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BIAS STANDARDS FOR SIGNAL PROCESSING

A IMS, PROCESSES AND RECOMMENDATIONS

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Coverpicture:Soundpressurelevel(oneminuteaverage)vs.distancetotheclosestshipattheBIASlocation12(BothnianBay).Thefiguresshowthatthenoiseofashipcloserthan5–10kmcanbedistinguishedfromthebackgroundnoise.ByJukkaPajala.

BIAS-BalticSeaInformationontheAcousticSoundscape

TheBalticSeaisasemi-enclosedseawithnineborderingstates.Itconsistsof8sub-catchmentareas(sub-basins)andanumerousofharbours.Theshippingdensityisoneofthehighestintheworld.Itisestimatedthatabout2000sizeableshipsareatseaintheBalticSeaatagiventime.Besidesshipping,existingandplannedwindfarmscontributetotheambientnoiseofthesewaters.

InSeptember2012,BIASstarted.ThisprojectisfundedbyEULIFE+andhasthreemainobjectives.ThefirstobjectiveistoestablisharegionalimplementationofDescriptor11oftheMarineStrategyFrameworkDirectivethroughunderwatersoundmeasurementsthroughouttheBalticSeaandthedevelopmentofuser-friendlytoolsformanagementoftheDescriptor.Thesecondobjectiveistoestablishregionalstandardsandmethodologiesthatwillallowforcross-borderhandlingofdataandresults,whichisnecessaryforanefficientjointmanagement.ThethirdobjectiveistousethemeasurementstomodelthesoundscapeoftheentireBalticSea.

BIASwillsolvethemajorchallengeswhenimplementingDescriptor11intheBalticSea.Intotal38sensorsweredeployedthroughouttheBalticSeain2014tomeasurethenoiselevelsduringtheentireyear.Themeasurementswereperformedbyfollowingthestandardsdocumentedinthisreport.Likewisewerethedataanalysedusingstandardizedsignalprocessingroutines.Resultsweresubjecttoaqualitycontrolandfinallystoredinacommondata-sharingplatform.

BIAS SIGNAL PROCESSING

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Thepresentsignalprocessinginstructionwasdrawnupwithinthescopeoftheresearchproject„BalticSeaInformationontheAcousticSoundscape”.Thisreportcanbecitedasfollows:BetkeK.,FolegotT.,MatuschekR.,PajalaJ.,PerssonL.,TegowskiJ.,Tougaard,J.,WahlbergM.(2015).BIASStandardsforSignalProcessing.Aims,ProcessesandRecommendations.Amendedversion.2015.Editors:VerfußU.K.,SigrayP.


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Contents A.Introduction...................................................................................................................5

B.Scope..............................................................................................................................6

C.Termsanddefinitions.....................................................................................................6

D.AimofBIASsignalprocessing.........................................................................................8

E.Standardsonsignalprocessing........................................................................................9I.Qualitycontrolofdata.............................................................................................................................................9II.Pre-processing........................................................................................................................................................11III.Processing...............................................................................................................................................................13IV.Presentationofresults.......................................................................................................................................16V.DataManagement..................................................................................................................................................21

F.References....................................................................................................................27

G.Appendix......................................................................................................................28I.ShortdescriptionofMatlabscriptsforBIAS...............................................................................................28


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A. Introduction Theambientnoiselevelsintheoceanshasincreasednoticeableoverthepast50yearsduetoincreasedanthropogenicactivitiessuchasshippingandmanytypesofoffshorework.SinceWorldWarII,theaverageleveloftheambientnoiseincreasedby12-15dB(Bjørnø,1998).Soundcanpotentiallyhavenegativeeffectsonmarineorganismsbydisruptingvitalbehavioursorphysiologicalprocesses,inextremecasesevenleadingtotheirdeath(e.g.Fernandezetal.,2005).TheEuropeanUnionthereforeregardstheintroductionofsoundenergyasoneofthethreatstothemarineenvironmentthatrequiresanEUwidecooperativeactionandregulation.ThisisadriverfortheMarineStrategyFrameworkDirective(MSFD),adoptedbytheEuropeanUnioninJuly2008.ThemaingoaloftheMarineDirectiveistoachieveaGoodEnvironmentalStatus(GES)ofEUmarinewatersby2020.Withregardstounderwatersound,Descriptor11oftheMSFDstatesthatGESisachievedwhentheintroductionofenergy,includingsound,isatlevelsthatdonotadverselyaffectthemarineenvironment.Forimplementingthis,amonitoringprogrammehastobeestablishedobservingthecurrentlevelandanytrendofambientnoiseinEuropeanseas.Definingacousticparametersandestablishingstandardsfacilitateregionalmarineenvironmentalmanagementofunderwatersoundandguaranteecompatibleandquality-assureddata.

Theinternationalproject“BalticSeaInformationontheAcousticSoundscape”(BIAS)startedinSeptember2012.ThisprojectisfundedbytheEuropeanCommissionundertheLIFE+programandnationalco-funderstoestablisharegionalimplementationofDescriptor11oftheMSFDfortheBalticSearegion.TheBIASsoundmeasurements,conductedthroughouttheBalticSea,willprovideabaselineofthecurrentlyprevailingambientnoiseforfuturemonitoring.Theprojectalsoestablishesregionalstandardsanduser-friendlymethodologiesthatwillallowforcross-borderstandardizedmeasurements,datahandling,signalprocessingproceduresandtheefficientmanagementofDescriptor11.

BIASreleasedastandardfornoisemeasurementsanddatahandlingin2014andarevisedversionin2015(Verfussetal.,2014;2015).Thecurrentdocumententailsastandardfordigitalsignalprocessing,withthescopeandthetermsanddefinitionsgiveninchapterBandchapterC.Thedocumentdescribestheaim(chapterD)andproceduresofsignalprocessingandthestandardsthatwereadoptedwithintheBIASproject(chapterE),includingqualityassurance(chapterE.I),pre-processing(chapterE.II)aswellasprocessingprocedures(chapterE.III),andrecommendationsonhowtopresentresults(chapterE.IV).AcousticdatasetcharacteristicsandformatsusedintheBIASprojectsaregivenintheDatamanagementsection(chapterE.V).ShortdescriptionsoftheappliedMatlabscriptsaregivenintheAppendix.

Theaimofthisreportistoconstitutethebasisforaregionalmonitoringofhuman-introducedunderwaternoiseintheBalticSeainaccordancewithMSFDdescriptor11thatcanserveasadraftforaEuropeanStandard.

TheBIASSignalProcessingStandardispreparedforBalticSeanoisedataandisbasedonthefollowingpreviouslypublishedstandards:

• IEC1995(EN61260),Electroacoustics-Octave-bandandfractional-octave-bandfilters,InternationalElectrotechnicalCommission,Geneva,Switzerland,1996.


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• IEC60565:2006Underwateracoustics-Hydrophones-Calibrationinthefrequencyrange0.01Hzto1MHz,IEC60565-2006(EN60565:2007,BS60565:2007),InternationalElectrotechnicalCommission,Geneva,Switzerland,2006.

• IEC60050:1994,InternationalElectrotechnicalVocabulary,part801:AcousticsandElectroacoustics,(section801-32coverstermsforunderwateracoustics),InternationalElectrotechnicalCommission(IEC),Geneva,Switzerland,1994.

• ISO1996-1:2006,Acoustics–Description,measurementandassessmentofenvironmentalnoise–Part1:Basicquantitiesandassessmentprocedures.InternationalOrganizationforStandardization,Geneva,Switzerland,2006.

