THE FEASIBILITY AND UTILITY OF IMPLEMENTING TEMPORAL DATA CUBES

TO SUPPORT PROJECTION OR “FORECAST” MODELS AND LAND CHANGE TRENDS

AReportoftheNationalGeospatialAdvisoryCommitteeLandsatAdvisoryGroup

April2018

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THEFEASIBILITYANDUTILITYOFIMPLEMENTINGTEMPORALDATACUBESTOSUPPORTPROJECTIONOR“FORECAST”MODELSANDLANDCHANGETRENDSExecutiveSummaryInAugustof2016,theU.S.GeologicalSurvey(USGS)requestedthattheLandsatAdvisoryGroup(LAG),asubcommitteeoftheNationalGeospatialAdvisoryCommittee,studythefeasibilityandutilityofimplementingtemporaldatacubestosupportprojectionor‘forecast’modelsoflandchangetrends.Thisstudywasafollow-ontotwopreviousLAGstudypaperson“ProductImprovement”and“Cloudcomputing”thathadbothbeenpublishedin2013.Thestudywasproposedtohelpaddresswhetheradeepermarketdemandforforecastinglandchangewoulddevelop.SeveralquestionswerealsoposedbasedonthepresumptiveuseofadatacubewithLandsatderivedinformation,asameasure,andtime,asadimension,whichthisreportdiscusses.BackgroundThejointNationalAeronauticsandSpaceAdministration(NASA)/UnitedStatesGeologicalSurvey(USGS)Landsatprogramprovidesthelongestcontinuousandopenlyavailablespace-basedrecordofEarth'slandinexistence.Landsatmissionshaveacquiredmoderateresolutionmultispectraldataforover40years.TheEuropeanSpaceAgency(ESA)hasbeengatheringEarthobservationdataforalongtimeandinitiatedsystematicarchivingandanalysisofdatafromotheragencies’satellitesintheearly1980s.ItbeganitsownEarthobservationswithEurope’sfirstEarthResourcesSatellite(ERS).TheESAEarthObservingSentinelsatellitesovernearlythepastfouryearshaveaddedtotheamount,thecomplexity,andtherelevanceofreadilyaccessibleremotelysenseddata.Havingafacile,agile,andreliablewayforalltointeract,directlyorindirectly,withthese,alreadyvastbutalsogrowing,collectionshasbothnationalandinternationalinterest.Thesecollectionsposethe“BigData”technologychallengetopreviousdataarchitecturesandtoolstomanipulateortointerrogatepricelessobservationsfromawide-rangeofsensors.Higherspatial,spectral,andtemporalresolutionofthecollectioncompoundsthechallengeaswellastheopportunitiestobetterunderstandourEarth.Improvedapproachestothemanagement,preparation,distributionandanalysiswillrelievesomeofthedata-to-information-to-knowledgeprogressionstress.Algorithmsforstatisticalanalysisofincreasinglylargersamples(andperhapssignificantlyvarying)“BigData,”usedunderdifferentconditionstoaddressdifferentissuesandperspectives,mustbewiselyselectedandusedtoavoiderroneousstatisticalinferenceorinadequateconclusion.TheFederalGeographicDataCommittee(FGDC)requested,forthe2016program,thattheLandsatAdvisoryGroupprovideadviceon“thefeasibilityandutilityofimplementingtemporaldatacubestosupportprojectionor‘forecast’modelsoflandchangetrends”andnotedthatthisworkwas“intendedasafollowontopictotheLAGstudypapersonProductImprovementandCloudcomputingpublishedin2013.”Fivequestionswereposed:

• InadditiontoLandsat,whatotherdatasources(toincludeEO,SAR,andLIDAR)areoptimallysuitedforleveraging(e.g.,co-registered)tosupportdatacubeimplementationsforlandchangeanalysisandforecastmodeling?

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• WhatkindsofLandsattime-seriesproductswouldhavethebroadestcommunityuseormostimpactfulcontributioninspecificareas?

• WhichorganizationswithexpertiseinforecastmodelingarebestposturedtoevaluateanddemonstratetheforecastpotentialfromaLandsat-basedtemporaldatacube?

• HowfarbackintimeintotheLandsatarchiveshouldthestagingof‘analysisreadydata’beconsidered?E.g.,earlydatacollectionssuchasmulti-spectralscanner(MSS)dataarelessequipped(intermsofmetadata)tosupportrigorousgeometricandradiometriccalibrationcomparedtolatercollections.

• Howcouldefficientsynergyberealizedamonggovernmentandcommercialrolesfordatacubedevelopment,andoperations(processing,storage,distribution)tosatisfybroadcommunityneeds?

TheNGACPaper,dated11December2013,on“ProductImprovement:AdviseUSGSonpotentialmeansofmodifyingthecurrentproductstomakethemmoreusefultocommercialinformationprovidersandvalue-addedanalysts”1madethegeneralrecommendationthat“USGSfurtherimproveLandsatproductstobothenhancethescientificvalueoftheimagery,butalsotoprovideadditionalvaluetothecommercialandgovernmentorganizationswishingtoextractthemaximumvaluefromtheimagery.”SevenpointsexpandedthatsummaryrecommendationforUSGS:

• ClearlydefinewhatUSGSwillproduceandavoidcompetitionwithcommercialwork.• Refinegeometricaccuracyandradiometricmeasurementstoenablebetterchange

detection.• ImproveL1Gproductgeometricaccuracyandco-registration.• Defineastandardsurfacereflectanceproduct.• Consolidatescientificresearchandpublishbestpracticesforarangeofproducts.• Providecertification/validationfacilitiesforproductsnotproducedbyUSGS.• SimplifyaccesstotheL1Tproduct.

