthe unsaturatedzone.”Forpracticalreasonsitisoftenseparatedintotwocomponents,surfacesoilmoisturecorrespondingtothefirstcentimeters(5cmingeneral),andtherootzonesoilmoisture,orsecondreservoir.Soilmoistureis usuallyexpressedingravimetricunits(g/cm3)whichisindependentofsoil characteristics(bulkdensity).Itis,however,alsocommonlyexpressedinvolumetricunits:m3/m3.Sometimesitisexpressedasafunctionofthewilting pointandthefieldcapacity.Thetwolatterunitsaresoiltypedependent.
2MEANSOFMEASURINGSOILMOISTURE
Toachievethegoalsmentionedpreviously,itisnecessarytohaveaccesstosoil moistureestimates.Ataspecificpointinspaceandtimethisisrelativelyeasy withgravimetricsampling.However,tohavemeasurementsrepresentativeofa largerarea(suchasafield),theprocedureisalreadysomewhatcomplexasit involvesadedicatedsamplingstrategy.Moreover,becausethesemeasurements aretimeconsuming,regionaland,evenmore,globalcoverageisoutofquestion.Providedoneusesautomaticprobes(resistive,capacitive,timedomain reflectometry,etc.)itispossibletoachievelargercoveragesbutthese approachescanonlybeconfinedtowell-equippedandmannedsites,asthey requirecareandmaintenance(Bircheretal.,2013).Finallythesesystemscarry theirownproblemsandinaccuracies(Chanzyetal.,1998;Escorihuelaetal., 2006;Vazetal.,2013).Alsotheinsituobservationsofsoilmoisture,such asthosefromprobeorgravimetricmeasurements,donotrepresentthespatial distributionaccuratelyassoilmoistureishighlyvariablebothspatiallyandtemporallyandthereforenotsuitableforregionalorglobalapplications.So,large scalemonitoringofsoilmoisturecanonlyrelyonremotesensingfromspace approaches(Srivastavaetal.,2013a,2014).
2.1RemotelySensedSoilMoisture,TheMainApproaches
Becauseofthehighneedforsoilmoisturemeasurements,alargenumberof approacheshavebeentested.Forsurfacesoilmoisture,thefirstoneswerebased onshortwavemeasurementsandonthefactthatsoilsgetdarkerwhenwet. Obviously,duetoatmosphericeffectsandpotentialcloudcover,aswellas vegetationcovermaskingeffects,thisapproachisboundtofailinmostcases (see Kerr,2007).Amorepromisingfeatureislinkedtolatentheateffects.Wet soilshaveahigherthermalinertiaandare“cooler”thandrysoils.Thesepropertiesledtovarioustrials(thermalinertiamonitoring,rateofheatinginthe morning,andsurfacetemperatureamplitude,etc.)(vandenHurketal., 1997)toassesssoilmoistureindirectly.Allthoseapproachesprovedtobe
somewhatdisappointingduetofactorsinherenttoopticalremotesensing (atmosphericeffects,cloudmaskingandforcing,andvegetationcoveropacity) aswellastothefactthatthermalinfrared:(1)probestheveryskinofsoilsand (2)thislayerisdominatedbytheexchangeswiththeatmosphere(Kerr,2007; Ochsneretal.,2013; Petropoulosetal.,2015).Consequently,toinfersoilmoisturefromsuchmeasurementsoneneedstoknowexactlytheforcings(wind,for instance,willchangedrasticallytheskintemperatureofawetsoil).Abrief reviewofsoilmoistureretrievalusingoptical/IRisprovidedby(Kerr,2007; Petropoulosetal.,2015)andsonotcoveredinthischapter.
Asmicrowavesystemsmeasurethedielectricconstantofsoilswhichis directlyrelatedtothewatercontent,researchhasquicklyfocuseditsefforts onassessingsoilmoisturewithradars,scatterometers,orradiometers (Pellarinetal.,2003).Thesesystemsoffer,whenoperatedatlowfrequency, theaddedadvantageofbeingallweather(measurementsarenotmuchaffected bytheatmosphereandclouds)andabletopenetratevegetation(Ulabyetal., 1986)andcanoperateduringthenight(Srivastavaetal.,2015).