• ISO80000-8:2007.Quantitiesandunits–part8:Acoustics,InternationalOrganizationforStandardisation,Geneva,Switzerland,2007.

• ISO/TR25417:2007.Acoustics—Definitionsofbasicquantitiesandterms.InternationalOrganizationforStandardisation(ISO),Geneva,Switzerland,2007.

• ANSI/ASAS12.64-2009/Part1,2009.QuantitiesandProceduresforDescriptionandMeasurementofUnderwaterSoundfromShips-Part1:GeneralRequirements,AmericanNationalStandardInstitute,USA,2009.

• ANSIS1.11-2004:SpecificationforOctave-BandandFractional-Octave-BandAnalogandDigitalFilters,AmericanNationalStandardInstitute,USA,ReaffirmedbyANSI2009.

B. Scope ThisdocumentspecifiesthesignalprocessingproceduresthatwereadoptedbyallpartnersoftheBIASproject(theBIASbeneficiaries).Itisrestrictedtotopicsrelatedtotheanalysisoftheretrieveddigitizedsounddataandthereforeonlydealswithdigitalsignalprocessing.Itdoesnotspecifydataacquisitionprocedures.Thosearepublishedinthe“BIASStandardsforNoisemeasurementsandDataHandling”(Verfussetal.,2014;2015).Foreachsteprelevantintheprocessingofthedata,ageneraldescriptionwillbegiventowhathasbeendoneintheBIASprojectwithsomejustificationtowhyithasbeendone,followedbyadetailedspecificationonthealgorithmsorproceduresandrecommendationsgivenbytheBIASteam.

C. Terms and definitions Thissectiondefinesthetermsasusedinthefollowingtext.

a. 1/3-octave frequency band Afrequencybandwithabandwidthofonethirdofanoctave.Oneoctaveisadoublingoffrequency,andonethirdofanoctaveisafrequencyratioof21/3≈1.26betweenthehighestandthelowestfrequency(adaptedfromRobinsonetal.,2014).

b. 1/3-octave f i l ter Abandpassfilterwithabandwidthof1/3-octave.

c. ANSI AmericanNationalStandardsInstitute.


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d. Arithmetic mean Thesumofseveralmeasurementsdividedbythenumberofmeasurements.

e. Bandwidth Thefrequencyrangewithinwhicharecordingsystemissensitive.

Thefrequencyrange(inHertz)obtainedbysubtractingthelowerfromtheuppercut-offfrequency.

f . Broadband level Thesoundpressurelevelobtainedoverawidefrequencyrangewithdefinedfrequencylimits.

g. Centre frequency Synonymtomidbandfrequency.

Thecentrefrequency(fm)ofabandequalsthegeometricmeanofthelower(flow)andupper(fhigh)cut-offfrequencies:𝑓! = 𝑓!"#𝑓!!"!.Fora1/3octavebandthecut-offfrequenciesaregivenas

𝑓!"# = 2!!!𝑓!and𝑓!!"! = 2

!!𝑓!(amendedfromANSI,2004).

h. Clipping Clippingoccurswhentherecordingsystemissaturatedbeyonditsmaximumsoundpressureorvoltagecapacity.Thisresultsinunderestimationofsoundlevelsaswellasspectraldistortion.

i . Cut-off frequency ( lower / upper) Synonymoustobandedgefrequency.

Frequenciesofthelowerandupperedgesofabandpassfiltersuchthatthecentrefrequencyisthegeometricmeanoftheloweranduppercut-offfrequencies(amendedfromANSI,2004).

j . Discrete Fourier Transform Thedigital(sampled)Fouriertransformoverafinitenumberofsamples(incontrasttotheintegralFouriertransform,whichisappliedtoacontinuous(analog)waveform).Thisalgorithminvolveslongcomputations,butcanbeappliedtosignalsofanylength,incontrasttotheFastFourierTransform(Bloomfield,1976).

k. Estimate Theruleofmethodofestimationiscalledestimator,andthevaluetowhichitgiveriseinaparticulariscalledtheestimate(Poularikas,1999).

l . Fast Fourier Transform AclassoffastalgorithmimplementingthediscreteFouriertransform,thatefficientlycalculatesthediscreteFouriertransformfromthesampledtimewaveform(Bloomfield,1976,2000).

m. Fourier transform Amathematicaloperation,whichtransformsarepetitivesignalintoasumofharmonicsinewavefunctions.Canbeperformedoncontinuous(analog)signals(integralformulation)anddigital(sampled)signals(discreteformulation)(Bloomfield,1976).


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n. Geometric mean Themeanofnpositivenumbersobtainedbytakingthenthrootoftheproductofthenumbers𝑚 = 𝑚!𝑚!…𝑚!

! .

o. IEC InternationalElectrotechnicalCommission.

p. IEC/ISO band number Indexofthe1/3-octavebands,asdefinedbyIEC,ISOandANSI.Centrefrequencyisgivenfromband

numberxas:𝑓! = 10!!",thusbandnumbers0,18and21havecentrefrequenciesof1Hz,63Hzand

125Hz,respectively.

q. ISO InternationalOrganizationforStandardization.

r . Measurand Thequantityintendedtobemeasured.

s. Ring-test Aninter-organizationcomparisonofsignalprocessingmethods,beingatooltoverifythecorrectpracticeindataanalysis.

t . Spectrum Aquantityexpressedasafunctionoffrequency,eitherasanarrowbandspectrum(e.g.1Hzbands)orasaggregatedbands(e.g.1/3-octavebands)(Robinsonetal.,2014).Spectracanbederivedbyvariousmethods,suchasanFFTorfilteringwithasetofband-passfilters.Acriticalrequirementofaproperspectrumisthatthesumofthepowerinallbandsshouldequalthetotalpowerofthesignal.

u. UTC UniversalTimeCoordinated.

D. Aim of BIAS signal processing ThemainroleoftheBIASsignalprocessingisfourfold:

1.Tocontrolthequalityofdata,

2.Toextractrelevantestimatesoutoftherawdataset,

3.Topresentthepropertiesofdatainanunderstandableway,

4.Toprovideresultsinanappropriateformatforsoundscapemodelling.

Long-termacousticrecordingsresultinextremelylargedatasetsthathavetobeprocessedaswellasstored.Itisthusnecessarytoautomatetheprocessingandtoreducedatabycalculatingestimatesthatarerelevanttoandaccessiblefortheendusers.

Processingofdataisnotuniquelydefined.Thereareanumberofoptionalmethodsthatcanbeemployed.Dependingonthemethodthestatisticalestimatemaychange,however.Theresulting


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valuewillbeinfluencedbyforexamplethewindowsizeusedinestimatingthespectrumortheaveragingtimelength.Theaimofthestandardpresentedhereistomakedatafromdifferentstudiesandanalysescomparableandcompatible.

Itistheenduserthatdefinestheprecisionneededinestimates,what‘relevantestimates’implyandtowhomthepresentationofdataisaimingat.InthecaseoftheMSFDdescriptor11therelevantestimatesaretheannualaveragesofthe1/3-octavebands63and125Hz.BIASintendstoalsoestimateanumberofadditionalparametersbasedonthemeasureddata.