ThesecondNGACPaperofthesamedate,entitled“CloudComputing:PotentialNewApproachestoDataManagementandDistribution”1endorsedtheuseofcloudcomputingandsuggestedhowUSGS/ EarthResourcesObservationandScience(EROS)shouldleveragethattechnologyby:

• Supportingthird-partycloudprovidersbyprovidingbulkdatadownload;• Co-locatingdataandon-demandprocessingforonlythedesiredinformation;• Transmittingtherequiredprocessingmodeltothecloudsomassivedatacouldbehandled

bymultipleCPUs;• DownloadingsubsetsofL1Tproducts;• Givingattentiontouseofopensoftwarestandardstoavoidtyinganyservicestoproprietary

software;and• Streamliningsecurity.

IntroductionExplaininginterestinthespatio-temporaldatacubeTheoptionsforstoringandaccessingrelevantdataofferarangeoffunctionalitybutaresomewhatlimitedwithmassivedataandspecificrequirementstosatisfyparticularbusinesscases.Inmanycases,adatawarehousecanadequatelysupportinformationprocessingasastableplatformforconsolidated

1 Twoofthe2013NGACKeyDocumentsfoundathttps://www.fgdc.gov/ngac/key-documents

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andtransactionaldata.However,ofincreasinginterest,onlineanalyticalprocessing(OLAP)moreadequatelyallowsformulti-facetedconsumptionofdatatomeetvariedneeds.Thedatacubeprovidesnotonlyastoragestructurebutalsothe“staging”spaceforanalysisoftheinformation.TheOLAPcubeisamulti-dimensionaldatabase,whichhasdrawnincreasingattentionoverthepastseveralyearsforearthobservationcollection.AmarketingpromotionforanEarthserverProjectworkshopondatacubesdescribedthedaylongworkshopfocusinthefollowingway.“Thedatacubeconceptpromisestotacklesomeofthechallengesthatcomealongwithlargevolumesofenvironmentalandgeospatialdata.Datacubesofferamoreon-demandandanalysis-readyaccesston-dimensionaldata,whichcanbeaccessedalonganyaxis,allowingforefficienttrimorsliceoperations.Thedatacubeconceptmakeslargevolumesofenvironmentalandgeospatialdatamoremanageableandthus,increasesthegeneraluptakeofBigEarthdata.”2ExamininganotionalarchitectureTheCommitteeonEarthObservationSatellites(CEOS)ofwhichtheUSisamembercountrybegananOpenDatacubeinitiativein2016.BrianKillough(NASA)andRobertWoodcock(CSIROofAustralia)havebeenprincipaladvocatesfortheinitiative.Whentheinitiativelaunched,useofthedatacube,withthedimensionsofspace,time,anddatatype,wasalreadyaprovenconceptbyGeoscienceAustraliaandtheAustralianSpaceAgencyandwithindevelopmentfortheirLandsatdataarchive.Theobjectivewastohave20countriesoperationallyinvolvedby2022.3Thepace,however,isexceedingtheJuly2017plan.InJuly2017,threecountries(Australia,Colombia,andSwitzerland)hadoperationalcapability.Fourotherwereunderdevelopmentandtwenty-onecountrieswereunderreview.DuringateleconferenceddiscussionwithDr.KilloughandtheTaskTeam2inmid-October2017,hecommentedthat29countrieswerealreadyunderreview.InMarch2018,duringabriefingattheCEOS7thWorkingGroupforCapacityBuildingandDataDemocracyAnnualMeetinginBrazil,itwasmentionedthatatleast40countrieshaveenteredintosomelevelofdiscussionalthoughtheobjectivedoesremain20.ThespeakernotedthatAustralia,Colombia,andSwitzerlandarestilldoingwell.TheUnitedKingdom,Uganda,Vietnam,Taiwan,Georgia,andMoldovaaremakingprogress.ThereareAfricanregionaldatacubesinGhana,Kenya,Senegal,SierraLeone,andTanzania.Therefore,thenotionofthedatacubeisgaininginterestandsupport.Theglobalnatureoftheinterest,however,addstothecomplexityofhowtheUSplanstoexpanditseffortswiththeLandsatcollections.Finding1:InternationallytheutilityofthedatacubefororganizingLandsatdataovertimeandlocationhasgrowingacknowledgementtosupporttimeseriesanalysis.3Colombiahasfoundvalueinexamininglandchangesince2000andenablingunderstandingthetrendsforforestmappingandmanagement.ThemainobjectivesoftheSwissDataCube(SDC)aretosupporttheSwissgovernmentforenvironmentalmonitoring.4TheVietnamDataCubeisintendedtocreatebroadapplicationsforsocio-economicsustainabledevelopmentgoalsforVietnamaswellasothercountriesintheregion.5AnalysisReadyData(ARD)6feedtheformationofadatacube.Landsat8OperationalLandImager(OLI)/ThermalInfraredSensor(TIRS)Tier1and2,Landsat7EnhancedThematicMapperPlus(ETM+)Tier1,

2 https://themes.jrc.ec.europa.eu/news/view/158675/earthserver-workshop-data-cubes-for-big-earth-data-19th-20th-october-2017-frascati-rm-italy 3Killough,BrianOpenDataCubeBackgroundandVision,https://www.opendatacube.org/eventsJuly7th,2017 4http://www.swissdatacube.org/5https://vnsc.org.vn/en/news-events/news/internal-news/introduction-of-satellite-data-sharing-system-vietnam-data-cube/6 https://landsat.usgs.gov/ard