Finally,inanattempttobeexhaustive,anewapproach,relyingonmeasurementsofthegravityfieldfromspace,isprovidinginformationonthechanges inthetotalcolumnofwaterwithaspatialresolutionof500kmormore.This columnincludestheatmosphere,vegetationandsurfacewater,possiblesnow orice,soilmoisture,andwaterstorage.Thefirstresultscertainlyshowasignal butitsrelationshipwithwaterstoragehasyettobevalidated.Actually,manycorrectionshavetobebroughttothesignaltoseparatewaterstorageintheground fromsurfacewater,atmosphericwater,vegetationwatercontent,orsnow(Han etal.,2005).
2.2MicrowaveasaToolforSoilMoisture
Monitoring:CurrentStatus
Onceitisestablishedthatthemostpromisingwaytoaccesssurfacesoilmoistureistheuseofmicrowavesystems,itisnecessarytoassesstheadvantagesand drawbacksofthedifferentpossibleapproaches.ThemostpopularapproachreliesontheuseofactivesystemssuchasSyntheticApertureRadars(SARs). Thesesystems,inusesince1977withSeaSatellite(SEASAT),offerallweather measurementswithafinespatialresolution(tensofmeters).Operationally, however,theysuffer—asmosthighresolutionsystems—fromaratherlowtemporalsampling(35daysfortheEuropeanRemoteSensingsatellite(ERS)for instance)whichisnotreallycompatiblewithhydrologicrequirementsorweather forecastmodels(Wagneretal.,2007).WiththeadventoftheCopernicusprogram andtheSentinel1satellites,thislimitationisboundtodecreaseaswith twoSentinel1satellitesandarevisitof12days,onemayexpecttoachieveanoverall6dayrevisitcapacity.ButthemostcomplicatedcharacteristicofSARsystems isthecoherentnatureofthesignalitselfandtheinteractionswiththediffusing medium.SARimagesareaffectedbyspeckleandbythescatteringatthesurface.
Thescatteringcanbeduetothevegetationcover(distributionofwaterinthecanopy) ortothesoil’ssurface(surfacescatteringwhenwet,andvolumescatteringwhen dry).Thedirectconsequenceoftheseperturbationsisasignalatleastasmuch sensitivetosurfaceroughnessastomoistureitself,notmentioningvegetation (seealso Wigneronetal.,1999).Obviouslytheseeffectsarefrequencydependent.
Alltheseinherentdifficultiesmightexplainthat,althoughseveralSARflew since1977,theywerenotusedinastandardandroutinefashion,norwasany realsoilabsolutemoisturemappingreallydone.Actually,toavoidtheroughnessandvegetationperturbations,anapproachrelyingonchangedetection, hencerelative,hasbeenusedwithrelativesuccess(Gorrabetal.,2015;Kim etal.,2012;Moranetal.,2002;Tomeretal.,2015).Thisworksaslongaseither vegetationorsoilroughnessdonotchange.Also,aslongasSentinel1and2are notoperational,again,temporalcoveragewilloftenbeanissue.
Theuseofscatterometersoffersaninterestingtradeoff.Thespatialresolutionismuchcoarser(tensofkilometers)butwithamuchwiderswathallowing reasonablyfrequentcoverage(every2–6daysonaveragedependingonthesystem).Italsoofferstheadvantageofbeinglesssubjecttospeckle(Magagiand Kerr,1997).Consequently,severalauthorsroutinelyproducesoilwetnessindex mapsofmanyareasoftheworldwithscatterometersusingchangedetection approaches.Theeffectofvegetationis,however,stillsignificantandactually correspondstomostofthesignalasthefrequenciescurrentlyavailableare C-bandon(MetOp)andhigher.Sothemostinterestingresultswereobtained overaridandsemiaridregionswherevegetationandsoilmoisturearevery highlycorrelatedanyway.Itshouldbealsonotedthatoverdryareas(arid andsemiarid)theretrievalsareoftenerroneous;areaswheresoilmoistureis pronetobeofimportancetousers(Wagneretal.,2013;Al-Yaarietal., 2014b).Theinfluenceofsurfaceroughnessisalsosignificant(Magagiand Kerr,2001)anditisbestdealtwithbyusing,hereagain,changedetection.