E. Standards on signal processing

I . Quality control of data Qualityassurance(QA)referstotheimplementationofsystematicactivitiessothattherequirementsensuringreproducibleresultsarefulfilled.Forqualityassurance,theanalysisistobedoneinasystematicway,followingguidelinesandstandards.Itentailsmonitoringofprocessesandfeedbackloopswhichconfererrorpreventionandinspectionprocesses.Oneexampleforafeedbackloopisthering-test.Thering-testisaqualityassurancetoolfortheanalysisroutinesofdifferentorganisationsthatshouldreturnsimilarresultstoensurethatthecorrectpracticeindataanalysisisappliedandresultsreproducible.Thestatisticalevaluationandinterpretationoftheco-operators’resultsisanimportanttoolforassessingthequalityandcomparabilityofallparticipants’analyses.Toestablishandensuretherequireddataqualityitisessentialtounderstandanddefinethepurposeoftheconductedstudy.

Conductingsignalprocessingtohighstandardsrequirestheidentificationofpossibleerrorsources,i.e.identifyingwhichprocessesdeliveruncertainresults.Identifyingthoseallowthedefinitionofanuncertaintybudget(alistofpossibleerrors)connectedtosignalprocessing.Signalprocessingishoweveronlyonesourceofpossibleerrors.Onehastobearinmindthattherearemoreerrorsourcessuchasthemeasurand,instrumentationmetrologicalperformance,calibration,sampling,interface,userandenvironmentalconditions.

Assessinguncertaintiesinsignalprocessingisnecessarytoimprovethequalityofthemeasurements.Forgivingameasureofconfidencetoacalculatedvalue,possiblecalculationerrorsshouldbedeterminedandthelikelysignificanceoftheeffectontheresultidentified.Theuncertaintiesconnectedtotheresultsofthesignalprocessinganalysiscanbeexpressedasanintervalinwhichtheerrorvalueswillliewithahighprobability.Theprocessofsystematicallyquantifyingerrorestimatesisknownasuncertaintyanalysis.Therearetwogeneralclassesofuncertainty:

• Randomuncertainty,whichcanbeassessedbyrepeatingcalculationsandexaminingthestatisticalspreadintheresults.Indigitalsignalprocessingitispossibletomakerepeatedcalculationsbyusingthesamerawdata.Randomuncertaintyisameasureoftheprecisioninthecalculations.Highprecisionisobtainedwhenthecalculationsarerepeatableandwithlittledispersioninresults,

• Systematicuncertainty,whichrepresentsapotentialsystematicbiasinananalysis,forexamplecausedbyincorrectformulaforthecalculationorprogrammingerror.Thiscategory


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ofuncertaintycannotbeassessedusingrepeatedcalculations,andmustbeevaluatedbyconsideringthepotentiallyinfluencingfactorsonthecalculationaccuracy.

Makingsurethatworkingroutinesareataproperlevelandincludepersonaltrainingandqualityassurancetoolsminimizesuncertainties.

Recommendedqualityassuranceproceduresandtoolsarethefollowing

• Controlofcomputersystem• Testingofsignalprocessingsoftware• Guidelinesandstandards• Monitoringofprocesses• Feedbackloops

a. Control of computer system OneQAprocedureistonominateonepersonthatisresponsibleforauthorizinganysoftwaretobeused.Withthehelpofasampledatasetitcanbedeterminedifvaluescalculatedbythesoftwarearecorrect.Thecontrollingsystemforsoftwareshouldeffectiveandauditable:eachcomputershouldhavealogwithinstalledhardwareandsoftware.Anynewsoftwareormodificationstoexistingsoftware,includingnewreleasesofcommercialpackages,hastoberecordedinthelogwithfirstdateofuse.Itisthenpossibletodeterminewhichversionofthesoftwarewasinuseatanyparticulartimeshouldanerrorneedtobetraced.

Itshouldbeassuredthat:

• Onehascontrolofwhatsoftwareisloadedontotheanalysiscomputer,• Allcomputersystems,includingsoftware,havebeencheckedtoensurethattheyrecordand

processdatacorrectly,• Allsoftwareissecuredagainstunauthorizedchanges,• Alogisusedcapturingsoftwareupdatesandsoftwarechecksonthecorrectfunctioning

afterupdate,• Aprocedureisinplaceforaregularbackupofdatastoredonthecomputers.

b. Testing of a signal processing software SoftwaretestingisaQAprocedureandinvestigationconductedtoprovideuserswithinformationaboutthequalityoftheproduct.Thetestingprocedureconsistsoftestspecification,testexecutionandtestreporting.

Whendecidingonsignalprocessingsoftwareitshouldbetestedifitfitsforonepurpose,andthatitisreliable,efficientandmaintainable.Itshouldbeassuredthat:

• Itmeetstherequirementsthatguideditsdesignanddevelopment,• Itrespondscorrectlytoexpectedinputs,• Itperformsitsfunctionswithinanacceptabletime,• Itachievestheresultitsusersdesireanditcanbeinstalledandruninitsintended

environments.


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InBIAS,Matlabscriptswerecompiledspecificallyforthepre-processingandprocessingofBIAS-data,whichcouldbeusedbyeachbeneficiary,althoughtheuseofthescriptswasnotobligatory(seering-test).

c. Guidelines and standards GuidelinesandstandardsareQAtoolsensuringthatproceduresaredoneinacomparablewaywithinaprojectteam.

InBIAS,aworkinggroupwasestablishedforthedevelopmentofthesignalprocessingstandardsandanyguidelinesgiventherein,discussingandagreeinguponwhichstandardstouseforthedigitalsignalprocessingofBIAS.Theresultsarecompiledandpresentedinthecurrentdocument.

d. Monitoring of processes Processesneedtobemonitoredforenablingtheirtraceabilityfromtherawdatatotheresultsandviceversa.InBIAS,instructionsandprotocolswerepreparedtailoredtotheBIAS-needstoguarantytheconductionofproceduresinastandardisedwaybyallbeneficiaries.

e. Feedback loops Feedbackloopsenablethecrosscheckingofroutinesforatimelydetectionoferrors.OnefeedbackloopusedinBIASisaring-test,forwhichidenticalsoundsamples,providedbytheQAcoordinator,wereanalysedbyallbeneficiaries.ThesampledatapackageincludedsignalsamplesinWAVformat,totalhydrophonesensitivityorfull-scalevalueandsetgain.Additionally,software(Matlabscript)foranalysiswasalsoincluded.EachBIASbeneficiarycarriedoutthedataanalysisonthesampledatausingthemethodandsoftwareasusedfortheanalysisoftheBIASdataobtainedatthemeasuringstationstosecurethattheresultsarecomparable.TheycouldchoosetoeitherusethecommonMatlabscriptdevelopedfortheBIASanalysisortousetheirin-housesoftware.Itisimportantthatthesamemethodandsoftwareisusedinthering-testthatlaterwillbeusedfortheBIASrawdataanalysis.IfothersoftwarethanthecommonMatlabscriptwasusedthenithadtobeassuredthattheheadingformatwasadaptedtothein-housesoftwareasrequired.

Errorsthatcanbeidentifiedwitharingtestare:

• Applicationofwronghydrophonesensitivityand/orinstrumentgainfactors,• Choosingthewrongsignalchannelwhenmorethanonechannelwasused,• Different1/3-octavefilterconfigurations,• Individualorunclearconfigurationofthefileheading,• Differencesbetweensoftware,softwarescriptsorsoftwareversionsused(theseweresmall

inBIAS,lessthan1dB).

I I . Pre-processing Pre-processingisabasicstepinsignalprocessingtopreparedatafordataanalysisandtoassessthequalityofthedata.

