Secondary Fault Activity of the North Anatolian Fault near Avcilar, Southwest of Istanbul

17 Pages·2016·7.7 MB·English

remote sensing
Article
Secondary Fault Activity of the North Anatolian Fault
near Avcilar, Southwest of Istanbul: Evidence
from SAR Interferometry Observations
FaqiDiao1,*,ThomasR.Walter2,FedericoMinati3,RongjiangWang2,MarioCostantini3,
SemihErgintav4,XiongXiong1andPauPrats-Iraola5
1 StateKeyLaboratoryofGeodesyandEarth’sDynamics,InstituteofGeodesyandGeophysics,
ChineseAcademyofSciences,Wuhan430077,China;[email protected]
2 GFZ-GermanResearchCentreforGeosciences,Telegrafenberg,Potsdam14473,Germany;
[email protected](T.R.W.);[email protected](R.W.)
3 e-GEOS—AnASI/TelespazioCompany,ViaTiburtina965,Rome00156,Italy;
[email protected](F.M.);[email protected]@gmail.com(M.C.)
4 DepartmentofGeodesy,KandilliObservatoryandEarthquakeResearchInstitute,Bog˘aziciUniversity,
Istanbul34680,Turkey;[email protected]
5 DLRGermanAerospaceCenter,MicrowavesandRadarInstitute,Weßling82234,Germany;
[email protected]
* Correspondence:[email protected];Tel.:[phone]
AcademicEditors:MagalyKochandPrasadS.Thenkabail
Received:12July2016;Accepted:11October2016;Published:18October2016
Abstract: Strike-slipfaultsmaybetracedalongthousandsofkilometers,e.g.,theSanAndreasFault
(USA)ortheNorthAnatolianFault(Turkey). Acloserlookatsuchcontinental-scalestrikefaults
revealslocalizedcomplexitiesinfaultgeometry,associatedwithfaultsegmentation,secondaryfaults
andachangeofrelatedhazards. TheNorthAnatolianFaultdisplayssuchcomplexitiesnearbythe
megacityIstanbul,whichisaplacewhereearthquakerisksarehigh,butsecondaryprocessesare
notwellunderstood. Inthispaper,long-termpersistentscattererinterferometry(PSI)analysisof
syntheticapertureradar(SAR)datatimeserieswasusedtopreciselyidentifythesurfacedeformation
patternassociatedwiththefaultingcomplexityattheprominentbendoftheNorthAnatolianFault
nearIstanbulcity. Weelaboratetherelevanceoflocalfaultingactivityandestimatethefaultstatus
(sliprateandlockingdepth)forthefirsttimeusingsatelliteSARinterferometry(InSAR)technology.
ThestudiedNW-SE-orientedfaultonlandissubjecttostrike-slipmovementatameansliprateof
~5.0mm/yearandashallowlockingdepthof<1.0kmandthoughttobedirectlyinteractingwith
themainfaultbranch,withimportantimplicationsfortectoniccoupling. Ourresultsprovidethe
firstgeodeticevidenceonthesegmentationofamajorcrustalfaultwithastructuralcomplexityand
associatedmulti-hazardsneartheinhabitedregionsofIstanbul,withsimilaritiesalsotoothermajor
strike-slipfaultsthatdisplaychangesinfaulttracesandmechanisms.
Keywords: fault activity; interferometric synthetic aperture radar (InSAR); persistent scatterer
interferometry(PSI);Istanbul;seismichazardassessment;NorthAnatolianfault
1. Introduction
Crustalstrike-slipfaultsarefoundtobehighlysegmented,withpatchesofhighorlowslip,and
parasiticorassociatedfaultsthatmaysporadicallybecomeseismicallyactive[1–3]andoftenlocalizeat
geometricbendsofthemainfaulttrace[4]. TheNorthAnatolianFault(NAF)isoneofthemostactive
strike-slipfaultsintheworldandcanbetracedfromeasternTurkeytothenorthernAegeanSeawitha
scaleof~1200km[5]. NeartheAlmacıkblock,theNAFseparatesintotwobranches,andthenorthern
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thbrea nnocrhthoefrtnh ebrNaAncFh( NofN thAeF N)cAoFn t(iNnuNeAsFsu) bcmonatrininueeisn stuobthmeaMrinaer minatroa tSheea M,aalirgmnainrag Sweiath, atlhigenninorgt hwaitnhd
thsoeu ntohrsthlo apneds osofuththe sÇloınpaersc oıkf tBhaes iÇnın[6a]rc(Fıkig Buarsein1 )[.6T] (hFeigsutrriek e1)o. fTthhee sntroirkteh eorf nthber annocrhthtehrenn bbraenncdhs tfhroenm
btehnednso frrtohmw etshtet onothrethwweesstt [t6o]. tAhes wweessth [a6l]l.d Aissc uwses isnhathlli sdwisocurks,s tihne tlhoicsa lwizoartkio, nthoef tlhocisalgizeoatmioentr oicf btehnisd
giesoamlseotrtihce breengdio nis oaflfsaou tltheco rmegpiloenx itoyf nfaeuarlt Kcüoçmüpklçeexkitmy enceeaLra Kkeü,çaüsksçoeckiamteedcew Litahkes,e caosnsodcairaytefda uwltiitnhg
spercoocnedsaserys tfhaautlctianngb peroobcseesrsvees dthuasti ncgans ybnet hoebtisceravpeedrt uurseinrga dsayrn(tShAetRic) paepresritsuternet rsacdaattre r(eSrAiRnt)e prfeerrsoimsteentrty
s(cPaSttIe),rearm inotderefrenrospmaecteryg e(PoSdIe)t,i ac tmecohdneirqnu sep.ace geodetic technique.

FFigiguurree 11. .GGeoeolologgiciacla mlmapa pofo tfhteh estsutduyd yaraerae. aT.hTeh belabclka clkinleins einsdinicdaitcea ttheet hdeisdtriisbturitbiounti oonf aocftiavcet ifvaeulftasu ilnts
thinist hairseaa r[e7a],[ 7w],hwerheearse athset hdeasdhaesdh egdragyr alyinleins esshsohwo wthteh etratrcaec eofo fthteh esesceoconnddarayr yfafauultlst sssoouuththwweests toof f
IsIstatannbbuul l[8[8].] .TThhee rreedd lilninee aanndd rreedd ssttaarr sshhooww tthhee ccoosseeiissmmiicc rruuppttuurree aanndd eeppiicceenntteerr ooff tthhee İI˙zzmmiitt//DDüüzzccee
eeaarrththqquuaakkeess, ,rreessppeeccttiviveellyy.. TThhee bbllaacckk bbooxx ddrraawwss tthhee sstutuddyy aarreeaa oof fththisis ppaappeerr. .TThhee ddaasshheedd oorarannggee bbooxxeess
sshhooww ththee ssppaatitaial lccoovveerraaggee oof fththee aasscceennddiningg aanndd ddeesscceennddiningg trtraacckk inin ththisis aarereaa. .NNNNAAFF: :NNoortrhtheernrn bbraranncchh
oof fththee NNoortrhth AAnnaatotolilaiann FFaauultl;t ;KKLL: :KKüüççüükkççeekkmmeeccee LLaakkee; ;BBLL: :BBüüyyüükkççeekkmmeeccee LLaakkee. .TThhee uuppppeerr leleftf tppaanneel l
sshhoowwss tthhees hsahdaedderde liereflmieaf pmofatph eostfu dtyhea resat,uidnyw hairceha,t heinis owlahteicrhe dtahree asissohloawte acrteivde laarnedassl idsehso[w9] .
active landslides [9].