Theadvancedscatterometer(ASCAT)givesoneofthefreelyavailable globalsoilmoisturedatasetsderivedfromthebackscattermeasurement.The ASCATonboardMetOpisareal-apertureandanactivemicrowaveremote sensinginstrumentwithverygoodradiometricaccuracy(about0.3dB)andstability.ItisaC-bandscatterometeroperatedatafrequencyof5.255GHzusing sixsideways-looking,verticallypolarizedantennae.Themainobjectiveof installinganASCATistomonitorwindspeedanddirectionovertheoceans, thoughitisalsousedforstudyingsoilmoisture.Currently,withASCATon boardMetOp,thesignalisscaledbetweenminimumandmaximummeasurementsaslongasthewholesoilmoisturerangeisexplored.
Thelastpossibilityinthemicrowavedomainistouseradiometers (Schmugge,1998).Thetechniqueisold(Newtonetal.,1982)andwellmasteredasmanysensorsandnotablysoundersrelyonpassivemicrowaves.To infersoilmoisture,thesesystemsareboundtoofferthebestcompromiseifused atlowfrequency,asdemonstratedintheearly1970swiththeveryshortSKYLABmission(EaglemanandUlaby,1975;Jacksonetal.,2004).Tobeefficient,
oneneedstoworkinaprotectedfrequencybandtoavoidunwantedman-made emissionsandradiofrequencyinterferences(RFIs)andneedsaninstrument sensitivetosoilmoisturewhileatmosphereistransparentandvegetationplays alimitedrole.AtL-bandtheemissivitymayvaryfromalmost0.5foraverywet soiltoalmost1foraverydryonegivingarangeof80–100Kforaninstrument sensitivityusuallyoftheorderof1K.Asthesignalisnotcoherent,surfaceroughnessandvegetationstructureplayareducedrolewhencomparedtoanactive system(UlabyandLong,2014).So,onemaywonderwhyL-bandradiometry wasnotusedextensivelybeforewhenithadbeenprovedtobemostefficient duringgroundandairbornemeasurements(JacksonandSchmugge,1991; Schmuggeetal.,1988).Thisisduetoaninherentlimitation:thespatialresolution isproportionaltotheantennadiameterandinverselyproportionaltothewavelength.At21cm,toachievea40kmresolutionfromanaltitudeof750km requiresandantennaofabout8mindiameterwhichisaverysignificanttechnicalchallenge.Sotheresearchwasperformedwithhigherfrequencysystemsas availableonthescanningmultichannelmicrowaveradiometer(SMMR) (6.6GHz)(KerrandNjoku,1990),thespecialsensormicrowave/imager(SSM/I) (19GHz),theEarthObservingAdvancedMicrowaveScanningRadiometer (AMSR-E)(6.8GHz)(NjokuandLi,1999)andnowitsfollowon,theAdvanced MicrowaveScanningRadiometer2(AMSR-2)(Imaokaetal.,2010;Kimetal., 2015).Eventhoughthefrequencyisnotideal,goodresultswereobtainedwiththe SMMR(inspiteofaverypoorresolutionduetoimportantsidelobes)andnow AMSR-E/2(Al-Yaarietal.,2014b;Gruhieretal.,2008;Lerouxetal.,2014; NjokuandLi,1999).Thelimitationsaremainlylinkedtothefactthatthevegetationbecomesrapidlyopaque,thefrequencyisnotprotectedandthusboundto bepollutedbyRFIs,andthesingleangularmeasurementmakesitdifficult—in severalcases—toseparatevegetationandsoilcontributionstothesignal.