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andLandsat4-5ThematicMapper(TM)Tier1comprisethecontiguousUS,Alaska,andHawai’iARD,whichisavailablefromtheEROSCenter,usingEarthExplorertodownload.Startingmid-March2018,twonewLandsatscienceproducts,SurfaceTemperatureandDynamicSurfaceWaterExtentwillbegintobeintegrated.Dr.RobertWoodcock,whohasworkedforalmosttwodecadesinthefieldofvisualization,spatialinformationsystemsandanalyticsanditsapplicationtoEarthSciencewithafocusonensuringresearch

Figure1.ThearchitecturalconceptsoftheAustralianGeoscienceDataCube

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innovationleadstobusinessinnovation,hasbeenreinforcingtheabove-mentionedworkwiththeOpenDatacubeinitiativeusinghisextensiveexperience.He,withsomecolleagues,preparedthediagramseeninFigure1,7whichdescribesanotionalarchitectureemployingthedatacube.Thefourlayersfrombottomtotopasfollows:

DataAcquisitionandInflow-Observationsarecollectedandpre-processedtoan‘analysisready’levelbyvariouscustodians;DatacubeInfrastructure-analysisreadydataareindexedintotheAGDCv2includingingestionintomulti-dimensionaldatasets,withasuiteoftoolsfortaskexecution,discovery,visualizationandsoon;DataandApplicationPlatform-Platformsandenvironmentsthatallowroutinegenerationofproducts,and,explorationofnewproductsina‘virtuallaboratory’environment;andUIandApplicationLayer-Adiversesetofapplicationsisenabledbytheunderlyinginfrastructure.

Finding2:TherecommendationsfromtheaforementionedLAGpaperscanbealignedwiththisnotionalarchitecture“tobothenhancethescientificvalueoftheimagery,butalsotoprovideadditionalvaluetothecommercialandgovernmentorganizationswishingtoextractthemaximumvaluefromtheimagery”andtooffer“potentialnewapproachestodatamanagementanddistribution.”EROSCenteranddatacubes:InNovember2016,USGS/EROSprovidedtheLAGteamwithabriefingontheLandChangeMonitoring,Assessment,andProjection(LCMAP)initiative“toharnesstheLandsatrecordinordertoprovidestate-of-the-artlandchangecapabilitiesneededbyscientists,resourcemanagers,anddecisionmakers.”Asexplainedduringthepresentation,tomanagetheresultantland-changeproductsrequiredaddressingtheissue“thattheLandsatarchive,currentlyorganizedaspathrows,isnotsufficientlyefficientfortimeseriesstudies.Movingtoagrid-baseddatacubeapproachwithAPI’sthatconditionandservedataperuserspecificationwillreducedatapreparationtime.”ThedatastructuretobeusedwasidentifiedasanOLAPcube.ThedatacontentitselfistheAnalysisReadyData(ARD)inthediagramabove.ThetilingschemeismodeledupontheWebEnabledLandsatData(WELD)andwillusetheAlbersEqualAreaConicprojectionandtheWordGeodeticSystem84datum.ARDarestandardizedwell-characterizedradiometricandgeometricproducts.Dr.TomLovelandcharacterizedtheARDasLandsatdataprocessedtoalevelthatenablesdirectuseinapplications.

§ Itwillsupportgeospatial,multi-spectral,andmulti-temporalmanipulationsforthepurposesofdatareduction,analysis,andinterpretation.

§ Itoffersconsistentradiometricprocessingscaledbothtotop-of-atmosphere(TOA)reflectanceandsurfacereflectance.

§ Itisdesignedforconsistentgeometryincludingspatialcoverageandcartographicprojection–e.g.,pixelsalignthroughtime,<12mRMSE.

§ Itprovidesmetadataondataprovenance,geographicextent,anddataquality.

7AdamLewis,SimonOliver,LeoLymburner,BenEvans,LesleyWyborn,NormanMueller,GregoryRaevksi,JeremyHooke,RobWoodcock,JoshuaSixsmith,WenjunWu,PeterTan,FuqinLi,BrianKillough,StuartMinchin,DaleRoberts,DamienAyers,BiswajitBala,Lan-WeiWangTheAustralianGeoscienceDataCube—Foundationsandlessonslearnedhttps://www.sciencedirect.com/science/article/pii/S0034425717301086

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Insimplewords,ARDareintendedtoprovidesomepre-processedproductsthatalleviatesomeworkburdenonthepartoftheusers.ThereinliesbothitsbenefitformostconsumersandconcernforsomeotherLandsatusersthatwillbeaddressedlater. QuestionsPosedbyUSGSInadditiontoLandsat,whatotherdatasources(toincludeEO,SAR,andLIDAR)areoptimallysuitedforleveraging(e.g.,co-registered)tosupportdatacubeimplementationsforlandchangeanalysisandforecastmodeling?AmongtheeffortsconsideredbytheLCMAPteamalreadyhasbeentoincreasetimeseriesdensitybyaddingSentinel-2.8IntheCEOSinitiative,ColombiaandSwitzerlandarestudyinghowtoincorporatebothSentinel-1(SAR)andSentinel-2(multi-spectral).TheVietnamprototypeincludesbothSentinel-2andALOSdata.Progresswasdiscussedon6March2018,whentheVietnamNationalSpaceCenterorganizedaworkshop“IntroductionofsatellitedatasharingsystemVietnamDataCube”inHanoi.Oneshouldnotassumethatallotherdatasourcescould,would,orshouldbehousedbyUSGS/EROS.Thedatacubedesignmustallowadditionaldimensionsorlayerstothecube.Itwilloftenbenecessaryforanothergovernment,academicorcommercialorganizationtoincorporatetheirown,sometimesproprietary,datasettoimprovetheresultsortopreparetailoredanalysis.Thus,inFigure1,onecouldconsideranalysisreadydatatobemultipledatasetsthathavebeenreadiedbysomepre-processingtoenterintothedatacubestructuring.HereasseeninFigure29,layersofdifferentdatasourceproductsandextensionsofmorelocationsortimescanbeadaptivelyincorporatedtoaddresseithersomespecificorgenericissue.Thegraphicmayobscuretherealitythatprospective“layering”demandsconsiderationofsomestandardizingstructureandfunctionalguidelines.