The1999I˙zmit/Düzceearthquakedisasterhighlightedthehighseismichazardandrevealeda
The 1999 İzmit/Düzce earthquake disaster highlighted the high seismic hazard and revealed a
westwardpropagationofearthquakestowardstheMarmaraSea[10]. Thetectonicevolutionofthe
westward propagation of earthquakes towards the Marmara Sea [10]. The tectonic evolution of the
NNAFbeneaththeMarmaraSeahasbeenwidelydiscussedinpastdecades;someauthorssuggest
NNAF beneath the Marmara Sea has been widely discussed in past decades; some authors suggest
thattheNNAFdeformsasasingleshearzone[11],whereasotherssuggestthatthecrustbeneaththe
that the NNAF deforms as a single shear zone [11], whereas others suggest that the crust beneath the
MarmaraSeaisseparatedbyanE-Wtrendinggraben[12].Besides,theevolutionoftheNNAFzonehas
Marmara Sea is separated by an E-W trending graben [12]. Besides, the evolution of the NNAF zone
alsobeeninterpretedasacombinationofen-echelonstrike-slipfaultsandpull-apartbasins[6,13,14]
has also been interpreted as a combination of en-echelon strike-slip faults and pull-apart
associatedwithnumeroussubparallelfaultscarpsofunknownactivity[7,15]. Theseinvestigations
basins [6,13,14] associated with numerous subparallel fault scarps of unknown activity [7,15]. These
mostlyfocusedonthefaultactivitybeneaththeMarmaraSea,butthepossibleactivityofsecondary
investigations mostly focused on the fault activity beneath the Marmara Sea, but the possible activity
faultsnorthoftheMarmaraSearemainedtobestudied. Asthefaultsareshapingthelandanddirectly
of secondary faults north of the Marmara Sea remained to be studied. As the faults are shaping the
affect the populated regions of western Istanbul, monitoring the fault activity in this region is of
land and directly affect the populated regions of western Istanbul, monitoring the fault activity in
greatimportance.
this region is of great importance.
Previous studies on seismic and bathymetric observations show evidence of the existence of
Previous studies on seismic and bathymetric observations show evidence of the existence of
secondaryfaultsnearthetwolakes(BüyükçekmeceLake(BL)andKüçükçekmeceLake(KL);Figure1),
secondary faults near the two lakes (Büyükçekmece Lake (BL) and Küçükçekmece Lake (KL);
northoftheMarmaraSea[8,16–19].ThesesecondaryfaultswerefoundtobeNW-SEorientedfollowing
Figure 1), north of the Marmara Sea [8,16–19]. These secondary faults were found to be NW-SE
thegeographicalignmentofthelake,whichalsoshowgeneralconsistencywiththeinlanddrainage
oriented following the geographic alignment of the lake, which also show general consistency with
patternandthescarpsofthesurroundingterrain[19]. Furthermore,theagreementbetweenthestrike
the inland drainage pattern and the scarps of the surrounding terrain [19]. Furthermore, the
andlocationofthesecondaryfaultsandoff-shoreactivefaultsindicatesthatthesecondaryfaultsnear
agreement between the strike and location of the secondary faults and off-shore active faults indicates
thelakesarenotlocalfaultsystems,butrelatedtotheNWextensionoftheNNAF[16].
that the secondary faults near the lakes are not local fault systems, but related to the NW extension
Near-fieldgeodeticobservationscanprovideanindependentconstraintonthepresentactivityof
of the NNAF [16].
thesesecondaryfaults. RecentGPSobservationsshowlocalcrustdeformation(~5mm/year)near
Near-field geodetic observations can provide an independent constraint on the present activity
KL[17,20],however,theinferredresultsmaysufferfromthespatiallimitationofthesurvey-modeGPS
of these secondary faults. Recent GPS observations show local crust deformation (~5 mm/year) near
KL [17,20], however, the inferred results may suffer from the spatial limitation of the survey-mode
GPS observation. Previous studies [21,22] already described the pronounced subsidence of the
RemoteSens.2016,8,846 3of17
observation. Previousstudies[21,22]alreadydescribedthepronouncedsubsidenceoftheAvcilararea
(Figure1),butthehorizontalmovementrelatedtothesecondaryfaultactivityremainedtobestudied.
Inthispaper,well-coveredlong-termPSImeasurementswerecarriedoutbyexploitingtheESA
ENVISATascending(Track429)anddescending(Track336)dataarchive,inordertostudythestable
near-fieldcrustaldeformation(Figure1). Aftergeometricdecompositionandmodel-basedcorrection
ofthepost-seismicviscoelasticrelaxationassociatedwiththe1999I˙zmit/Düzceearthquakes,theslip
rateandlockingdepthofthesecondaryfaultbeneathKLweredeterminedforthefirsttimebasedon
theassumptionofasingledextralfaultthatwasinferredfromgeologicalstudies[16,17]. Wecompare
our findings to independent information and discuss the implications of these secondary faults,
aswellastherelationshipofthefaultslipandfaulttrendtothegeomorphologyandlandslideactivity.
2. DataHandlingandMethod
SpaceborneSARinterferometry(InSAR)allowsinvestigatingthestudyareaathighresolution
andidentifyingsubtledeformationoccurrences. ThebasicprinciplesofSARinterferometryhavebeen
extensivelydescribedintheliterature[23,24],andthetechniqueswerethensignificantlyimprovedby
theapplicationoftimeseriesprocedures. Thesmallbaselinesubsettechnique[25]allowssuchtime
seriesanalysisandisbasedoninterferogramswithsmallbaselinestolimitgeometricdecorrelationand
wasusedtomapsubsidencezonesintheAvcilarareanearbyIstanbul[22]. ThePSItechnique,with
theideaofselectingdistinctpixels,namedpersistentscatterers(PS),characterizedbyacoherentsignal
overalongseriesofacquisitions,irrespectiveofthebaseline,broughtimportantadvancesinthefield,
allowingmillimetricprecisionofdisplacementdetection[26]. Sincethen,differentPSIand,ingeneral,
multi-interferogramInSARtechniqueshavebeendeveloped[25,27–31]. BymeansofPSItechniques,
verylongtimeseries,suchasavailableoverthestudyareawestofIstanbul,canbeprocessed,andvery
densePSmeasurementscanbeobtainedinspiteoftemporalandgeometricaldecorrelationeffects.
Inthiswork,anadvancedPSItechniquenamedpersistentscattererpair(PSP)[30]wasusedto
processthefullENVISATarchiveofSARdata,inordertostudyaseismicdeformationstothewestof
Istanbul,aregionthatislocatedinthevicinityofanimportantbendoftheNNAF.
2.1. SARInterferometryProcessing
The PSP approach was recently proposed [29,30,32] for the identification of PSs in series of
fullresolutionSARimagesandtheretrievalofthecorresponding3Dpositionsanddisplacements.
DifferentlyfromstandardPSItechniques,thePSPmethodreliesonlyontherelativesignalinpairs
of nearby points, both for identification and analysis of PSs. For this reason, the PSP technique is
intrinsically robust to spatially-correlated disturbances (such as atmospheric and orbital artifacts)
anddoesnotneedapreliminaryprocessingaimedatcompensatingthesecontributionstothesignal.