Thepre-processingprocedureinBIASconsistsofanumberofconsecutivestepsasfollows:

• Measuringself-noise,• Organisationofrecordeddata,


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• Testingofdatacoverage,• Testingoffilesizeandfilelengthoftherecordedfiles,• Testingofnon-numericalvaluesintherecordeddatafiles,• Testingofclipping.

a. Measuring self -noise Itisimportanttoreassurethattheself-noiseofeachrecordingsystem(includingtheanchoringsystem)doesnotexceedtheambientnoiselevelsprevailingatthemeasuringstation.Thisshouldbedonebymeasuringandcomparingtheself-noisetotherecordednoiselevels.

b. Organisation of recorded data Foreachstation,theamountofdatahastobedetermined,i.e.thenumberoffilespermonthandstation,andthecorrespondingfilesizes.Alldatafilesforonestationandaspecificmonthareplacedinacorrespondingdatafolder.Datarecordedbeforedeploymentafterretrievalofthesystemaretoberemoved.Datarecordedduringdeploymentandretrieval,whilethedeploymentshipwasclosetothesensorandcontributedtotherecordedambientnoise,arealsotoberemoved.

c. Testing of data coverage Forcalculatingthedatacoverage,thetimeanddurationofrecordeddataarecomparedrelativetotheplannedrecordingtimeandduration.Thecoverageisgivenaspercentageofperiodcoveredperperiodplanned.

d. Testing of f i le size and f i le length Pre-processingshouldentailatestofthefilelengths.IntheBIASprojectaminimumof15minutesperhourrecordingsarerequired.TheMatlabscriptbias_gaps.m(seeSectionG.I.d)notesthetimedifferencebetweentherecordinglengthandtherequiredminimumtimeof15minutes.Thisscriptteststhetimelengthandthesizeoftherecordedfilesbyreadingtheheaderofthefiles.Thetestofthefilelengthisdonetoassurethatallfileshavethesamelength.

e. Testing of non-numerical values Fileswithcorrectlyrecordeddatacontainonlynumericaldata.Inthescriptbias_mean.m(SectionG.I.a)thequalityofthedatasamplesarecheckedfornon-numericalvaluesNaN(not-a-number)andInf(toohighvalueforanumericalrepresentation).NaNistheIEEEarithmeticrepresentationforNot-a-Number.ANaNisobtainedasaresultofnotdefinedoperationssuchas0.0/0.0.InfreturnstheIEEEarithmeticrepresentationforpositiveinfinity.Infinityisalsoproducedbyoperationssuchasdivisionsbyzero,(e.g.1.0/0.0).IfNaNandInfareobtainedinthedatathesevaluesareomittedpriortoprocessing.ThepresenceofNaNorInfintherawdatacanleadtoerrors,whicharedifficulttotrace,asthebehaviourofprocessingfunctionswhenencounteringNaNorInfcannotalwaysbepredicted.

f . Testing of cl ipping Whenreceivedsignalsareofhighersoundpressurethanwhatcanbepickedupbytherecordingsystem,thesystemgetssaturated.Thecorrespondingdigitisedvaluewillreturnthemaximumsoundpressurethatthesystemisabletorecorded,whichislowerthanthetruevalueofthesignal.Thisphenomenoniscalledclipping.Fordeterminingthequalityofdata,theamountofpositiveandnegativeclippingistobequantified.Theamountofclippingiscalculatedandpresentedaspercentageofclippeddatasamplesforaperiodof20s.Therecommendationistoflagforclipping


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whenatleast0.1%ofthesamplespersecondofdataisclipped.Clippingoflessthan0.1%ofthesampleswillaffecttheestimatesoftheanalysisinsignificantly.Informationontheflaggeddatashouldbenotedintheprocessingprotocolforfurtherconsiderationandtracking.Anyfurtherproceduresdecideduponwithregardstotheflaggeddatashouldbetrackedcarefully.

TheMatlabscriptsdesignedfortheBIASpre-processing(SectionK.I)areusedondatarecordedwithLoggerheadandWildlifeautonomoushydrophonesensors.

I I I . Processing ProcessingofdataconstitutesthemainanalysisoftherawdatawiththeaimofextractingthefundamentalmeasuresneededformodellingsoundpropagationandtosumupthestatisticsforthenationalresponsibleagenciesandtheirreportstotheEuropeanCommission.TheCommissionDecision2010prescribestheEuropeanmemberstatestomonitorunderwaternoiseinthe1/3-octavebandsaround63and125Hz(CommissionDecision2010/477/EU,2010).

1/3-octavebandanalysisisawell-establishedmethodtofilterasignalwithabankofoverlappingfilters,allwiththesameQratio,whichistheratiobetweenbandwidthandcentrefrequency.Thespecificationsforsuchfilterbanksarewellestablishedininternationalstandards(IEC1995(EN61269),1996andANSI,2004).Thereareseveralreasonsforchoosinga1/3-octavebandanalysis;mostimportantly,therearephysiologicaljustifications:Substantialexperimentalevidencefromhumans(Scharf,1970)andothermammals(Fay,1988)showthatthemammalianearcanbewellmodelledbyafilterbankconsistingofoverlappingfilters,roughly1/3-octavewide.Thefilterbandwidthisknownasthecriticalbandwidthandcanbemeasuredexperimentallybymaskingexperiments.Thedetectionthresholdofapuretoneismeasuredwhileapplyingnoisewithincreasingbandwidtharoundthetone.Whenthebandwidthofthenoiseislargerthanthecriticalbandwidth,thedetectionthresholdofthetoneisconstant,i.e.independentofthenoisebandwidth.Whenthebandwidthofthenoiseissmallerthanthecriticalbandwidth,thedetectionthresholdofthetonedecreaseswithdecreasingnoisebandwidth.Thecriticalbandwidthisthusdeterminedasthebandwidthwherethethresholdstartstodecrease.Asimpler,butindirectestimateofthefilterbandwidthisaccomplishedthroughmeasuringtheso-calledcriticalratio(Fletcher,1940).Thecriticalratioistheratiobetweentheintensityofapuretonesignalandthespectrumdensitylevelofabroadbandnoisemasker(whichhasaflatfrequencyspectrum)atthedetectionthresholdofthemaskedtone.BecausethenoiseisgiveninunitsofintensityperHz,thecriticalratiowillautomaticallybegiveninunitsofafrequency.Asubstantialnumberofstudieshavebeenconductedwherecriticalbandand/orcriticalratioweremeasuredindifferentmarinemammals.Thesestudiesincludebottlenosedolphin(AuandMoore,1990),harbourporpoise(Kasteleinetal.,2009)andharbourseal(Southalletal.,2003)andaregenerallyconsistentwithaconstant-Qfilterbankmodel,althoughwithconsiderablevariation.Inactualmeasurementsthebandwidthsderivedfromcriticalratiomeasurementsareusuallyconsiderablysmallerthanthosederivedfromdirectmeasurementsofthecriticalband.ThecriticalbandwidthandthecriticalratiovaluesarenotthesamebecausecentralassumptionsmadebyFletcher(1940)inderivingthecriticalratioarenotmetbythemammalianear.

Thusa1/3-octavefilterbankappearstobeausefulfirstapproximationformodellingtheabilityofmarinemammalstodetectnarrowbandsignalsinnoise.