3SATELLITEMISSIONS
ConsideringthenecessityofmakingL-bandmeasurements,severalapproaches havebeentestedtoovercometheantennasizeissue.Thefirstwasinitiatedinthe early1990swiththeideatoapplyradioastronomytechniques(verylargearrays andverylargebaselineinterferometers)toEarthremotesensing(Martin-Neira etal.,2014).Theone-dimensionalconcept,electronicallyscannedthinnedarray radiometer(ESTAR)wasimplementedasanaircraftversionandprovedto fulfilltherequirements(LeVineetal.,1994).Itisasystem,deployableinspace asasortoflargerakeandoffering—atthecostofareducedsensitivity—an acceptablespatialresolution.Inparallel,anotherapproachusinginflatable(or umbrella-likedeployingtechnology)wasstudiedattheJetPropulsionLaboratory (JPL).Theconceptsappearedtobecomplextodeployandtorun,ortooffertoo limitedmeasurements(singleangleandfrequency).By1991,asmallgroup startedtoworkfortheEuropeanSpaceAgency(ESA)onthedevelopment ofasimilarinstrumentbutworkingintwodimensions(Goutoule,1995; SoilMoisturefromSpace:TechniquesandLimitations Chapter 1 7
Goutouleetal.,1996).TheconceptwasnamedMicrowaveImagingRadiometer withApertureSynthesis(MIRAS)andanairborneprototypewasmadeandoperated(Bayleetal.,2002).Fromthenontheconceptevolvedintoamoretailored instrumentwhichwasproposedtotheCentreNationald’EtudesSpatiales (CNES)in1997andthentotheESA(Kerr,1998)intheframeworkoftheEarth ExplorerOpportunitymissionunderthenameofSoilMoistureandOceanSalinity(SMOS)mission.SMOSwaslaunchedinNov.2009(Kerretal.,2001,2010). Similarly,amissionwasproposedandselectedbyNASAbasedonadeployable androtatingantennarelatedtobotharadiometerandaradarandcalledSoilMoistureActivePassive(SMAP)(Entekhabietal.,2010,2014).Thesatellitewas launchedinJan.2015.NotethattheSMAPradarbrokedownonJul.7,2015 becauseofpowersupplyfailureonitshigh-poweramplifier.BothSMOSand SMAPpassiveinstrumentshavesimilarcharacteristicsinspiteoftheverydifferentconcept(spatialresolutionofmorethan40km,3dayrevisitwithtimeof overpassat6:00am/6:00pmlocalsolartime)butwithnoticeabledifferences. SMOSmeasurestheangularsignaturesofthebrightnesstemperature,while SMAPmeasuresatonlyoneangle(40degree)butwithabettersensitivity(less than1Kvs.morethan3KforSMOSoverlandsurfaces).SMAPalso hasasophisticatedRFIdetectionsystem(Spenceretal.,2013)whosenecessity wasidentifiedduringthefirstmonthsoftheSMOSmission(Daganzo-Eusebio etal.,2013;Khazaaletal.2014;Olivaetal.,inpress;Soldoetal.,2014,2015).
TheSMOSmissionisthefirstpolarorbitingsatellitelaunchedthat,operatingatL-band,measuresbothseasurfacesalinityandsoilmoisture.ItisanESAledEarthExplorerMissionwithcontributionsfromtheCNES(France)andthe CentroparaelDesarrolloTeccnologicoIndustrial(CDTI)inSpain.Itwas launchedonNov.2,2009.Itaimsatcollectingcontinuousglobalobservation ofnear-surfacesoilmoistureandvegetationopacityoverland,seasurfacesalinityandextremewindspeedovertheoceans,andthinseaiceathighlatitudes. SMOSisona755kmpolarsun-synchronousorbitwithanequatorcrossingtime of6:00am(ascending)and6:00pm(descending).Theinstrumentonboard SMOSisa2DinterferometeroperatingatL-band(1404–1423MHz).Itmeasurestheemissionfromthesurfaceinafullypolarimetricmodeandwitha largenumberofviewangles(from0to55degree).TheSMOSlevel2soilmoistureproductsaredefinedontheISEA4H9grid(i.e.,IcosahedralSnyder EqualAreaprojectionwithaperture4,resolution9anditsshapeofcellsashexagon)(Kerretal.,2010).Eachpoint(ornode)ofthisgridisknownasaDiscrete GlobalGrid(DGG)thathasfixedcoordinatesandisassignedwithanidentifier the“DGGId.”Level3and4productsaredefinedontheEqual-AreaScalable Earth(EASE)-grid2projection.DataisavailablethroughtheESAportalfor level1and2dataandthroughtheCentreAvaldeTraitementdesDonnees SMOS(CATDS)forlevel3and4.