Inaddition,deviationsfromthemodelsofdisplacementevolutiontypicallyusedinPSItechniques
(forexample,duetostrongnonlinearevolutions)aremitigatedbythePSPapproachbecauseclose
pointslikelyhavesimilardeviations. Againstthementionedadvantages,workingwitharcsrequires
manymorecomputationsthananalyzingsinglepoints: infact, Npointscanform(N − 1) × N/2
differentarcs. ThePSPapproachisbasedonacomplexalgorithmdesignedtofindasetofvalid(inthe
senseofthemulti-acquisitioncoherenceoranalogousparameters)arcstoformagraphwithgiven
connectivityandcardinality. ThePSpointsareidentifiedasthenodesofthisgraph.
ThehighnumberofarcsandthehighconnectivityofthegraphguaranteereliablePSidentification
andaccuratePSmeasurements. Moreover,itmakesitpossibletofullyextractcoherentinformation
even from low-intensity SAR signals, even when strongly scattering structures are not present,
thesensedsignalisweakandthescatteringdistributed,asinthecaseofrathersmoothsurfacesor
naturalterrains. Inthissense,PSareintendedinthegeneralsenseofscattererswhosebackscattering
propertiespersistunalteredovertime(atleastfortheperiodofinterest),asthenamesuggests,but
thatcanbealsofullydistributed. Infact,thankstothehigherrangeresolutionandthestricterorbital
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control,intherecentsatelliteSARsystems,theinterferometricbaselineisbelowthecriticallimit,and
theTrehaer erendousntrdoanngt sipnafotiramldateicoonr replraotvioidnepdh ebnyo mtheen ah.ighly connected PSP graph is conveniently
exploitTehde rteod ugnudaarannttienefo rmmoarteio nacpcruorvaidtee dmbeyatshuerhemighenlytsc obnyn ecat edrePceSnPt grmapehthiosdc onfovre nrioenbtulyste xpphloasitee d
untowgrauparpainntge eamnodr efaincictuer adteifmfeereansucere minetnetgsrbaytioanr ec[e3n3]t, mwethhiocdh foarrero bkuesyt pphraosceeussniwngra pspteinpgs ainnd fithnei te
redcoifnfesrtreunccteioinnt eogfr aPtSio nel[e3v3a],tiwonhsi chanadre dkiesyplparcoecmesesnitnsg fsrtoemps IinnStAheRr edcaotnas. trTuhceti ounseo foPfS ae lemvualttiio-nscsaalen d
dedciosmplpacoesmitieonnt smfertohmodI n[3S4A] Raldloawtas. oTnhee tou speeroffoarmm au lgtlio-sbcaall eprdoecceosmsinpgo saiptipornomaceht haolsdo [i3n4 l]aarglleo warseaosn e
wtiothp heirgfho rPmS adegnlosbitayl, pdreoscpeistes itnhge ahpigphro caocmhpalustoatiinonlaarlg deeamreaansdw reitqhuhiriegdh bPyS tdheen esxitpyl,oditeastpiointe otfh evehriyg h
recdoumnpduantatt iinofnoarlmdaetmioann. drequiredbytheexploitationofveryredundantinformation.
ThTeh eadavdavnatnatgaegse osfo gflgolboabllayll yexepxlpoliotiintign grerdeudnudnadnatn atracsrc csocnonnenceticntgin gdidffiefrfeernetn ptapirasi rosfo PfSP Scacna nbeb e
papratirctuicluarlalyrl yrerleevleavnatn itni norodredre trot oobotbatiani nrerleialibalbe leanadn dacaccucruartae temmeaesausruermemenetns tws hwehne nthteh PeSP Saraer evevreyr y
spsaprasres, ea,sa isni tnhteh ceocnosnidsiedreerde rdergeigoino onfo IfstIasntabnublu, wl,hwihchic ihs icshcahraacratecrteizreizde bdyb tyheth perpesreensecnec oef owfawteart ebrobdoiedsi,e s,
mmouonutnatianisn asnadn dlalragreg veevgeegteattaetde daraeraesa. s.
FoFro rthtihs isstustduyd,y a,na naraerae aofo fabaobuotu t60600 0kmkm2 2susrurroruonudnidnign gKLK Lwwasa sanaanlaylzyezde dexepxlpoliotiintign gthteh eESEAS A
ENENVIVSIASTA Tasacsecnednidnign g(T(rTarcakc k42492)9 )anadn ddedsecsecnednidnign g(T(rTarcakc k33363)6 )ddataat aaracrhchivive.e .ThTeh easacsecnednidnign gdadtaatsaeste t
cocnosnisstiesdte dofo 3f33 3imimagaegse csocvoevreinrign gthteh epepreiorido dDDeceecmembebre 2r020020–2A–Aprpilr i2l021001 0anadn dthteh ededsecsecnednidnign gdadtaatsaeste t
cocnosnisstisetde dofo f323 2imimaaggeess ccoovveerriningg tthhee ppeerriioodd AApprriill 22000033––SSeepptteemmbbeerr 22001100..T Thheei mimagagesesa caqcuqiurierdedfr ofrmomth e
thEe NEVNIVSAISTAAT SAASRAsRe nsesnorsohra hvaevteh ethfeo lfloolwloiwngincgh cahraacrtaecrtiesrtiicssti:csst:r siptrimp ampaipm iamgaegme omdoed,ae,r ae sroelsuotliuotnioonf o5fm
5 ×m 2×5 2m5 pme rppeirx epli,xVelV, VpoVl apriozlaatriiozna,tiaonn,o ma ninoamliinncaild ienncciedeanncgel eaonfg2le3 dofe g2r3e edseagnredeas manadx iam mumaxbimasuemlin e
baosfe1li8n0e0 omf .1T80h0e 3m-a. rTchseec 3S-RarTcMsecD SERMTMw aDsEuMse dwaassa unsiendit iaasl ganu eisnsitfioarl tghueersesm foorv athleo frtehmeotvoaplo ogfr atphhe ic
tocpoongtrraibpuhtiico nco.nDturirbiuntgiothne. DPSuPrinpgro tchees sPinSgP, pthroeceelsesviantgio, nthien efolervmaattioionn iwnfaosrmfuarttihoenr wreafisn feudrtfhroemr rtehfienSeAd R
frodmat athseta ScAk,Rb ydaetsati smtaactkin, gbyin ecsotirmreastpinogn dinen ccoerroefsepaocnhdPeSncthe eofc oerarcehc tPioSn thtoe bceorarpepctliioedn ttoo tbhee aipnppluietdD tEoM .
thTeh inepPuStP D(EanMd., Tinheg PenSPer (aaln,dP,S iIn) pgeronceersasl,i nPgSIm) parkoecseistspinogs smibalkeetso itr epaocshsiablme teotr riecaeclhe vaa mtioetnripc reelceivsaiotinonfo r
preeaccishioPnS fwori tehacEhN PVSI SwAitTh dEaNtaV.IIStAisTt doabtae. nIto itse dtot bhea tntohteedu tsheaot fthaeh uigshe eorf rae hsoigluhteiro nreDsoEluMtioans tDhEeMin iatsia l
thgeu iensisticaol ugludersesd cuocueldth erecdoumcep uthtaet icoonmalpcuotsattoiofnthael caolgsto roifth tmhe, baulgtowriothumld, nboutti mwporuolvde ntohte ifimnpalroevleev athtieo n
finaaclc uelreavcaytioofne aacchcuPrSa.cy of each PS.