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1/3-octavefiltershavetraditionallybeenmeasuredusinganaloguefiltersbuthavenowbeenalmostentirelyreplacedbydigitalsignalprocessingequivalents.Themostdirectwayistouseasetofdigitalband-passfilters,butsuchfilteringcanbeslowanddifficulttoimplement,andgreatcarehastobetakentomakesurethefiltersarestable.Themainproblemwithadigitalfilterbankisthataverylargenumberoffiltercoefficientsisrequiredtocoverthelowfrequencies,oralternatively,asdoneinthefiltbankfunctionforMatlab,recursivelydown-samplethesignal.AmuchfasterandsimplerapproachistousefiltersbasedonaFastFourierTransformation(FFT).ThefiltersareconstructedtoconformascloseaspossibletotheIEC/ANSIstandardforthistypeoffilters.

Centre,loweranduppercut-offfrequenciesofthestandard(IEC/ANSI)filtersaregivenas:

𝑓! 𝑥 = 𝑓!𝐺 !!!" !

𝑓!"# 𝑥 = 𝑓! 𝑥 𝐺!! !

𝑓!!"! 𝑥 = 𝑓! 𝑥 𝐺! !

where

fmisthecentrefrequency

flowisthelowercut-offfrequency

fhighistheuppercut-offfrequency

xistheIEC/ISObandnumber,

fristhereferencefrequency(1,000Hz)

Gistheoctaveratio(base10system)with𝐺 = 10! !"

Anothercommonstatisticalquantitywidelyusedinnoiseengineeringisthepercentilelevel.ItisdefinedasthelevelLNthatisexceededforNpercentofthetimeintervalconsidered.Forexample,L1isthelevelthatisexceeded1%ofthetime.TheL1canbeusedasameasureforthemaximumlevel.Itisamorerobustestimatethanthesinglemaximuminthedata,sincetheabsolutemaximumispronetoheavybiasfromsingularevents,suchasrattlingoftheanchoringsystemorelectrictransientnoise.Accordingly,L99andL95areusedtodescribetheminimumlevel.L50isthemedianlevel.

ThefundamentalrequirementoftheBIAS-processingistoprovidemeansoundpressurelevelsinthe1/3-octavebandscentredon63Hzand125HzasrequiredbytheMSFD.ThefinalversionoftheReportoftheTechnicalSubgrouponUnderwaterNoiseandotherformsofenergy(VanderGraafetal.,2012)pointsoutthatambientnoisepeaksathigherfrequencylevelsthanthesetwofrequenciesbands,especiallyinshallowwater,suchastheBalticSea.TheTechnicalSubgroup(TSGNoise)thereforesuggeststhathigherfrequencybandsshouldalsobemeasuredandanalysed,astheymayprovetobevaluableinfuture.TheBIASteamsharesthisviewanddecidedtoadditionallyprocessthe2,000Hz1/3-octaveband.Furthermore,thebroadbandsoundpressurelevelsaredetermined.


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Processingofthesounddataincludes:

• Filteringdata,• Analysingdata.

Processingshouldbeperformedonlyonquality-controlledandpre-processeddata,sothattheoutputhassufficientqualityforanymodellingandreporting.Inreality,however,theremaybeaneedforadditionalqualitycontroloftheoutputtorevealirregularitiesnotcapturedbythepre-processing.

a. Filtering data Theextractionoftheenergyinthethree1/3-octavebandsismadewithanFFT-filter.Thisfiltercalculatesthesumoftheenergyfromfrequencybinscoveredbythefrequencyrangeofthe1/3-octaveband.ThespectrumisderivedbycalculatingtheDiscreteFourierTransform(DFT)ofthesignal.ThefiltersusedinBIASarebandsnumber18,21and33.Bandnumber18and21arethe1/3-octavebandscentredat63Hzand125Hz,respectively,asrequiredbytheMSFD,whilenumber33iscentredat2000Hz(Table1).SeveraladjacentFFT-binscanbesummedtoapproximatea1/3-octavebandfilter.Thebandwidthwillhowevernotmatchexactly,asthereisafinitenumberofbinsperFFT-filter.Anadjustmenttermisaddedtocorrectforthis.

𝐵𝑊!"##$!%&"' = −10 log!"!!!"#$!%!!!"!!!!"#

,

where

BWcorrectionisthecorrectionfactortoaddtothesumacrossbins,

BWactualistheactualbandwidthvalue.

1/3-octavefiltersrealisedasFFT-filtersareverysteep,muchsteeperthantraditionalhardwarefilters,butstillwithintheIEC/ANSIspecifications.Filtersathigherfrequenciesfitbettertothestandardwhereasthediscrepancybecomessubstantialatthelowestfrequencies.

Withregardstothefiltering,theBIASrecommendationistoderivetheDFTwithanominalbandwidthof1Hz.ThisisacompromisebetweentimeresolutionandthepossibilityofimplementingFFT-basedband-passfilterswithreasonableshapeevenatlowfrequencies.Usingasegmentsizeof1sfortheDFT,thenominalbandwidthoftheDFT-binsbecomes1Hz.

Table1Informationonthe1/3-octavebandfiltersusedinBIAS.FlowandisFhigharethelowerandhighercutofffrequencies,respectively.Fmisthecentrefrequency.‘Bandwidthcorrection’isexplainedinthetext.

IEC/ANSI

bandno.

Nameofband Flow

(Hz)

fm

(Hz)

Fhigh

(Hz)

Numberof1Hzbands

Bandwidthcorrection(dB)

18 63 56.2 63.1 70.8 14 0.17

21 125 112.2 125.9 141.3 29 0.1

33 2000 1778 1995 2239 460 0.01


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b. Analysing data TheBIAScalculationoftheaverageisdoneinanumberofconsecutivesteps.Thebasisforthesestepsisthepre-processeddataofrecordedtimeseriesfromeachBIAS-beneficiary,withdifferentsamplingratesdependingontypeofsensorusedbythebeneficiary.Inthefirststep,anFFT-analysisisdoneoverconsecutive1-secondperiods,givingamplitudespectrawitha1Hzresolution.Inthesecondstep,thesoundpressurelevels(SPL)asdefinedinVerfussetal.(2014,2015)arecalculatedintherequired1/3-octavebandsover1second.The1-saveragesarethenfurtherprocessedtoaveragesover20seconds.

Estimatessuchashourly,dailyandmonthlyaveragesarecalculatedbasedonthe20-saverages,eventhoughthesearenotrequiredbytheMSFDdescriptor11.Finally,theannualmeanisalsoderivedusingthe20-saverages.InBIASmonthlyandannualarithmeticmeansandthepercentilelevelsareestablishedfor63,125and2,000Hzaswellasforthefrequencybandfrom10to10,000Hz.

ForspatialmodellingtheBIAS-recommendationistousethe20-secondaverageddata.Thisisacompromisebetweenasufficientlylongtimeintervaltoobtaingoodestimatesofthemeanandanintervalshortenoughforthenoiselevelfromnearbyshipstoremainapproximatelyconstantwithineachsegment.

IV. Presentation of results Thissectionshowsexamplesforcommonorusefulrepresentationsofambientnoisedataforastandardisedanduniformpresentationofnoisemeasurementresults.Formattingaspectsofgraphicalrepresentationofdata,suchaschoosingameaningfulaxisrange,captionsize,whetherornottoincludeagrid,orwheretoplacethelegend,willnotbegivenhere.

ForthedataobtainedintheBIASprojecttheBIASbeneficiaryagreedonthefollowinggraphicalpresentationsofthenoisemeasurements:

• Levelversustime,• 1/3-octavespectrum,• Levelstatistics:levelhistogram,cumulativedistribution,percentilelevels.