Figure2.GraphicofConceptualDataCube

ThenotionthatavarietyofpossiblesourcesofdatawouldaccompanytheARDwithintheframeworkoftheUSGSLCMAPinitiativewascharacterizedinthegraphicofFigure3providedbyDr.Loveland.

8Dwyer,John,“USGSAnalysisReadyData”presentationtotheLandsatScienceTeamonJanuary14,2016andrecentreleaseindicatinginterest:https://landsat.usgs.gov/february-17-2018-us-landsat-ard-special-issue-call-manuscripts9Adaptedfromhttps://www.slideshare.net/algum/data-cubes-7923771/5

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Figure3.LCMAPConceptualFrameworkandFlow10

WhatkindsofLandsattime-seriesproductswouldhavethebroadestcommunityuseormostimpactfulcontributioninspecificareas?TheAnalysis-readydata(ARD)preparation,ingeneral,restsuponfoundationaltechnologythatcanbenefitnearlyallusersofLandsatdata,notjustafewspecificapplications.Forexample,ensuringthatalldataareconsistentlycalibratedandcarryappropriatequality-assurancemetadataisofbenefittoeveryone,regardlessofwhethertheyareusingdatainoneoftheexistingUTMgridsoranewcountry-specificgrid.TheU.S.LandsatARDtilingsystemisamodifiedversionoftheWELDstructure.ThreetilegridextentsaredefinedforCONUS,Alaska,andHawaii.ThegridoriginsaredefinedinrelationtotheWGSdatumbutadjustedtoalignwiththeNationalLandCoverDatabase.Theyarecountryspecific.Inaddition,thedevelopmentofaUS-specificARD-baseddatacubeinanAlbersEqualAreaConicmapping projectioniswell-alignedwiththemissionoftheUSGSservingitsUScustomers,asispreprocessingothergeographically-coincidentdatasetstobeavailableinthatsameprojection.ThatapproachbothenablesandfacilitatesthedevelopmentofarangeofUS-specifichigher-leveldataproductsandservices.However,asdatacubesbecomeubiquitous,whatworkswellfortheUSmaybequiteawkward

10Loveland,ThomasAnLCMAPOverview:LandChangeMonitoring,Assessment,andProjection,aDiscussionwiththeLandsatAdvisoryGroupandAmericaViewMembers,November16,2016

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forothercountries.WhentheOpenGeospatialConsortium(OGC®)firstbeganitsDiscreteGlobalGridSystem(DGGS)11workinggroup,itsoughttoestablishaspecificationtoaddresscollatingspatialdatafrommultipleplacesandsourcesandovercomingthechallengesofworkingwithdifferentreferenceorgridsystems.ARDpresenttheBigDatachallenge.AsexplainedbyUSGS/EROS,ARDarethefoundationofLCMAPprovidingstandardizedwell-characterizedradiometricandgeometricproducts(Level-1Collection1),theatmosphericcorrectionandgeo-physicalsurfacereflectanceandsurfacebrightnessretrievals(Level-2),andhierarchicalmetadatatoincludepixel-levelattributes.Alsoavailablewouldbe“opensource”codetoestablishtheprocessingandmetadatastandards,toaccommodatescalablearchitectures,todeployintopublicorprivateclouds.ThelatterareallpointsconsistentwiththerecommendationsfromtheCloudComputingpaper.Taskteammembersendorsedthisopennessbutrecommendalsothedistributionofverificationproceduresthatthemethodsandworkflowshavebeenreplicatedproperlyforanynon-USGSproductionthatincorporatedothersourcesandinitiatestailoredanalysis.ThoseproceduresmightmirrorwhatUSGSitselfuse.Atthistime,theARD’s“opensource”codeisaccessiblethroughhttps://github.com/USGS-EROS.Thedownloadofatilestillinvolves5000x5000pixelspercollectioneventandanypartitioningdowntosomesmallergeographicfootprintforamorelocalareaoccursinthechosenenvironmentoftheuser.Improvementstothelengthyandspacedemandingdownloadandprocessingtasksareneeded.Finding3:Non-USGSprocessingofdatausingtheopen-sourcecodeandalgorithmsavailablefromUSGScouldnecessitatethatUSGSalsoreleaseproceduresdocumentationandsomeverificationtestdatasets.ThetaskteamresponsibleforthisreportcautionsthattheUSGSshouldensurethatitsvariouseffortsrelatingtoLandsatdataprocessingdistributionarewellalignedwitheachotherandclearlyarticulatedtotheusercommunity.Inparticular,therelationshipbetweentheCollection1reprocessingeffort,existingSurfaceReflectanceprocessinganddistributionefforts,andtheAnalysis-ReadyDataeffort,mayneedtobeclarified.Fundamentalimprovementstoprocesses,likesensorcalibration,shouldbeappliedequallytoprocessinganddeliveryofbothUTManddatacubedata.Similarly,bothTOAandSurfaceReflectancedataareofvalueinallproductformsandshouldbemadeavailableinaconsistentmanner.Keepingalltheseeffortsalignedmayminimizeduplicationofeffort,butmoreimportantly,itwillavoiduserconfusion,whichcouldotherwiseleadtoerroneoususeofdatabyendusers.12RecentlybroughttotheattentionoftheTaskTeamhasbeenthevoiceofthosewhoworryabouttheimpactof“normalizing”thereflectanceproductacrossallthecollections.Fromtheirperspective,theyagreethatpre-processingtheLandsatdataintothis“normalized”statesothattime-seriesanalysisofmultiplecollectionsoveralargeareabringsgreatefficienciesbyreducingprocessingburdenonamanyorevenmostoftheusers.Whattheconcernedgroupquestionsiswhaterrorisintroducedinthatpre-processingthatmightaffectanalysisofsmallerfootprintsandmorerestrictedtimesequences.Importantly,theyarenotclaimingthatsignificanterrorsmightresult.RathertheyareconcernedthatwhateveranalysismayhavebeencompletedbeforemovingaheadwithARDhasnotbeenquantifiedforthem.TheyendorsethattheLevel1Tproductswillremainavailableandwillwanttodomorestudyon