TheSMAPwasthefirstEarthobservationsatellitemissiondevelopedby NASAontherecommendationoftheNationalResearchCouncil’sEarthScienceDecadalSurvey,EarthScienceandApplicationsfromSpace:National
ImperativesfortheNextDecadeandBeyondin2007.ItwaslaunchedonJan. 31,2015.Likewise,SMOS,theSMAPmissiondesignedtocollectcontinuous globalobservationofnear-surfacesoilmoisture(0–5cmdepth)andfreeze/ thawstateevery2–3daysathydrometeorology(10km)andhydroclimatology (40km)scales.TheSMAPisafor-synchronoussatellitethatrunsfrompoleto poleandcrossesEarth’sterminatorattheequator.TheSMAP’sorbitis685km aboveEarth’ssurface.BecauseEarthspinswhileSMAPrevolves,swathsfrom eachorbitareoffsetfromeachotherand,after8days,thesameswathis repeated.Over2–3days(2daysatthepolesand3daysattheequator),thegaps betweenswathsarecompensatedforandthusaglobalmapofsoilmoistureis generated.TheinstrumentonboardSMAPconsistsofasimultaneousactive(in theformofradar)andpassive(intheformofradiometer)microwaveinstrumentsatL-bandfrequency(1.2–1.4GHzrange).Theradiometerinstrument oftheSMAPsatelliteisbasedonasinglefeedanddeployable6mreflector antennasystemthatrotatesaroundthenadiraxis.Thisrotationantennaenables conicalscanningataconstantincidenceangle(40degree).Theradiometer (1.41GHz)measurestheintensityofmicrowaveradiationemittedfromthe Earth’ssurface(i.e.,brightnesstemperature)ataspatialresolutionofapproximately40km.Theradiometeracquiresmeasurementsinfourchannels,vertical(V)polarization,horizontal(H)polarization,third,andfourthstokes.The radar(1.26GHz)transmitsmicrowaveradiationintwolinearpolarizations andmeasuresthescenebackscatterat1–3kmspatialresolutioninmultiple polarimetricchannels.Eachchannelreceivesandtransmitspolarizedradiation indifferentorientations:HH,VVandHV,orVH.Radiometric-basedmeasurementalgorithmsprovidebettersoilmoistureestimationundervegetatedconditions.TheSMAPbaselinedataproductsaremadeavailablepubliclythrough NASA’stwoDistributedActiveArchiveCenters(DAACs),theAlaskaSatellite Facility,andtheNationalSnowandIceDataCenterforallotherproducts.
OneshouldalsomentiontheAquariusinstrument(LeVineetal.,2014)which, eventhoughdesignedtomeasureoceansalinity,wasalsousedoverlandtoinfer soilmoistureatacoarsespatiotemporalresolution(Bindlishetal.,2015).Thethree L-bandmissioncharacteristicsaregivenin Table1.Notethat,onJun.7,2015,the satellitecarryingAquariussufferedapowersupplyfailure,endingthemission.
Itisworthmentioningatthislevelthatotherpassivemicrowaveinstruments,thoughnotspecificallydesignedforsoilmoistureretrievals(seeAMSR specificationsin Table2 forinstance)canshowgoodperformances(Al-Yaari etal.,2014b).
4SOILMOISTURERETRIEVALFROMSPACE USINGPASSIVEMICROWAVES
Eventhoughseveraltechniquesareavailable,wewillfocushereonthemost promising,theapproachusingpassivemicrowavesatlowfrequencyandinparticularatL-band.