Thegraphsarebasedonsoundpressurelevelsthatwerecomputedinstepsof1second.

Theexamplesshownhere,inparticularthosefromtheBIASposition31(Fehmarnbelt)showratherhighsoundpressurelevelvaluescomparedtomeasurementsfromotherplacesintheBaltic.ThisreflectsthehighambientnoiselevelscausedbyaveryhighshippingdensityinthiswesternBalticarea.

a. Level versus t ime InLevelversustimeplots,thesoundpressurelevel(SPL;definedinVerfussetal.,2014,2015)isusuallypresentedinaclassical"stripchart"diagram.Thesimplestoptionforalevelversustimeplotistoplotthe1-secondlevels,i.e.anSPLwithanintegrationtimeover1second,theoutcomeofthefirstanalysisstepwithoutfurtherprocessing.Anexampleforthe1/3-octavelevelsforthe63Hzand125HzbandsaswellasthebroadbandleveloverthewholerecordingbandwidthisgiveninFigure1.


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Thebroadbandlevelisusefulforaplausibilitycheckofthedata,asthe63Hzand125Hzlevelscanneverexceedtheoveralllevel.

Figure2showsthe20-second-averagesoundpressurelevelsofthedatashowninFigure1,meaningthattheyareslightlymoreprocessed.

InBIASitwasdecidedthatthetimescaleshouldrefertothestartofanaveraginginterval,whichwasimplementedinFigure2:Adatapointate.g.13:05representsanaveragingintervalfrom13:05:00to13:05:59.

Figure1.TwentyminutesrecordingfromtheBIASstation31,Fehmarnbeltwithashippassingbyverycloselyat13:04.Thecurvesshow1-secondsoundpressurelevelsofthefirstanalysisstepwithoutfurtherprocessing.

Figure2.20-second-averagelevels(20secondsLeq)computedfromthedatashowninFigure1.


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b. 1/3-octave spectrum Amorecomprehensivedescriptionofthenoisemeasurementsrequiresthecalculationofthefrequencyspectrum.Forunderwaterambientnoise1/3-octavebandsisusuallyanadequatefrequencyresolution.Analternativespectralrepresentation,whichwillnotbefurtherdiscussedinthecurrentdocument,isthenarrowbandspectrum(usuallyin1Hzintervals).Suchapresentationismoresuitablewhentonalfeaturesofasoundsignalshallbeanalysedindetail,e.g.inacousticshipsignaturesorwindturbineoperatingnoise.

Examplesof1/3-octavespectraareshowninFigure3.Themaximumfrequencythatcanbedisplayedinaspectrumdependsonthefrequencyresponseoftherecordingsystemandthesamplingfrequencyused.FortheWildlifeAcousticsSM2Mwithasamplingfrequencyof32kHz,forexample,thehighestusable1/3-octavebandis12.5kHz.

Figure3.1/3-octavespectrum(60secondsLeq)fortwopointsintimefromFigure2:Trianglesshowthecloseapproachofashipat13:04,andopencirclesshowthespectrumtenminuteslater.

c. Level histogram and cumulative distr ibution Amethodtoobtainstatisticalinformationfromnoiserecordingsistoplotahistogram,adistributionofthebasic1-secondlevels(Figure4).Iftwoormorehistogramsshallbedisplayedinthesamediagram,straightlines(Figure5)maybemorecomprehensiblethantheclassicalbargraphstyle.Inbothfigures,thevaluesarenormalized.

Attimes,acumulativedistributionisshowninsteadofahistogram(Figure6),representingthepercentageofmeasurementvaluesthatarelowerorequaltothevaluegivenonthey-axis.However,littleadditionalinformationcanbeobtainedfromitcomparedtothelevelhistogram.Featuressuchastheskewnessorasecondarymaximum,whichmaywellbeseeninahistogram,aredifficulttorecognizeinacumulativedepiction.


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d. Percenti le level Percentilelevelscanbecombinedwithalevelversustimediagramandalsowithaspectrumdisplay.PossiblerepresentationsareshowninFigure7andFigure8.Asbefore,thegraphsarebasedon1-secondaveragesofthesoundpressurelevel.

Figure4.Levelhistogramsof1secondvaluesfor63Hz1/3-octavebandandfortheoveralllevel,computedfromthreemonthsofrecording(dutycycleis20minutesofrecordingperhour).

Figure5.AlinegraphismorecomprehensiblethanthebargraphstyleofFigure4.,iftwoormoredistributionsaretobeshowninthesamediagram.


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Figure6.100-CumulativepercentageofthedatashowninFigure1.

Figure7.Dailypercentilelevels(i.e.intervallength=86400s)ofthe125Hz1/3-octavebandatposition31,Fehmarnbelt,forJanuarythroughMarch2014.


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Figure8.Percentilelevelsatposition31,Fehmarnbelt,forJanuarythroughMarch2014.Thestatisticalanalysisisbasedon2.592·106values(0.333·86,400secondsperday·90days),sincetheprimarydataintervalis1sandtherecordingdutycyclewas20m/60m=0.333.

V. Data Management Thequalityofthedatamanagementisofhighimportancesinceitwilldirectlyinfluencethemanagementoftheresultsandinparticularthemodellingtasks.

Acousticdata,onceprocessed,needstobesharedinordertoprovideacommondatasettobeusedformodelling.Sincethemodellingismostlydoneataregionalscale,thedatamanagementruleswillensureuniformityanduniversalityoftherepresentationandthestorage.Aspecialcareshouldbetakentothefollowings:

• Theoverallvolumeofacousticdatacanrapidlybeveryhigh.Itisrecommendedtohandledatainchunksnotlongerthanone-monthperiods;

• Non-acousticparameterssuchasinstrumentgain,samplefrequencyorhydrophonedepth,shouldbereportedwithamaximumofcare.Automaticnumericaltranscriptiontoolsshouldbedevelopedsince:

o Themanualtranscriptionoftheseparametersfrompaper-formsfiledat-seaisapotentialsourceoferrors;

o Themanualtranscriptionoftheseparametersintheprocessingtoolsisapotentialsourceoferrors.

• Thequalitycheckoftheprocesseddatashouldbedoneusingallsortsofdataofopportunity.Forinstance,thedepthofthehydrophoneshouldbecomparedtothebathymetricmaptoverifytheconsistencyofthevaluesreported.

ForBIAS,thefollowingcommonguidelinesandformatsaredefinedwhichwillensureaccessandhandlingoftheprocesseddatainauniformedanduniversalmanner.Therefore,thissectionaddresses:


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• Theproceduretodeliverthefilesinadatasharingplatform;• Thecommonconventionstobeadopted;• Theformatofthefilesthatwillcontenttheprocesseddatatobeshared;• Thecontentofthefiles.

a. Delivery procedure Thedeliveryprocedure(Figure9)isspecifiedformaximizingthelevelofefficiencywhenmultipleorganizationexchange,processandexploittheprocessedacousticfiles.Theprocedurecanbeimplementedforanyperiodoftime.IntheBIASproject,ithasbeendecidedthateachperiodisequaltoacalendarmonth.Theprocedureincludesaqualityassessmentphasewhichobjectiveistoinsuretheconsistencyofthedatasetandtoavoiderrorsbeforethedatasetismadeavailable.