11http://www.opengeospatial.org/projects/groups/dggsswg12StevenJ.Covington,PrincipalSystemsEngineerfortheUSGSLandRemoteSensingProgram,commentedCurrentthinkinghasCollection2encodedwithCloudOptimizedGeoTIFF(COG)toenableefficientextractionofuser-definedareassmallerthantheplannedstoragegranule(aWRSScene)

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thealgorithmsthathavebeenusedtocreateARDsotheycanreliablyassesstheerror,ifanyornegligible,introducedintothedata.ArecommendationwouldbethatUSGSEROSCenterreleaseanystudyanalysiscompletedontheerrorimpactofthepreprocessingorinitiatesuchastudy.(Itisrecognizedthatifthereisconcernthatcannotberesolved,onecanreversetheprocessthatproducedtheTOAproductandhavethehistoricalradianceproduct.)WhichorganizationswithexpertiseinforecastmodelingarebestposturedtoevaluateanddemonstratetheforecastpotentialfromaLandsat-basedtemporaldatacube?MuchhasbeenwrittenaboutproblemsofforecastingwithanyBigData,includingalltheimageryandgeospatialcollections-withtheforemostchallengebeingthelackofpersonnelskilledforthistask.ThetilingschemechosenforARDandappliedtotheLandsatimagesovertheUSshouldassurealignmentoftilessothat“drilling”thoughseveralimagesoverthesamegeographyprovidesthesamefootprintforsubsequenttimeseriesanalysisthatcouldleadtoforecastingfutureconditionsbaseduponpastinformation.Itistrustedthatrigoroustestinghasbeendonetoassurethelayeredfootprintsovertimearepositionedwithinsomedefineddegreeofpositionalaccuracy.OneobjectivesoftheARDeffortcouldbetoimproveuseof“biggeodata.”Withinsomeoftheresearchandanalysisworkwithlargequantitiesofgeospatialdatahasbeendiscussionofthefrustratinginsufficiencyoftraditionalstatisticaltechniquesorofthechallengingselectionofthemostappropriatestatisticaltechniquetoobtainreliableandconsistentforecastsfromlargequantitiesofdata.IntheinitialreleasesoftheLandsatARDandthetemporaldatacube,itwouldbewisetoconsidertheuseofacademicresearchcenterstoassesshowmuchthenewstructureactuallyfacilitatesanalysisandtoencourageuniversitiestoreviseclassroommodulesthatpreparethefutureanalystsandinformationmanagers.WillARDenablebetterforecastswithBigDatausingavarietyofnoveltechniques?NotonlycanacademicorganizationsbeexcellentpartnerswiththegovernmentusingthesevaststoresofdatabutalsoseveralprivatecompanieswillbeeagertousetheARDandbuildversionsofthedatacubetailoredtosupportprocessingthatdeliverstheanswersneededbytheircustomers.HowfarbackintimeintotheLandsatarchiveshouldthestagingof‘analysisreadydata’beconsidered?E.g.,earlydatacollectionssuchasmulti-spectralscanner(MSS)dataarelessequipped(intermsofmetadata)tosupportrigorousgeometricandradiometriccalibrationcomparedtolatercollections.ThedecisiontoincludetheMSSdatahasbeenstronglyrecommendedwithinUSGSattheEROSCenter.Addressingthequestionmaybeamootpoint,givenitsvalueinthelongtermofcontinuousEarthimagingandobservationanditsinclusionbeingstronglyrecommendedbysomemembersofthepreviousLandsatScienceTeam.However,thistaskteamstronglyrecommendsthatprioritizingdevelopmentworkshouldbecarefullyscrutinizedwithinUSGS.IsglobalARDwithoutMSSofgreatervalue,toagrowinginternationalcommunityofusers,thanUSARDwithMSS?Inaddition,followingsomeoftheconcernaboutforecastsfrommassivedatastores,theissueofsignaltonoise(noteasilymitigatedbytheseriouslydiminishedamountofmetadataforMSSdata)shouldalsobeevaluated.Howcouldefficientsynergyberealizedamonggovernmentandcommercialrolesfordatacubedevelopment,andoperations(processing,storage,distribution)tosatisfybroadcommunityneeds?CautionwasurgedbyteammembersabouthowmuchoftheproductionworkloadshouldbeassumedbyUSGS.TheanalysisoftheARD,asingestedintothedatacubeinfrastructure,shouldnotbesolely