Equatorcrossingsolar time(ascendingorbit)
Datesofoperation Nov.2,2009Jun.11,2011to Nov.7,2015 Jan.31, 2015
Radiometer InterferometerPushbroom Conical scan Spatialresolution(3dB)27
Polarization Full Threestokes Full Bandwidth(MHz) 1404–14231400–1427
Incidenceangle(degree)0–60 29.36,38.49,46.2940
4.1SurfaceSoilMoisture
SoilmoistureisaveryeasytargetatL-bandastheamplitudeofthesignalcan reach100Kforthewholesoilmoisturerange.Theproblemisnevertheless complicatedbythepresenceofvegetation,topography,freeze/defreezecycles, snowcover,orwaterbodies.Tocopewiththese,averyspecificretrievalalgorithmwasdeveloped(Kerretal.,2012)andimplementedfromlaunch.Itrelies onthemultiangularcapacityoftheSMOSinstrument(Kerretal.,2014).
ThesignalmeasuredbyapassivemicrowavesensoratL-band,overanonfrozenandsnowfreesurface,ismainlyafunctionofsoilmoisture,vegetation opacity,andeffectivesurfacetemperature.Othersurfacecharacteristicslike soiltextureandroughnessalsoplayanimportantrole.Atmosphericcontribution(includingcloudsandrain)andgalacticreflectioncanbeeasilyneglected overlandsurfacesatL-band.
Atatypicalspatialresolution(40kmonaverageforSMOSorSMAP),the surfacecontributiontotheL-bandsignalisrarelyuniform.Asurfaceareacorrespondingtoapixeloftenconsistsofsomewaterbodies,lowandpossiblyhigh vegetationfields,possiblyfrozenandsnowcoveredsurfaces,topography,and
TABLE2 AMSRSeries:Characteristics
Datesofoperation Dec.14,2002toOct.25,2003May4,2002toOct.4,2011 May18,2012
Frequenciesandresolutions
others.Consequently,anyphysicallybasedretrievalalgorithmhastobeableto accountforanumberoffeaturesintheobservedarea.Somesurfacecharacteristics,suchassoiltextureandlanduse,areobtainedfromstaticmapswhile others,suchastemperatureandsnow,areobtainedfromforecasts.Therefore, itisasignificantchallengetodeterminewithanadequateaccuracyandglobally thesurfacecharacteristics,andusethemintheretrievalprocesstoinferthe desiredcharacteristics.TheSMOSandSMAPmissionsdifferslightlyatthis level.Bothuseaphysicallybasedapproachusingstateoftheartmodelsbut SMOSusesthemultiangularinformationforassessingvegetationcontribution whileSMAPreliesontheuseofsatellitederivedvegetationindices.
TheSMOSalgorithmusesaniterativeapproachwhichaimsatminimizinga costfunctionwhosemaincomponentisthesumofthesquaredweighteddifferencesbetweenmeasuredandmodeledbrightnesstemperaturedata,foracollectionofincidenceangles.Thisisachievedbyfindingthebest-suitedsetof parameterswhichdrivethedirectTBmodel(e.g.,soilmoistureandvegetation characteristicsusingtheL-MEBmodel)(Wigneronetal.,2007).
Despitetheapparentsimplicityofthesoilmoistureretrievalprinciple,the modelingoftheradiometricsignaliscomplexandrequirescloseattentionto manydetails.TheSMOS“pixels”cancorrespondtoratherlarge,inhomogeneoussurfaceareasinvolvingmanylandusetypes(cropfields,forests,water bodies,urbanareas,etc.),eachwiththeirowncharacteristics.Moreover,the radiometricsignalisimpactedbythedirectionalpatternoftheSMOSinterferometricradiometer.Therefore,modelingoftheSMOSradiometricsignal involvesboththemodelingofthegroundtargetandtheantennaforavariety ofincidenceangles.Themodelingofthegroundtargetinvolvesestimation ofvariousparameters(suchassurfacetemperatureandsoilmoisture)atvarious positionswithinthetarget.Theantennapatternisrepresentedthroughaweightingfunctionwhichdependsontheincidenceangle.Itisimportanttonotethat, thankstothe“reconstruction”principle,theobservationsarecomputedforany givenpointofthesurface(withanaccuracyof400m)anditisalwaysthesame center.So,fromoneacquisitiontothenext,theinstrumentfootprintisexactly thesame.