Twolevelsofresponsibilityhavebeendefined(Figure9):

• Thebeneficiarylevelcorrespondstoorganizationsthatareresponsibleforimplementingthemeasurementsandthesignalprocessing.Beneficiariesareresponsibleforarchivingthedataissuedfromtheirmeasurementstations,andtosplitthedatasetintogroupsforeachperiodoftime(inBIAS,eachcalendarmonth).Theprocessingoftherawdataisperformedforeachperiodseparately.Headerinformationareupdatedaccordinglytoinsurethatmeta-dataassociatedtoeachdatasetiscorrect.Somequalitycheckshouldbeperformedinordertoavoidanomaliesintheprocessedfilesproduces.

• Thequalitymanagerlevelcorrespondstoauniqueorganizationthatisresponsibleforqualitycheckofalltheprocesseddata.Thequalitymanagerwillgatherthedatafromeachcontributorsorbeneficiaries,andwillperformthefollowingqualityverificationsinordertoensure:

o Thatdatahavebeenprocessedforeachmeasurementstation;o ThatthefilenamesarecompliantwithspecificationdefinedinsectionE.V.c;o Thattheprocesseddataisconsistentwiththedeploymentperiodsforeach

measurementstation;o Thatallthedataarepresentforthegivenperiod;o Thatallexpected1/3-octavebandshavebeenprocessed;o Thatallfilesarenotemptyorsuspiciouslysmall;o Random1validationofmeasurementstationpositions;o Randomcheckoftheheader;o Randomcheckoftheformat.

1Randomvalidationshouldbedoneonaminimumof5filespermeasurementperiod.


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Figure9.Datamanagementprocedureoftheacousticfiles.

b. Common Conventions Theprocessedacousticdatasetaremadeoftheacousticdataitself,butalsoofdescriptivedatasuchastimeofmeasurementandposition.Thosedatashallbereleasedaccordingtothefollowingconvention.

i. Acoustic quantity to be delivered for the modelling

Theacousticquantitytobedeliveredforthemodellingis20-secondaveragesoundpressurelevels.

ii. Time convention

AlltimeindicationsshouldusetheUTCformat.

iii. Position convention

Alllatitudeandlongitudearetobeexpressedindecimaldegrees.PositivelatitudesaretowardsNorth.PositivelongitudesaretowardsEast.

c. Format Thissectiondescribestheformatofthefilescontainingtheprocessedacousticdata.FilesaretobegivenasASCIIfiles.ThestandardC-languageconventionisusedtodescribetheformatfornumbers,asillustratedinTable2.


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Table2.FormatsofnumbersinstandardC-languageconvention.

Format Explanation Example

%03dIntegercodedwith3digits.Ifthevalueislessthan100,forcethenumbertobepaddedwith0s.

074

%05dIntegercodedwith5digits.Ifthevalueislessthan10000,forcethenumbertobepaddedwith0s.

01984

%8.2fFloatingpointwrittenwithmaximum8charactersandwith2decimalsdigitsprintedafterthedecimalpoint.

534.24


98.98747263

%5.1fFloatingpointwrittenwithmaximum5charactersandwith1decimaldigitprintedafterthedecimalpoint.

234.6


9.98747263

i. Content of the processed acoustic files

Eachfilehastocontainthevaluesofonlyonesinglebandwidthoftheprocessedacousticdata.Theamountofdatacontainedineachfileisnotlimited.Itishoweverrecommendedtorestrictthefilelengthtoonemonthofdata.

ii. Names of the processed acoustic files

Eachfileistobenamedusingthefollowingconvention:

StationIdSSS_BBBFFFHz_StartYYYYMMDDHHMMSS_EndYYYYMMDDHHMMSS.asci

Where:

• SSSistheStationId,format:%03d;• BBBisakeyworddescribingthebandwidth.Itshallbe‘ThirdOctave’or‘BroadBand’

accordingtothenatureoftheacousticdatathatisstoredinthefile;• FFFistheroundedcentralfrequencyofthebandwidthwhenBBBisnot‘BroadBand’;format:

%05d;• Startdesignatethetimeofthefirstacousticdatacontainedinthefile;• Enddesignthetimeofthelastacousticdatacontainedinthefile;• YYYYMMDDHHMMSS:Year,Month,Day,Hour,Minute,Second

d. Content of the processed acoustic f i les Eachfileismadeofaheaderandatable.Theheaderofthefilegivesinformationaboutthemeasurement.Theheaderwillallowtheuserofthefiletogetthecontextofthedatathatispresentinthetableofthefile.Thefollowingsectiondescribeshowtoformattheheaderandthetable.


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i. Header

Theheaderofthefile

Organizationname %Issuedby StringStationId %StationId Integer%03dStationName %NameoftheStation StringLoggerId %DataLoggerunitId StringDataType %Typeofacousticdata ‘SPL’or‘SEL’dBunit %Unitsoftheacousticdata StringBandType %ThirdOctave/Broadband StringFc %Centralfrequencyoftheband Float %8.2fFmin %Minimumfrequencyoftheband Float %8.2fFmax %Maximumfrequencyoftheband Float %8.2fWindow %Processingwindow(sec) IntegerLatitude %LatSigneddecimaldegrees,WGS84 Float %11.8fLongitude %LonSignedDecimaldegrees,WGS84 Float %11.8fL %Heightabovebottom(m) Float %5.1fH %Waterdepth(m) Float %5.1fHdate %Dateofwaterdepthmeasurement(UTC) StringYYYYMMDDIssued %Dateofissue StringYYYYMMDDProgramName %Processingprogramused StringSync %SynchronisationDateofDataLogger StringYYYYMMDDDrift %LoggerDrift(s/day) Float %10.8fN %Numberoflinesinthetable Integer

ii. Table

Eachrowhastoincludecolumnswiththefollowingformat:

• 1stcolumn:Date–String-YYYYMMDDHHMMSS• 2ndcolumn:MinimumLevel(%6.2f):forM-secondvalues,theminimumlevelisdefinedas

theminimumoutoftheMvaluesof1-secondprocesseddata,withM=Window(integer);• 3rdcolumn:MeanLevel(%6.2f):forM-secondvalues,themeanlevelisdefinedasthe

geometricmeanoftheMvaluesof1-secondprocesseddata;• 4thcolumn:MaximumLevel(%6.2f):forM-secondvalues,themaximumlevelisdefinedas

themaximumoutoftheMvaluesof1-secondprocesseddata;• 5thcolumn:Standarddeviation(%6.2f):forM-secondvalues,thestandarddeviationis

definedasthestandarddeviationoftheNvaluesof1-secondprocesseddata;• 6thcolumn:Ratioofpositiveclippingsamplesintheprocessedwindowtothenumberof

samplesintheprocessedwindow(%10.8f)–Numberbetween0and1.• 7thcolumn:RatioofNegativeclippingsamplesintheprocessedwindowtothenumberof

samplesintheprocessedwindow(%10.8f)–Numberbetween0and1.