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dependentonthecomputinginfrastructureoftheUSGS,whichisunlikelytohavereadyaccesstosomeofthelatesttechnologyadvancements,giventhebudgetingprocesses.ManyoftheorganizationsveryinterestedinthepromiseofLCMAPmightneedattentionmorefocusedonspecificareasthattheEROSCenterhadnotplannedtoaddressimmediately.ThosespecificareasmighthavelargerorsmallerfootprintsortheymightbeoutsidetheUS.Itisnotclearthatthegovernmentispreparedforsuchflexibleresponseforbuildingsuchspecificdatacubes,norhasanygoodjustificationbeenprovidedforwhythegovernmentshouldassumethatroleofproduction.MembersoftheTaskTeamhighlyrecommendedmoreconsiderationoftheprivatepublicpartnershipconceptintheend-to-endprocessfromLandsatlevel1productstoARDtouser-tailoreddatacube.TheTaskTeamagreedthatUSGS,astheLandsatsourceexperts,shouldberesponsibleforLandsatARDqualityandconsistency,althoughtheywouldlikelybenefitfromcommercialsupportfortheprocessinganddistributioninfrastructure.Finding4:Thecommercialsectorisreadytoprovidedatacubetailoringassistance,givenitsincreasingexperiencewithglobalgeospatialdata.ItisalsopreparedtoprovisioninfrastructuretoassistintheproductionofARD.Astheneededtoolsandtechniquesmature,theteamsimilarlyrecommendsthatUSGSshouldnotundertaketoscalethiscountry-specificeffortgloballythemselves.Thereisnoonepeerlessglobalprojectioncoordinatesystem.Givenspecificneeds,anyspatialmulti-dimensioneddatacubecanbequiteparochial,andeachcountryorregionthatwantsadatacubewouldlikelyselecttheirowntilinggridtominimizedistortionintheirregionandmaximizeinteroperabilitywithotherexistingregionaldatasets.TheUSGSshouldfocusonopeningupitstoolsandthenecessaryinputdatasetssothatthirdpartiesintheprivatesectorcanofferaserviceofbuildingthesedatacubesforglobalcustomersinaccordancewithUSGSbestpractices.Suchascenario,mightalsoinvolveothercountriesproducingtheirownARD,andiffromLandsat,thatcouldrequiretheUSGStoreleaseimagedata(perhapsLevel0),DEM,GCPdata,andallothernecessaryinputsinadditiontothecodethatUSGSusestocreatetheUSARDproduct.Inthisway,theUSGScouldfocusondevelopingexpertiseandonbuildingoperationalsystemsfortheUS,withoutstrayingintobuildingoperationalsystemsfortheworld.TheconcernaboutUSGSproducingeitherARDordatacubesfortheglobalcustomerrelatesbacktotheearlierdescriptionofbothamappingprojectionandagridsystemthatdonotapplywellglobally.ThatraisedthequestionabouttheprioritiesoftheUSGSproductionplansandhowandwhytheprivatesectorcanstepforward.TheCEOSinitiativeisnotwithoutquestionsforsimilarchallenges.EvenifglobalstakeholdersagreethatanOpenDatacubevisionhaspromise,willtheymaketheircontributionstomitigatetheriskthattheconceptcannotbescaledwithlimitedresources?GiventheadoptionoftheconceptandthedevelopmentofnationaldatacubesundertheCEOSinitiative,havingexcellenttransformationalgorithmsfortheprojectionswouldallownecessaryflexibility.Thetilingscheme,however,couldbefarmorechallenging,ifandwhenadjacentcountriesbuildnationaldatacubesandselectdifferingschemes.TheroleofCEOSinestablishingorinstantiatingstandardsandspecifications,likethoseintheDGGSmentionedabove,shouldnotbeunderestimated.Previouslythispapermentionedstandardswithrespecttotheopensoftwarestandardsneededtoavailanyrequesterofthesoftware,whomightrequirethealgorithmsusedbyUSGSinpreparingtheARDatanypointintheanticipatedimprovementsovertime.Finding5:Thedatacubeimplementationinvolvesabroadscopeofstandardsissues.• InFebruary2018,afteraninformaldiscussionofthetopic,anOGCgrouppreparedanOGC

discussionpaper:“Inresponsetoarecentdiscussion(viatheOGCemaillists)regardingperceptions

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aboutdatacubesandDGGS,itwassuggestedthatwebeginamoreformaldiscussiononthistopicwithintheOGCTechnicalCommittee.ThisinformationdocumentaimstoinitiateadiscussionofthebroaderdefinitionofadatacubeandthecomplementaryrolethatDGGStechnologiesplay.”13Thefollowingfutureactionswereidentified.“…theAuthorsrecommendsometargetedactionswithwhichweshouldproceedincollaborationwiththecommunityoftheDGGSspecificationanddomaingroups.Theseactionsmainlyfocusoninvestigatingtheefficiencyonqueryingandexploringlargemulti-dimensionalarrayswhileusingtheDGGStechnologiesonDatacubes.Theseactivitieswillbeexercisedunderspecificongoingbigdataresearchinternationalprojects.”