Asforanypixel,theremightbealargevarietyofsurfacetypes,notallof whicharecharacterizedbythesamesetofparameters.Itis,therefore,notrealistictocarryoutthesameretrievaleverywhere.Itisunderstoodthatallsurface types,regardlessofwhethertheysupporttheretrievalofagivensetofparameters,docontributetotheSMOSsignalaccordingtoagivenmodel.However, estimationofsoilmoistureisonlymeaningfulovercertainsurfacetypes.For instance,whilealakecontributestotheradiometricsignal,itisnotparameterizedbysoilmoisture.Inordertofacilitatetheretrievalprocess,anodeis dividedgenerallyintotwoareas,onewheretheretrievalwilltakeplaceand onewherethecontributionstotheoverallnodesignalneedtobeestimated butnoretrievalswillbeperformed.Thislatterpartisthenconsideredtohave fixedcontribution(defaultcontributions)andtheretrievalismadeonthe
remaining—dominant—area.Forinstance,ifthereisanareaoflowvegetation withadenseforestandalake,wewillestimatethecontributionofthelakeand thatoftheforestusingeitherexternaldataorpredeterminedvaluesofthesurfacecharacteristics:the referencevalues.Thisdefaultcontributionwillbe assumedconstantinthemodeledsignal,andtheretrievalisperformedonly ontheremaining,dominantpart.
Oncethedominantareaisascertained,itscontentmustbetakeninto account.Actually,asurfaceareacontributingtotheSMOSsignalmayinclude alargevarietyofsurfacetypes,suchascultivatedagriculture,grasslands,and forests.Theseland-useclassesaregroupedtogetherbasedontheirL-band microwaveemissionproperties.Allsurfacetypesareaggregatedintoasmall number(about10)ofgenericclasseshavingthesamemodelingcharacteristics andusingsimilarparameters.Atargetareaissubdividedintoanumberofunits (4 4km2 bydefault)andeachunitisdefinedbyacollectionofsuchaggregatedfractions.TheSMOSpixelscorrespondtovariousviewsofanodeasseen fromdifferentangles.Thespatialextentsoftwodifferentviewsofthesame targetaregenerallydifferent.Thedifferenceincreasesastheviewingangles arefurtherapart.
Thedominantpartdoesnotalwayscovernicerollinghillsofgreenpastures (alsoknownas“nominal”).Thesoilcanbefrozenorcoveredwithsnowor rocks.Thetargetcouldbeanislandwithinaseaorhavealargeurbanormountainouscomponent,nottomentionmarshesorricefields.Thesenonnominal,or exotic,casesneedtobemodeleddifferently.Theexoticsurfacescouldbeeither complementary(i.e.,thereisnooverlapbetweentwoclassesofthistype)or supplementary(theynecessarilyoverlapwithcomplementaryclasses).For instance,surfacecharacteristicscanbesupplementarywhentwo“special”cases arepresentatthesameplaceandsamemoment(i.e.,topographyandwaterbody orforest).Theycanbesupplementarywhentheyexcludeoneanothersuchas waterbodyandforest.
Whenitisnotpossibleorrelevanttoretrievesoilmoisture,itmaybepossibletoretrieveotherparametersofinterest.Forinstance,onecanretrieve dielectricconstantparameters(usingtheso-calledCardioidapproach)(Kerr etal.,2014).
Thealgorithmhasbeenundergoingcontinuousvalidationusinggroundsites andsubsequentimprovements.Asalreadystated,RFIconstitutesanissue,so resultsobtainedinEuropeandAsiaarealwaysdifficulttointerpret.Sitesin theUnitedStateshaveprovedtobemuchmoreuseful(Albitaretal.,2012; Jacksonetal.,2012).Theresultsareavailable(SMOSspecialissueMay 2012andRSEspecialissue2016).Currentlyversion620isbeingrunand resultsareverysatisfyingovernormallandsurfaces(flattishareawithlowvegetationandnoRFI).