EachcolumnisseparatedbyaTAB.

iii. Case of no acoustic data for a station Inthecasethatastation/recorderhasnorecordeddataornovaliddataafterprocessing,foranyreason,alltheprocessedfilesmuststillbeproducedandthefilenamemustagreewithformat


26

describedinSectionc.ii.Incaseofno-data,thefilemustcontainonlythetextnodatainthefirstline,noothertext.

iv. Case of one value is unknown in the header

Inthecaseofaheadervalueisunknownthefieldmustbereplacedbyadash.

e. File template

i. File name StationId031_ThirdOctave00063Hz_Start20140101000000_End20140104211240.asc

ii. File content

FOI %Issuedby031 %StationIdTourEiffel %NameoftheStationSM2M-08 %DataLoggerunitIdSPL %TypeofacousticdatadBref.1µPa: %UnitsoftheacousticdataThirdOctave %ThirdOctave/Broadband63.00 %Centralfrequencyoftheband56.23 %Minimalfrequencyoftheband70.79 %Maximalfrequencyoftheband20 %Processingwindow(sec)48.858093 %LatitudedecimaldegreeWGS84-2.294694-2.294694 %LongitudedecimaldegreeWGS843.63.6 %Heightabovebottom(m)53.4 %Waterdepth(m)20131213121355 %Dateofwaterdepthmeasurement(UTC)20140507 %Dateofissueleif_program(1.0).m %Processingprogramused20131214 %SyncDateofdatalogger0.205284 %Drift(s/day)7 %Numberoflinesinthetable

%TimeUTCMinMeanMaxStdPosClippingNegClipping

20140101000000 100.82 102.50 105.01 1.41 0.00000000 0.0000000020140101000020 102.21 104.33 106.98 1.33 0.00000000 0.0000000020140101000040 99.89 100.01 101.02 0.22 0.00000000 0.0000000020140101000100 98.76 100.01 101.02 0.22 0.00043000 0.0003100020140101000120 102.21 104.33 106.98 1.33 0.00000000 0.0000000020140104211220 99.89 100.01 101.02 0.22 0.00007700 0.0008900020140104211240 100.82 102.50 105.01 1.41 0.00000000 0.00000000

iii. Data storage

Thedatastoragehastobecompliantwithspecificationsmeetingthegeneralrequirementsforstoringdataonadataplatform.


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F. References ANSI.SpecificationforOctave-BandandFractional-Octave-BandAnalogandDigitalFilters.

S1.11[ReaffirmedbyANSI2009].2004.USA,AmericanNationalStandardInstitute.

Au,W.W.L.andP.W.B.Moore.1990.CriticalratioandcriticalbandwidthfortheAtlanticbottlenosedolphin.TheJournaloftheAcousticalSocietyofAmerica88:1635-1638.

Bjørnø,L.Man-madecontributionstoambientnoiseintheseas.Alippi,A.andCannelli,G.B.ProceedingsoftheFourthEuropeanConferenceonUnderwaterAcoustics2,543-548.1998.Rome.

Bloomfield,P.1976.Fourieranalysisoftimeseries:Anintroduction.JohnWileyandSons,NewYork.

Bloomfield,P.2000.Fourieranalysisoftimeseries:Anintroduction.Secondedition.Wileyseriesinprobabilityandstatistics.JohnWileyandSons,NewYork.

CommissionDecision2010/477/EU.2010.CommissionDecisionof1September2010oncriteriaandmethodologicalstandardsongoodenvironmentalstatusofmarinewaters(notifiedunderdocumentC(2010)5956)(TextwithEEArelevance).OfficialJournaloftheEuropeanUnionL232.

Fay,R.R.1988.Hearinginvertebrates:apsychophysicsdatabook.Hill-FayAssociates.

Fernandez,A.,J.F.Edwards,F.Rodriguez,A.E.DeLosMonteros,P.Herraez,P.Castro,J.R.Jaber,V.Martin,andM.Arbelo.2005.Gasandfatembolicsyndrome involvingamassstrandingofbeakedwhales(FamilyZiphiidae)exposedtoanthropogenicsonarsignals.VeterinaryPathologyOnline42:446-457.

Fletcher,H.1940.Auditorypatterns.TheJournaloftheAcousticalSocietyofAmerica12:47-65.

IEC1995(EN61269).Electroacoustics-Octave-bandandfractional-octave-bandfilters.1996.Geneva,Switzerland,InternationalElectrotechnicalCommission.

Kastelein,R.A.,P.J.Wensveen,L.Hoek,W.W.L.Au,J.M.Terhune,andC.A.F.deJong.2009.Criticalratiosinharborporpoises(Phocoenaphocoena)fortonalsignalsbetween0.315and150kHzinrandomGaussianwhitenoise.TheJournaloftheAcousticalSocietyofAmerica126:1588-1597.

Poularikas,A.D.1999.Thehandbookofformulasandtablesforsignalprocessing.CRCPressLCC,BocaRaton.

Robinson,S.P.,P.A.Lepper,andR.A.Hazelwood.Goodpracticeguideforunderwaternoisemeasurement.2014.NationalMeasurementOffice,MarineScotland,TheCrownEstate.NPLGoodPracticeGuideNo.133.

Scharf,B.1970.Criticalbands.Pages159-203inFoundationsofmodernauditorytheory.TobiasJ.V.ed.AkademicPress,NewYork.

Southall,B.L.,R.J.Schusterman,andD.Kastak.2003.Auditorymaskinginthreepinnipeds:Aerialcriticalratiosanddirectcriticalbandwidthmeasurements.TheJournaloftheAcousticalSocietyofAmerica114:1660-1666.

VanderGraaf,A.J.,M.A.Ainslie,M.André,K.Brensing,J.Dalen,R.P.A.Dekeling,S.P.Robinson,M.L.Tasker,F.Thomsen,andS.Werner.EuropeanMarineStrategyFrameworkDirective–GoodEnvironmentalStatus(MSFDGES):ReportoftheTechnicalSubgrouponUnderwaternoiseandotherformsofEnergy.2012.


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Verfuss,U.K.,M.Andersson,T.Folegot,J.Laanearu,R.Matuschek,J.Pajala,P.Sigray,J.Tegowski,andJ.Tougaard.BIASstandardsfornoisemeasurements.Backgroundinformation,guidelinesandqualityassurance.2014.

Verfuss,U.K.,M.Andersson,T.Folegot,J.Laanearu,R.Matuschek,J.Pajala,P.Sigray,J.Tegowski,andJ.Tougaard.BIASstandardsfornoisemeasurements.Backgroundinformation,guidelinesandqualityassurance.Amendedversion.2015.

VanderGraaf,A.J.,Ainslie,M.A.,André,M.,Brensing,K.,Dalen,J.,Dekeling,R.P.A.,Robinson,S.,Tasker,M.L.,Thomsen,F.andWernerS.(2012).EuropeanMarineStrategyFrameworkDirective–GoodEnvironmentalStatus(MSFDGES):ReportoftheTechnicalSubgrouponUnderwaternoiseandotherformsofEnergy.

G. Appendix

I . Short description of Matlab scripts for BIAS

a. Bias_mean.m Thisscriptestimatesthetotalpowerin1/3-octaveband63,125,2,000Hzandinthebroadband10–10,000Hzbyintegrationinthespectraldomainforeach1secwindowandsavestheresultsinastructnameds.InputareDSGorSM2Mfiles.

b. Bias_output.m ThisscriptpreparesthedataforoutputASCIIfilesin20secarithmeticaveragesandestimatethearithmeticmean,median,standarddeviation,maxandminvaluesandthepercentageofclippinginbothnegativeandpositivedirectionineach20secblock.

c. Bias_plot.m ThisscriptmakessomeplotsofBIASvariablessuchasarithmeticmeanvs.time.AlsomakecumulativeplotsincorrespondingwithTSGgrouprecommendations.

d. Bias_gaps.m Thisscriptcanbeusedforpre-processingofDSGorSM2Mdatainwavfiles.Checkingthefilesizesandgapsbetweenconsecutivefiles.Thisscriptalsochecksgapswithinfilesforcheckingofmissingdatasamples.

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