• AlsoinFebruary,theOpenGeospatialConsortiumannouncedthatitwasseekingpubliccommentonWebCoverageService(WCS)2.1CandidateStandard.Thequalifierstatementfortheannouncementread“UpdatedWCS2.1Standardwillsimplifyaccesstospatio-temporal‘bigdatacubes’”.14Thereleasealsooffersmoreexplanation.“BysupportingthemoregeneraldatacubemodelofCIS1.1,theWCS2.1standardwillsimplifyaccesstospatio-temporal‘bigdatacubes’,withanoperationspectrumrangingfromsimplesub-settinginspaceandtimeuptocomplexspatio-temporalanalyticsthroughWebCoverageProcessingService(WCPS).WCPSoffersaprotocol-independentlanguagefortheextraction,processing,andanalysisofmulti-dimensionalcoveragesrepresentingsensor,image,orstatisticsdata,suchasmightbeenvelopedwithinadatacube.

• In2017,Dr.PeterBaumann,ProfessorofComputerScience,JacobsUniversityBremen,publishedapositivelyprovocativepaperwithinthecommunityofinterest,namedtheDataCubeManifesto15,inwhichhecommented,“Recently,thetermdatacubeisreceivingincreasingattentionasithasthepotentialofgreatlysimplifying“BigEarthData”servicesforusersbyprovidingmassivespatio-temporaldatainananalysis-readyway.However,thereisconsiderableconfusionaboutthedataandservicemodelofsuchdatacubes.”Thatstatementwasfollowedbyhissixprinciplesofdatacubeserviceconcludingwiththesixthbeing“Datacubesshallsupportalanguageallowingclientstosubmitsimpleaswellascompositeextraction,processing,filtering,andfusiontasksinanad-hocfashion…TheOGCdatacubestandards,CISandWCS/WCPS,areembracedbyopen-sourceandproprietaryimplementers,comingwithcompliancetestsenablinginteroperabilitydowntothelevelofsinglepixels.Availabilityofdatacubestandardsandtoolsisheraldinganeweraofservicequalityand,ultimately,betterdatainsights.”

TheTaskTeamrecommendsthatOGCbeencouragedtocontinueworkonthestandardsthatsupporttheagileandreliableandconsistentuseofadatacubeapproach.Thiswouldhelpaddressthissection’squestionabouttheefficientsynergybetweenpublicandprivatesectorusetomeetcustomer/clientrequirements.

AnotherquiterelevantpointthathasemergedduringthemonthsofdiscussiononthisLAGtaskassignmenthasbeenthequestionoflocalorcloudstorageand/orprocessing.Assumptionsaboutthedesirefornationstowantalltheirdatadownloadedtotheirownserversratherthanpreferringthevalue-addedsolutionsprovidedbythecloudserviceprovidersarenotnecessarilyreinforcedbythe

13Purss,M.,Peterson,P.,Strobl,P.,andSabeur,Z.DiscussionPaper:ADGGSPerspectiveonDatacubes18-006,14February2018(Permissiontouse:TheOGCWorkingGroupthatdevelopedthepaperapprovedreleaseforusebytheNGACmembership.26March2018.)14http://www.opengeospatial.org/pressroom/pressreleases/273815Baumann,Peter,TheDatacubeManifestohttp://earthserver.eu/tech/datacube-manifestoResearchsupportedbyECcontract654367

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emergingevidence.16Insomecountries,thetoolstoworkwiththemassivedataareeithernotavailableortheskilllevelsarecurrentlyinadequate.Theprivatesectorworkingcloselywiththenationalgovernment’simagerycoulddramaticallysimplifydatausewhensolutionsratherthandataisthedesiredoutcome.Cloudcomputing,inadditionorinlieuofcloudstorage,maybethetailoredapproach.Evenwhendataarewhatmaybeneeded,theresponsecouldbeatailoreddatacubeprovisionwherethenationaldata,likeARD,arelayeredwithotherdatasourcesandrefinedtoaparticularfootprint,consistentwiththeprecedingdiscussioninthisstudy.OnequestionraisedwashowtheprivatesectormightcollaboratetohelpwithtilingtheadditionalsourcestomatchthatofARDasthelayersofthedatacubeareincorporated.DuringtheCEOSbriefinginBrazilinMarch201817,thetopicofcooperationwiththeprivatesectorundersomegrantagreementswasincludedasaneededfacilitatoroftheglobaleffort.PartnershipswithGoogle,Amazon,andotherswereseenasenablingthe“scalablesolution.”MajorRecommendations

Thisreportmakessomespecificrecommendations,specificallywithrespecttotheU.S.LandsatAnalysisReadyData(ARD)anditspotentialforbeingincorporatedinavarietyofdatacubes,asadirect-usedatasetinmonitoringandassessinglandscapechange.1. TaskteammembersendorsetheopennessoftheEROSCentercommitmenttoprovidethesource

dataandtopublish,as“opensource,”thesoftwareandalgorithmsusedtoproduceARD.TheTeamrecommendstheUSGSshouldpublishverificationproceduresthatthemethodsandworkflowshavebeenreplicatedproperlyforanynon-USGSprocessing.TheseprocedureswouldlikelyreflecttheveryprocessesthatUSGShasusedinpreparingARD.TheverificationtaskitselfwouldnotbetheresponsibilityoftheEROSCenterbutratherofanyotherentityusingthesoftwareandalgorithms.