FoFro eraecahc hdadtaatsaest,e tt,hteh ienitnetreferrfeorgorgarmams wswithit hrersepsepcet cttot othteh feirfisrt sitmimagaeg oefo tfhteh seesreiersie wswereer geegneenreartaetde d
(s(insignlge lemmasatsetre rinitnetrefrefreorgorgarmam cocnofnigfiugruartaiotino)n. )I.n Ifnacfta, ctw,hwehne nwowrkoirnkgin gat aftufllu lrlerseosluoltuiotnio nwwithit hPSPIS I
tetcehcnhinqiuqeuse, st,hethree ries inson aoddadedd eidnfoinrfmoramtioanti oinn tihne tohteheort hinerteirnfeterorfgerraomgrsa (malsl t(halel pthoesspibolses pibaliersp caairns bcea n
exbaectelxya ocbtltyaionbetda ianse ad lainseaarli cnoemarbcionmatbioinna otfio tnheo sfitnhgeles imngalsetemr ainstteerrfienrtoegrrfearmogs)r.a Pmesrs).isPteenrsti sscteantttesrcearstt aerreer s
bya rdeebfiynidtieofinn qituioitne qinusietensiintisveen stiot isvpeattoiasl paantdia lspaencdtrsapl edcetcroalrrdeelactoiorrne leaftfieocntse, fafencdt sl,aargned tleamrgpeotreaml apnodra l
spaantidals pbaatsieallinbea sienlitnerefeinrotegrrfaemrosg rcaamn sbcea nusbeedu, saelldo,walilnogw tihneg tfhuell feuxllpeloxiptalotiiotant ioonf loofnlgo ntgimtiem seersieersi eosfo f
acaqcuqiusiitsiiotinosn. sT.hTeh deidagiargarmams osfo tfhteh teemtempoproarl aalnadn dspsaptaiatli adlidstirsitbriubtuiotino nofo SfASRA Rimimagaegse csocrorrersepsopnodnidnign gtot o
thteh tewtwo oanaanlaylzyezde ddadtaatsaestest asraer eshsohwown nini nFiFgiugruer e2.2 .

FiFgiugruer e2. 2S.pSaptiaatli aalnadn tdemtepmopraolr adlisdtirsibtruibtiuotnio onf oSfASRA Rimiamgaegs efsorf otrheth EeNEVNIVSAISTA Tdadtaastaest eatcaqcuqirueidre dini n
asacescnednidnign (ga)( aa)nadn ddedsecsecnednidnign (gb()b g)egoemometreitersie. s.
ByB yusuinsign gthteh ePSPPS Pmmetehthoodd, a,baboouut t224400,0,00000 aanndd 220000,0,00000 PPSS ppooiinnttss wweerree eexxttrraacctteedd ffoorr tthhee ssttuuddyy aarreeaai n
ina sacsecnednidnignga nadndde sdceesncdeinndginggeo mgeeotmrieest,rrieess,p ercetsipveeclyti.vBealyse. dBoansetdh eosnta ttihstei csatlaatnisatilycaslis athnaatlywsies ptehrafot rwmee d,
petrhfeorsmtanedd,a rtdhed setvainatdioanrdo fdtehveiadteiofonr mofa tthioen dmefeoarsmuraetmioenn mteerarosurriseminetnhte eorrrdoerr ios fi3n mthme ,otyrdpeicra ollfy 3r amngmin, g
tybpeictwalleye nra1nganindg 5bmetwme,edne p1 eannddi n5g momn,t hdeepqeunadliitnygo ofnth tehes pqeucaifilitcyP oSf athned sopnecthifeict yPpS eanofdg orno uthned tcyopvee r,
of ground cover, whereas the refined height measurements have a metric accuracy. The average
measurement density is 100 PS/km2 over the whole area and reaches 1000 PS/km2 in the most
urbanized areas.
Remote Sens. 2016, 8, 846 5 of 17
2.2. Signal Decomposition
Due to the radar viewing geometry, ENVISAT observations are ~3-times more sensitive to
vertical motion than to fault-parallel motion in this area, assuming a fault trend of N30°W and a
strike-slip motion. Previous investigations show that the Avcilar district underwent clear
subsidence [21,22]; this signal can overwhelm the horizontal motions induced by fault movement. In
order to investigate the particularities of these deformations, we apply a signal decomposition
approach that we designed for investigations related to the N30°W striking fault slip. By combining
ascending and descending PS-InSAR observations, the LOS (line of sight) velocities can be projected
onto any desired set of two orthogonal basis vectors under the assumption that the third component
RemoteSens.2016,8,846 5of17
is zero [35]. Such an approximation is particularly suitable for areas around the middle of a straight
fault segment as in the present case.
wherTeahset hteimreefi-sneerdiehs eidgahttam oefa stuhree msteundtsy hraevgeioanm esutrgicgaecsct uvraecryti.cTahl, ebauvte raalgseo mseigasnuifriecmanetn thdoernizsoitnytaisl
1d0i0spPlaSc/ekmme2not vceormthpeonwehnotsle. Ianr eoardaenrd troe aimchperso1v0e0 t0hPe Ss/igknma2l-tion-tnhoeisme orasttiuor, bwaen iezsetdimaaretea st.he mean LOS
velocity between 2002 and 2010. Then, we projected the obtained ascending and descending LOS
2.2. SignalDecomposition
velocities (Figure 3) onto motions in the fault-parallel and vertical direction using a least square
methDodu e[3to5,t3h6e].r aAd aurnvifioewrmin fgaguelto-mpaertaryll,eEl NdiVreIScAtioTno bosfe hrvoaritzioonnstaalr em~o3v-teimmeenstm woares saesnssuimtiveedt,o wvheertriecaasl
mthoe tfiaounltt-hpaenrptoenfdauiclut-lpaar rhaollreilzomnotatilo cnoimnpthoniseanrte wa,aass nsuomt cionngsaidfearueldt tinre tnhde omfoNd3e0ll◦iWng.a Tndhias hstorrikizeo-nsltiapl
mstroitkioe-ns.liPpr emviootuiosni nwveasst iaglaretiaodnys sinhdoweptehnadtetnhtelyA vincfilearrreddis tfrriocmtu tnhdee rGwPeSn tocblseearrvsautibosnid ienn cthei[s2 1a,r2e2a] ;[t3h7i]s,
saiggrneaelincagn woivthe rtwheh eolrmienthtaetihoonr iozfo tnhtea lKmLo ftaiounlts tihnadt uwcaeds sbhyofwaunl btym soevisemmiecn itn.vInesotirgdaetrioton i[n1v8]e,s atisg wateellt haes
pbayr stitcruuclaturirtaiel sstoufdtiheess [e16d]e. formations,weapplyasignaldecompositionapproachthatwedesigned
forinTvhees tidgeactoiomnpsorseeladt ehdotroiztohnetaNl 3a0n◦dW vsetrrtiikcianl gmfaouvletmsleipn.t Bayrec oshmobwinni ning aFsicgeunrde i4nag,ba.n Cdldeaers creenladtiinvge
PmSo-vIneSmAeRnto inbs tehrev faatuioltn-sp,atrhaelleLl OdSire(clitnioeno wf asisg ohbt)sevrevleodc iotine stwcaon sibdeesp orfo tjehcet eKdL ofanutolt,a wnyhidche saigreredess ewteolfl
twwitoho trhtheo tgeocntoanlibc absiasckvgercotournsdu n(ddeexrtrthale cahsasuramctpetri)o noft hthaitst hfaeutlht.i rWdceo fmoupnodn etnhtaits rzeelraotiv[3e5 ]h.oSruizcohnatanl
ampopvroemximenattsi osntriiskpinagrt icNu3la0r°lWy suloitcaablllye foexrcaereedas 5a.r0o umndmt/hyeeamr.i dTdhleiso fdaefsotrrmaigahtitofna upltastteegrmn einst ains ignotohde
pagrerseeenmtecnats ew. ith horizontal velocities from GPS data (see Figure 4a). The quantitative comparison
betwTeehne tthime eh-soerriizeosntdaal taGPoSf tvheelosctiutyd yanrde gtihoen isnuvgegretesdt vheorrtiizcoaln,tablu ItnaSlAsoR svigelnoicfiictya nits hsohroizwonn tianl
dFiigspulraec Aem1,e fnrotmco wmhpiochn ewnets c.anIn seoer dtheart ttohei mInpSrAoRv evethloecistiigesn aalr-et og-ennoeirsaellrya ctioom, pwaeraebslteim waitthe tthhaet mofe tahne
LGOPSS ovbesloecrvitaytiboent wine teenrm20s0 o2f amnadgn20it1u0d.eT ahnedn d,iwreectpioronj,e tchteodugthh ea odbiftfaeirneendcea sisc efonudnindg oann ad fedwes scteantdioinnsg.