TheSMAPmissioniscurrentlyinitsfirstyearandfourretrievalalgorithms arebeingtestedandevaluated.Themostusedareone(singlechannelalgorithm)basedononlyonechannel(theVpolarization)asselectedattheend
ofthecommissioningphaseandoneusingthetwopolarizations(dualchannel algorithm).FirstintercomparisonexercisesshowthatbothSMOSandSMAP areverycoherentintheirresultsandshowsimilarquality.SMAPhastheadded advantageofanefficientRFIfiltering,enablingamoreexhaustivespatialcoveragewhileSMOSseemstobemoreabletocopewithverydensevegetation,at leastforthetimebeing(SMAPhandbook).1
Globally,theSMOSretrievalalgorithmperformswellintermsofcoverage withthebigcaveatoftheRFIwhichaffectsmainlyobservationsinEuropeand Asia.Thequalityoftheresultsisalmostwithinexpectations(0.04m3/m3), whichisencouragingwhenoneconsidersthatthesatellitewasthefirstspaceborneinterferometricsystemandhasbeenoperatingfor6years.Goodresults areobtainedoverRFI-freeareasandveryencouragingresultsareobtainedover moderatelydenseforests(Rahmouneetal.,2014;Vittuccietal.,inthisissue).
SoilmoistureretrievalsareinthecorrectrangewithpossibleunderestimationlinkedtoRFIascouldbeexpected.However,insomecasesandaftera heavyrainfallevent,thesoilmoisturevaluesobtainedseemtoohigh(sometimesexceeding0.65m3/m3).Thismaybeduetopondingeffects,saturation oftheuppersoillayerandcanindicateflooding.Insomecases,itcanbelinked toretrievalerrorslinkedtoerroneousauxiliarydata.
Anotherpointofconcernisthewaycoldareasareprocessed.Iffreeze/thaw iseasilydetected(soilappearssuddenlydrywhenitfreezesandvegetation becomestransparentwhenfrozen)(Matzler,1994;Schwanketal.,2004),the mainissueatthislevelisthefactthatahighspatialresolutionisrequired tomonitorfreeze/thaw,especiallyinthetransitionareas.Snowcoverismore complex.Whendry,snowisalmosttransparent,andL-bandissensitivetothe relativelywarmsoilunderneath.However,whenthesnowiswetitisratheropaque.Alltheintermediarycases(bothintermsofsnowstateandspatialdistribution)makeretrievalintransitionareasverydifficultandtheproductisprone tobeingerroneous.Anothersourceofconcernislinkedtowaterbodies.There arenoavailabledynamicmapsofwaterbodiesatafineenoughresolutionand waterbodiesdochangewithtime,beitthroughseasonalvariations,floods,or eventides.Anerrorof2%onthewaterbodysurfacecanleadtoanerrorinsoil moisturecorrespondingto0.01m3/m3 (Kerretal.,2012).
QuantitativeevaluationoftheL2algorithmhasbeendescribedinseveral papersforbothSMOSandSMAP.Anexampleisgivenin Fig.1 anddescribed furtherin(Kerretal.,submittedforpublication)andfortwodifferentcases;a semiaridenvironment(WalnutGulch)andatemperateone(LittleWashita).The chartsshowthetemporalevolutionofthesoilmoistureforSMOS,ascatterometer(ASCAT),modeloutputs(EuropeanCenterforMedium-RangeWeather Forecasts,ECMWFandModernEra-RetrospectiveanalysisforResearchand Applications(MERRA))andinsitudata.BelowistheCumulativeDistribution
1. http://smap.jpl.nasa.gov/system/internal_resources/details/original/178_SMAP_Handbook_ FINAL_1_JULY_2014_Web.pdf
FIG.1 TypicalresultsofretrievalsoveraUSWatershed(see Jacksonetal.,2012):(A)forWalnut Gulchand(B)forLittleWashita.
Function(CDF)plotandaTaylor’sdiagramforthesamemeasurements. Thesetypesofplotsallowforagoodestimationoftheretrievalsqualityeven thoughnotallaspectscanbecovered(inparticularthespatialrepresentation). Thetemporalbehaviorsoverthisexampleofaridenvironmentshowsthat theASCATtendstohaveastrangebehaviorwithlargeerrorsassociated (Wagneretal.,2013),whilemodelstendtolargelyoverestimatesoilmoisture