LNOoStev tehlaotc itthiees in(Fviegrutered 3h)oorniztoonmtaolt IionnSAsiRn vtheelofcaiutilets-p oanr atlwleol acnodntvineurtoicuasl sdtiarteioctnios n(AuVsiCngT aanleda sKtCsqEuKa rine
mFiegtuhroed A[13)5 f,3it6 w].eAll uwnitifho trhmatf aouf ltth-pe aGrPalSle olbdsierrevcatitoionno. fFhuortrhizeormntoarlem, colveaerm seunbtswidaesncaes swuams eodb,swerhveerde ains
tthweof aaurelta-sp (eFripgeunrde i4cub)l:a rthheo lrairzgoen toanlec oism lopcoanteednt awt tahsen wotecsot nosf iKdeLr eadliginnitnhge amloondge lal ipnrgo.nTohuisncheodr ivzaolnletayl;
sthtrei ksem-sallilp omneo itsio lnocwataesd aaltr etahde yeainstd oefp tehned leanktel yfaiunlfte. rSruedbsfirdoemncteh aeloGnPgS KoLb stheruvsa itsi oanssioncitahtiesda wreiath[ 3th7]e,
astgereepe intogpwogitrhapthhey oarniedn ctaletiaornlyo afstshoecKiaLtefda uwltitthh athtew satseeshpoerw snlobpyesse. iSsumbiscidinevnecset iegaastti oonf [K18L],, ians twuernll, aiss
bfoyusntrdu ocntu ara rleslatutidvieelsy[ f1l6a]t. plain.

Figure 3. Persistent scatterers (PS)-InSAR velocity in the LOS (line of sight) direction for
Figure3. Persistentscatterers(PS)-InSARvelocityintheLOS(lineofsight)directionforascending
ascending (a) and descending geometry (b). Positive means that the ground points move toward
(a)anddescendinggeometry(b).Positivemeansthatthegroundpointsmovetowardthesatellite.
the satellite.
The decomposed horizontal and vertical movement are shown in Figure 4a,b. Clear relative
movement in the fault-parallel direction was observed on two sides of the KL fault, which agrees
wellwiththetectonicbackground(dextralcharacter)ofthisfault. Wefoundthatrelativehorizontal
movementsstrikingN30◦Wlocallyexceed5.0mm/year.Thisdeformationpatternisingoodagreement
withhorizontalvelocitiesfromGPSdata(seeFigure4a). Thequantitativecomparisonbetweenthe

horizontalGPSvelocityandtheinvertedhorizontalInSARvelocityisshowninFigureA1,fromwhich
wecanseethattheInSARvelocitiesaregenerallycomparablewiththatoftheGPSobservationinterms
ofmagnitudeanddirection,thoughadifferenceisfoundonafewstations. Notethattheinverted
horizontalInSARvelocitiesontwocontinuousstations(AVCTandKCEKinFigureA1)fitwellwith
thatoftheGPSobservation. Furthermore,clearsubsidencewasobservedintwoareas(Figure4b): the
largeoneislocatedatthewestofKLaligningalongapronouncedvalley;thesmalloneislocatedat
theeastofthelakefault. SubsidencealongKLthusisassociatedwiththesteeptopographyandclearly
associatedwiththesteeperslopes. SubsidenceeastofKL,inturn,isfoundonarelativelyflatplain.
RemoteSens.2016,8,846 6of17
Remote Sens. 2016, 8, 846 6 of 17
Remote Sens. 2016, 8, 846 6 of 17

Figure 4. Decomposed InSAR velocity in the horizontal (positive means that points move along
Figure 4. Decomposed InSAR velocity in the horizontal (positive means that points move along
NN3300°◦WW)) ((aa)) aanndd tthhee vveerrttiiccaall ddiirreeccttiioonn ((bb));; ((cc,,dd)) aarree tthhee hhoorriizzoonnttaall ((NN3300°◦WW)) aanndd vveerrttiiccaall ccrruussttaall vveelloocciittyy
tthhaatt wwaass iinndduucceedd bbyy tthhee ppoosstt--sseeiissmmiicc vviissccooeellaassttiicc rreellaaxxaattiioonn ooff tthhee 11999999 I˙İzzmmiitt// DDüüzzccee eeaarrtthhqquuaakkeess;;
((ee,,ff)) aarree faFfauigulutl-rtpe-p a4ar. arDallleelcleolam napdnodsve edvr etIinrctSaiAclaRvl e vlveoelcolicotiyctyita yifnt eatrhfteree rhm orroeivzmoinnotgvalit nh(pgeo pstihotiesv te-p smoesiestam-nssei citshvmaits iccpo oveinliatsscs tomiecolrvaeesl taaicxlo anrtegio lanxeaftfieocnt
eofffethcet oI˙zf mtNhi3et0/ İ°DzWmü) z(iatc/)eD aneüdaz rtchtehe qevuaerrattikhcaeqls ud;iabrkelacetcsiok; nba (lrbar)co; k(wc ,adsr)ri anorwe( atsh) eis nhh oo(rawi)z osGnhtPoalSw (Nv G3e0lPo°SWc iv)t yaenliodnc vitethyrti isicnaal r tcehrauiss[ t3aa7lr ev].ael o[3ci7ty].
that was induced by the post-seismic viscoelastic relaxation of the 1999 İzmit/Düzce earthquakes;
33.. EEffffeecct tooff PP(oeos,fst) -taS-rSeee ifsiasmumlti-pcica VrValiliseslc coaoneedll avasestrtitiiccc aRlR veeelllaoaxcxiatayt tiaiooftnenr removing the post-seismic viscoelastic relaxation
effect of the İzmit/Düzce earthquakes; black arrows in (a) show GPS velocity in this area [37].
The post-seismic viscoelastic relaxation effect (PVRE) may affect crustal deformation near large
The post-seismic viscoelastic relaxation effect (PVRE) may affect crustal deformation near
3. Effect of Post-Seismic Viscoelastic Relaxation
elaarrgtheqeuaarktheqs ufaokre sdfeocraddeesc ad[3e8s].[ 3S8t]u. dSiteusd ioens opnopsto-sste-issemisimc idcedfeofromrmatiaotnio nofo ftthhee 11999999 I˙zİzmmitit//DDüüzzccee
earthquakes sTuhge gpeosstt- stehisamt tich vei sPcVoeRlaEst iicn rdeluacxeatdio bny e ftfhecets (eP VeRvEen) mtsa iys acflfeecatr c arunsdta ls hdeofuorlmd antiootn bnee airg lnaorgree d in the
earthquakes suggest that the PVRE induced by these events is clear and should not be ignored in
earthquakes for decades [38]. Studies on post-seismic deformation of the 1999 İzmit/Düzce
PS-InSAR observation period [39]. In this paper, we estimated and removed the PVRE using a
thePS-InSARobservationperiod[39]. Inthispaper,weestimatedandremovedthePVREusinga
earthquakes suggest that the PVRE induced by these events is clear and should not be ignored in the
model-based method following [40]. The detailed model construction and PVRE estimation have
model-baPsSe-dInmSAeRth oobdsefrovlaltoiown inpgeri[o4d0 ][.3T9]h. eInd tehtias ilpeadpemr, owdee lecstoimnsattreud catinodn raemndovPeVd RthEe ePsVtiRmEa utisoinng haa v ebeen
bgeiveenn giinve[m4no0 id]n,e al[-n4ba0ds]e,s dao nmmdee tshkooemdy efso tkleloepwys isnatgre ep[4ds0 e]a.s rTcerh ideb eedsdectraiiinlbeetdhd mi sionsd etehcl ticisoo snnes.tcrtuicotnio.n and PVRE estimation have
Firstbleye,n a g tihverne ein-l a[4y0e],r a vndis scoomelea ksetyic s mteposd aerel wdeascsr sibeetd u ipn tthoi sf osercwtioanr.d simulate this viscoelastic effect on
Firstly, athree-layerviscoelasticmodelwassetuptoforwardsimulatethisviscoelasticeffect
each PS-InSAFRir sptloyi, nat t hwreieth-lainy etrh vei socobesleasrtvica mtioodne pl weraiso sdet ( uFpig tou froer w5)a.r Td hsiem mulaotde ethl ihs avsis cooneela setliac setfifcec ut opnp er crust
oneachPS-InSARpointwithintheobservationperiod(Figure5). Themodelhasoneelasticupper
each PS-InSAR point within the observation period (Figure 5). The model has one elastic upper crust
layer and two viscoelastic layers representing the lower crust and upper mantle, for which the
crustlayerandtwoviscoelasticlayersrepresentingthelowercrustanduppermantle,forwhichthe
layer and two viscoelastic layers representing the lower crust and upper mantle, for which the
Maxwell rheology was applied (Figure 5).
MaxwellMrhaexowleollg ryhewolaosgya pwpasli aepdp(liFeidg (uFrigeu5re). 5).

Figure5.FSigkuertec h5. mSkaetpchs mhoawp sshtohwes vthies cvoisecloaesltaiscticm mooddeell uusseedd fofor rpopsot-sste-issmeiiscm viisccoveilsacstoice lraelsatxicatrioenla exffaetcito neffect
(PVRE)e(sPtiVmRaEt) ieosnti.mation.

Figure 5. Sketch map shows the viscoelastic model used for post-seismic viscoelastic relaxation effect
(PVRE) estimation.
RemoteSens.2016,8,846 7of17
Secondly,thelowercrustanduppermantleviscosityoftheMaxwellrheologyplayanimportant
roleinReemsottiem Seanst.i 2n01g6,t 8h, 8e46P VREeffect[38]. Theseparameterswereinferredfromthepost-s7e iosf m17 icGPS
observationinasimilartimeperiodbyemployingagrid-searchmethod[40].
Secondly, the lower crust and upper mantle viscosity of the Maxwell rheology play an important
Thirdly,wecalculatedthePVREateachPS-InSARdatapointusingthederivedoptimalviscosity
role in estimating the PVRE effect [38]. These parameters were inferred from the post-seismic GPS
parametersandthenumericalcodeprovidedby[41]. TheresultsshowthatthemeanPVREeffect
observation in a similar time period by employing a grid-search method [40].
ongroundTvhierldolcyi, twyei csaalclumlaotesdt cthoen PsVtaRnEt aitn eathche PoSb-IsneSrAvRa tdioatna ppoeirnito uds.inUg sthine gdetrhiveeodp otpitmimaall vviissccoossitiyti es,the
calculaptaerdamPeVteRrsE anids tehset nimumateerdicatlo cobdee p~r2ovmidmed/ byye [a4r1]h. Tohreiz roesnutlatsll syhoinw tthhaet tshteu mdyeaanr PeVaRaEn edffeicst tohne refore
considgerroaubnlde vfoerloicnitvye irst ianlmgothste cfoanuslttanmt oinv ethme eonbtse(Frvigatuiorne 4pce,rdio)d..H Uoswinge vtehre, tohpetimPVal RvEiscroesviteieasl,s tahes mooth
calculated PVRE is estimated to be ~2 mm/year horizontally in the study area and is therefore
spatialpatternintheareaaroundtheKLfault,sothatitsinfluenceontheestimationofthefaultslipis
considerable for inverting the fault movement (Figure 4c,d). However, the PVRE reveals a smooth
notsosignificant.
spatial pattern in the area around the KL fault, so that its influence on the estimation of the fault slip
Atlast,weremovedthePVREfromtheInSARvelocities,inordertoobtainthedeformationsignal
is not so significant.
thatislargAelty lafsrte, ewoef rtehmeopvoedst -tsheei sPmVRicEe ffrfoemct t(hFei gIunSrAeR4e v,fe)l.ocities, in order to obtain the deformation
Tosiganvaol itdhatt hise laerfgfeelcyt sfriene douf tcheed pobsyt-soetihsmericl oefcfaeclt d(Feifgourrme 4aet,ifo).n processes (landsliding, groundwater
extractionTaon davootihde trhse) ,ewffeectlso win-dpuacsesd fiblyt eortehdert hloecadl adteafoursminagtioans pimropcelsesems e(dlainadnslfiidltinegri, nggromunedthwoadte.rW egot
theveleoxctritayctoiofne aancdh oInthSeArsR), wpoe ilnotwb-pyacsas lfcilutelaretdin tghet hdeatma uesainngv aa lsuimepolfen meeigdhiabno friiltnegrinpgo imnetsthwodit. hWine agodt istance
the velocity of each InSAR point by calculating the mean value of neighboring points within a
(filtering length). After filtering the small-scale signal, the relative fault movement becomes more
distance (filtering length). After filtering the small-scale signal, the relative fault movement becomes
visible(Figure6),whichhighlightstherelativemotionsoftheKLfault.Othersmall-scaleprocessesmay
more visible (Figure 6), which highlights the relative motions of the KL fault. Other small-scale
slightlyaffectthedeformationpatternandplayasecondaryroleincontrollingthecrustaldeformation
processes may slightly affect the deformation pattern and play a secondary role in controlling the
inthiscarurestaa.l deformation in this area.

FigureFi6g.uHreo 6r.i zHoonritzaolnvtaell ovceilotycitfiye flidelda laolnonggN N3300◦°WW nneeaar rKKL:L (:a)( aW)iWthiotuhto suptatsipala ftiilatelrfiinlgte; r(bin–gd); (Fbil–tedre)dF iltered
data with different spatial filtering length. Purple boxes show the location of the velocity profile
datawithdifferentspatialfilteringlength.Purpleboxesshowthelocationofthevelocityprofile(A–A’)
(A–A’) shown in Figure 7.
showninFigure7.
4. Modelling and Results
4. ModellingandResults
After removing the PVRE, a velocity profile perpendicular to the fault orientation was
constructed (Figure 7), which was used to estimate the fault slip rate and locking depth based on a
AfterremovingthePVRE,avelocityprofileperpendiculartothefaultorientationwasconstructed
widely-used 2D screw dislocation model [42]. In this model, the fault-parallel velocity ((cid:1874)) as a
(Figure7),whichwasusedtoestimatethefaultsliprateandlockingdepthbasedonawidely-used
function of its perpendicular distance to the fault ( (cid:1876)) can be drawn by:
2D screw dislocation model [42]. In this model, the fault-parallel velocity (v) as a function of its
perpendiculardistancetothefault(x)(cid:1874)c(axn)=be((cid:1848)d/r(cid:2024)a)w×nabrcyt:an((cid:1876)/(cid:1830)) (1)
where (cid:1848) and (cid:1830) are the slip rate and the locking depth of the KL fault, respectively. A grid-search
method was applied to search forv th(xe )sl=ip r(aVte/ aπnd) ×locakricntga nde(pxt/h Dov)er ranges of 0.5–20 mm/year and (1)
0.5–20 km with 0.5-mm/year and 0.5-km intervals. The RMS (root mean square) misfit between the
whereV and D arethesliprateandthelockingdepthoftheKLfault, respectively. Agrid-search
metho dwasappliedtosearchforthesliprateandlockingdepthoverrangesof0.5–20mm/yearand
0.5–20kmwith0.5-mm/yearand0.5-kmintervals. TheRMS(rootmeansquare)misfitbetweenthe
RemoteSens.2016,8,846 8of17
Remote Sens. 2016, 8, 846 8 of 17
modelandobservationforeachcombinationoftheparameterswascalculated,fromwhichtheoptimal
model and observation for each combination of the parameters was calculated, from which the
valuesopotfimthael vsalilpuersa otef tahned slliopc rkaitne gandde plotchkiwnge rdeefiptxhe dwebrye mfixiendi mbyiz miningimthieziRngM tShem RiMsfiSt .misfit.

FigureFi7g.uDree 7c.o Dmecpoomsepdosheodr hizoorinztoanltvale vloecloitcyity(N (N3300◦°WW)) oonn pprrooffiilleess ppeerprpenednidcuicluarl ator tthoet horeieonrtiaetniotant oiof nthoe fthe
fault and comparisons to the model predictions that were inferred from the optimal fault parameters:
faultandcomparisonstothemodelpredictionsthatwereinferredfromtheoptimalfaultparameters:
(a) Original fault-parallel velocity without spatial filtering; (b–d) Velocity profiles obtained from
(a) Original fault-parallel velocity without spatial filtering; (b–d) Velocity profiles obtained from
low-pass filtered data. The blue lines in each subfigure are the forward predictions based on the
low-pass filtered data. The blue lines in each subfigure are the forward predictions based on the
inverted optimal fault parameters. In each subfigure, the gray dots show the original or filtered data
inverted optimal fault parameters. In each subfigure, the gray dots show the original or filtered
along the profile, and the red dots represent the mean values at each distance along the profile. The
dataalongtheprofile,andthereddotsrepresentthemeanvaluesateachdistancealongtheprofile.
location of this profile is shown in Figure 6.
ThelocationofthisprofileisshowninFigure6.
The uncertainty of the obtained optimal slip rate and locking depth were estimated statistically
using the Monte Carlo method [43]. We firstly constructed the 1D variance-covariance matrix of the
Theuncertaintyoftheobtainedoptimalsliprateandlockingdepthwereestimatedstatistically
ascending and descending InSAR data using the method of [44] and generated spatially-correlated
usingtheMonteCarlomethod[43]. Wefirstlyconstructedthe1Dvariance-covariancematrixofthe
noise. Secondly, we obtained the perturbed dataset by adding the noise to the observation. Finally,
ascendinganddescendingInSARdatausingthemethodof[44]andgeneratedspatially-correlated
we searched for optimal parameters based on each disturbed dataset and could analyze the
noise. Secondly,weobtainedtheperturbeddatasetbyaddingthenoisetotheobservation. Finally,we
best-fitting model. We run these steps 500 times in order to obtain a robust estimation about the
searchuendcefrotarinotpyt iomf tahlep paarraammeetteerrss. Tbhaes eddistornibeuaticohn dofi stthuer sbliepd radtaet aansdet loacnkdincgo duelpdtha naarely inzfeertrheedb freosmt-fi at ting
modeMl.oWntee rCuanrltoh seismeusltaetpiosn5 a0n0dt ismhoews ian goerndeerralt ocoonbsitsatienncae rwobituh stthees RtiMmSa tmioisnfiat bmoaupt (tFhieguurne c8e)r. tTahinet yof
theparerasumlte stteartsis.tTichalelyd riesvtreiablsu tai omneaonf tshliep srlaitpe roaf t5e.1a n± d0.4lo mckmin/ygeadre apntdh aa rloeciknifnegr rdeedptfhr oomf 1a.0 M± o0.n5 tkemC arlo
simul(atthieo nmaenand vsahlouwe aandg ethnee roanlec-soingmsisat uenncceerwtaiinthtyt;h FeigRuMre S8)m, siusgfigtemstainpg (tFhiagtu three 8K)L. Tfahueltr iess auclttivseta wtiistthic ally
reveaals sahamlloewan losclkipinrga dteepotfh.5 T.1he±re0fo.4rem, am te/ctyoenaicraallnyd anadl opockteinntgiadllye psetihsmofic1a.l0ly± act0i.v5e kfamul(t tihs elomcaeteadn inv alue
the immediate vicinity of western Istanbul, with important implications as discussed in the
andtheone-sigmauncertainty;Figure8),suggestingthattheKLfaultisactivewithashallowlocking
following section.
depth. Therefore,atectonicallyandpotentiallyseismicallyactivefaultislocatedintheimmediate
In order to test the effect of possible small-scale deformations (such as landsliding), we also
vicinityofwesternIstanbul,withimportantimplicationsasdiscussedinthefollowingsection.
inverted the low-pass filtered data using the same method mentioned above. As shown in Figure 8,
we found that similar results as those inverted from the unfiltered data could be obtained, although
Remote Sens. 2016, 8, 846 9 of 17
the data misfits became smaller as the filtering length increasing. The estimated locking depths tend
systematically to a very small value (<1 km), suggesting possible creep of this secondary fault. Similar
fault creep and shallow locking depth have been found on other strike-slip fault, such as the central
RemoteSens.2016,8,846 9of17
section of the San Andreas fault [45] and western sections of the NAF [46].

FFiigguurree 88.. IInnvveerrssiioonn rreessuullttss:: tthhee ffiirrsstt ccoolluummnn sshhoowwss tthhee sslliipp rraattee vveerrssuuss ffaauulltt lloocckkiinngg ddeepptthh;; tthhee sseeccoonndd
aanndd tthhiirrdd ccoolluummnnss rreevveeaallt hthees tsattaistitsicticd idstirsitbriubtuiotinonof othf ethseli pslripat eraatned alnodc klioncgkidnegp tdhepintfhe rirnefderfrreodm feroamch
evaeclhoc viteylopcritoyfi pler.oIfnileth. Ienfi trhset fciorslut mconlu,mthne,b thlaec kblcaicrkcl ceisrcrleepsr reespenretstehnet othpeti ompatlimsoallu stoioluntiionnfe irnrefedrrferodm fro5m00
5M00o nMteonCtaer Cloasrilmo suilmatuiolantsi.o(nas). S(ah)o Swhsotwhse trheesu rletstuhlat tthwaat swinasfe irnrfeedrrferdom frothme tohreig oirniaglindaalt ad;a(tba–; d(b)–sdh)o swhothwe
trhees ulrtesstuhlatst wthearet inwveerret edinfvreormtedfi ltferroemd dfaitlatewreidth dfialttear inwgitlhen gfitlhteorifn2gk mle,n4gtkhm oafn d2 6kkmm, re4s pkemct ivaenldy.
6 km respectively.
In order to test the effect of possible small-scale deformations (such as landsliding), we also
5. Discussion and Implications
invertedthelow-passfiltereddatausingthesamemethodmentionedabove. AsshowninFigure8,
wefoundthatsimilarresultsasthoseinvertedfromtheunfiltereddatacouldbeobtained,although
5.1. Limitations
thedatamisfitsbecamesmallerasthefilteringlengthincreasing. Theestimatedlockingdepthstend
systeAm antiucmallbyetro oaf vleirmyistamtiaollnvs aloufe t(h<e1 kpmre)s,esnutg gsetustdinyg npeoesdsi btloe cbree epdioscfuthssisedse ctohnadt amryafya ualftf.eScitm tihlaer
ifnatuelrtpcrreeteaptioann dasnhda llcoowrrelocct kuinngdderesptathndhianvge boef enoufro urnedsuoltns.o tAheltrhsoturigkhe -stlhipe fhaeurlet,insu uchseads tPhSe-cInenSAtraRl
tseecchtinoinquoef tphreoSvaidneAs nvderreya rsofbauusltt [r4e5s]ualtnsd awt aes pteirxnels erecstioolnustioofnt htheaNt Ais Fh[i4g6h]e.r than hitherto presented
results in the region, the signal investigated is still rather small. Horizontal motions in the
5. DiscussionandImplications
sub-centimeter scale are very challenging to observe, which is why we have decided to exploit the
average velocity rather than certain time-dependent increments of the data. The advantage of this
5.1. Limitations
approach is that the total displacement values become significant. The disadvantage is that temporal
Anumberoflimitationsofthepresentstudyneedtobediscussedthatmayaffecttheinterpretation
andcorrectunderstandingofourresults. AlthoughthehereinusedPS-InSARtechniqueprovides
RemoteSens.2016,8,846 10of17
veryrobustresultsatapixelresolutionthatishigherthanhithertopresentedresultsintheregion,
thesignalinvestigatedisstillrathersmall. Horizontalmotionsinthesub-centimeterscalearevery
challenging to observe, which is why we have decided to exploit the average velocity rather than
certain time-dependent increments of the data. The advantage of this approach is that the total
displacementvaluesbecomesignificant. Thedisadvantageisthattemporalvariationsmaynotbe
interpreted. Thestrongseasonalityofthesubsidenceregion[22]orthetemporalvariationsofthe
landslides[17]arenotdiscussed,asisthenatureofthestrike-slipfaultmotion. Inthis,wecannot
decipherifthisinferredfaultslipisashort-termbehaviororalong-termprocess,warrantingfurther
studies. Furthermore,futurestudiesmayusethetemporalvariabilityofthedifferentprocessesto
investigatethedifferenttypesofdeformation(faulting,landslidingandsubsidence).
In addition, compared with the descending data, the ascending data are less sensitive to the
horizontalmovementoftheKLfaultduetothegeometricsetting. Thislimitationmayhighlyaffect
theextractionofhorizontalmotionifonlythedescendingdataareavailable. Inthispaper, owing
tothecombinedanalysisoftheascendinganddescendingdata,suchaneffectwouldbedecreased
toacertaindegree. Synthetictestswerecarriedoutinordertoinvestigatehowthehorizontaland
verticaldeformationsignaldependonthegeometricsettingoftheascending,descendingdataandthe
faultorientation. AstheresultsshowinFiguresA2–A5,wefindthattheinputhorizontalandvertical
signalscangenerallybewellrecoveredwiththegeometricsettingoftheInSARdataandthefault
orientationinthisarea. Nevertheless,morecloseinvestigations,suchascontinuouscross-faultGPS
andstrain-meterobservation,arestronglyrequiredinordertoobtainamorerobustestimationofthe
faultmovement.
This study is based on assumptions made from earlier studies on the KL fault mechanism.
Inaddition,itishardtofurtherdistinguishwhethertheKLfaultisasimplefaultoranarrowzone
includingafewsmallactivefaults[18]usingthegeodeticdatashowninthispaper. Weassumeditto
beasingledextralfaultasafirstorderapproximation.
5.2. TectonicImplication
GeodeticresultsinthispapershowcleardextralmovementofthefaultnearKL,revealingthe
movement of an active secondary fault north of the Marmara Sea. Our results of relative motion
(~5mm/year)onthetwosidesofKLprovideanimportantindicationoftheexistenceofthesecondary
faultsinthisarea. Combinedwithpreviousgeologicalandseismicresults[8,16–19],thisactivefault
perhapscanbeinterpretedasanextensionofthenorthernbranchoftheNAF(NNAF)[16,18]. This
interpretationsuggeststwopossibilitiesabouttheevolutionofthenorthbranchoftheNAF:oneis
thattheNNAFdoesnotbendfromNWtoWSWatKLandconnecttotheGanosfaultatthewest,but
extendstoKLnorthwest[16];theotheroneisthattheNNAFmightseparateintotwobranches,one
runningnorthwestintotheKLandtheotheronebendingtotheWSWdirection.
For detailed analysis of the two possibilities, more close observations, such as more dense
near-fieldGPS[36]andnumericalsimulations[47],arerequired. However,nomatterwhichpossibility
revealsthedevelopmentofthenorthbranchoftheNAF,theactivefaultbeneathKLwouldplayan
importantroleinregionaltectonicevolutionandrelatedseismichazardassessment.
Fault complexities at fault bends are observed worldwide. These are commonly explained
by perturbations induced by geometrical complexities in a main fault trace [4]. During multiple
earthquake cycles residual stresses may accumulate and lead to the formation and dislocation of
secondaryfaults. WhetherthehereininvestigatedN30◦Wtrendingfaultonlandisseismogenically
activeisnotknown. However,duetotheshallowlockingdepthshownbyourmodellingresult,the
KLfaultmightbesubjectedtoaseismiccreep. Thisperhapscanexplainthatonlyafewearthquakes
wereobservedinthisarea[48].