2. Studiesmayalreadyexistthatcharacterizehow“normalizing”reflectanceacrosssensorsandyears

mightaffectvalues.TheTaskTeamrecommendsthatUSGSEROSCenterreleaseanyerror/differencestudyandanalysisbetweenthereflectancevaluesoftraditionalscenepixelsandtheARDunitpixels,whichmayhavealreadybeencompleted,todetermineanyradiometricchangesresultingfrompreprocessingtocreatetheARD.Offeringaccesstothosestudiescouldbebeneficialtosomeresearchers.Ifsuchananalysishasnotbeencompleted,theTaskTeamrecommendsthatonebeinitiated.

3. TheTaskTeamexpectsprocessingtechniques,algorithms,andassociatedtoolstoimproveover

time.Reprocessingtheentiredataset,vicelimitingnewapproachestoonlydataacquiredafterthedevelopmentofimprovements,wouldmeetthe“analysis-ready”objectiveofreducingthedataprocessingloadofdatauses.TheTeambelievesthatcompleterevisionoftheentireARDcouldfollowaMODISapproach.TheteamwasadvisedbyUSGSthatsuchprocessingofsomuchdatacouldtakeuptotenmonthssoareasonablescheduleforupdateswillneedtobeestablished.TheTaskTeamrecommendsthatwhenimprovedprocessingapproachesareready,thereprocessing

16TheCEOSDataCube,Three-YearWorkPlan2016-2018http://ceos.org/document_management/Ad_Hoc_Teams/SDCG_for_GFOI/Meetings/SDCG-10/Cube%203-Year%20Work%20Plan%20-%20v1.0.pdf.17Holloway,Kim“OpenDataCubeInitiative”Agendaitem#8,CEOS7thWorkingGroupforCapacityBuildingandDataDemocracyAnnualMeeting,INPEJosedosCampos,Brazil,6-8thMarch2018

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shouldapplytotheentiredatasetinuseandthatusersshouldnotberequiredthemselvestoapplycompatibilityadjustmentstoanyARDreceivedpriortothechange.

4. TheTaskTeamdoesagreethatMSSshouldbeincorporatedintoARDtooptimizeuseoftheentire

forty-fiveyearsofcollectionhistory.However,theTeamrecommendsthatprioritizingdevelopmentworkshouldbecarefullyscrutinizedwithconsiderationgiventowhethergloballyextendingARDmaybemoreimportantthanspendingavailabletimeincorporatingtheMSScollection.Ingeneral,itisrecommendedthatUSGSassessallneedsandwantsandestablishcriteriatoprioritizeLandsatwork,includingenhancementstotheARDinitiative.

5. TheTaskTeamrecommendsthatUSGSshouldnotundertaketoscaletheUSARDcoverageeffort

globallybythemselves,astheprivatesectorisbetterpreparedwithneededtools,maturetechniques,and,particularlyscalableinfrastructure.

Thisreportalsomakesrecommendationsaboutgeospatialdatacubes,astheybecomemoregloballyemployedtomanageandexchangeinformationforavarietyofapplications.1. TheTaskTeamrecommendsthatUSGSrepresentation,asaStrategicMember,totheOpen

GeospatialConsortiumshouldadvocateforandparticipateinmorediscussionaboutdatacubestandardswithintheOGCTechnicalCommittee.

2. TheTaskTeamrecommendsthatpreparingdatacubesforspecificusesshouldnotbeanobjectiveofthegovernment,whichshouldbecautiousaboutproceedingevenwithproductionofsomegenericformsofadatacube.Thetailoreddatacubesshouldnotbeafederalgovernmentproductionresponsibility.

Additionalrecommendationsaremadewithreferencetothisreport.1. TheTaskTeamrecommendsthatasubsequentrequestbemadetoafutureLAGTeamtoevaluate

progressonthefindingsandrecommendationsofthispaperandtoupdateasneeded.2. TheUSGShasonlyfledglingexperiencewithARD,havingfirstreleasedittothecommunityofusers

attheendofOctober2017.Atthispoint,therehasnotbeenextensiveexperienceonthepartofARDusersandcertainlynotmuchevidenceoftheresultingdatacubes.ItwouldbehelpfulforUSGStosurveythosewhorequesttheARDonsomeroutinebasis,gatheringinformationforasubsequentreport.AmongthefactorstobesurveyedwouldbeifusersaretransitioningtoARDorstillrequestingthepreviousdistributionformats.ThePecoraConferenceinmid-November2017providedaninitialopportunityforgroupsofLandsatuserstodiscusstheirearlyreactionstothereleaseofARD.Sincethattime,usehasincreasedbutnotallusersarefullycomfortableknowinghowtousethedatatoitsbestadvantage.Similarly,on-goinginformationexchangesbetweenthepublicandprivatesectorsmayprovidemoreinsightintodefiningtheinterdependenciestomakedatacubesthemosteffectivewaytoadvanceuseofimageryandexpansionofGIStechnology.

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AcronymListforthisPaperALOS AdvancedLandObservingSatelliteJapaneseEarth-observationsatellite,

developedbyJAXA(JapanAerospaceExplorationAgency)ARD AnalysisReadyDataCEOS CommitteeonEarthObservationSatellitesCOG CloudOptimizedGeoTIFFCSIRO CommonwealthScientificandIndustrialResearchOrganisationisan

independentagencyoftheAustralianFederalGovernmentresponsibleforscientificresearchinAustralia.

DGGS DiscreteGlobalGridSystemEO Electro-opticalsystemsoperateintheopticalportionoftheelectromagnetic

spectrum.EROS EarthResourcesObservationandScience,aUSGSCenternearSiouxFall,SDERS EarthResourcesSatellite,thefirsttworemotesensingsatelliteslaunchedbyESAESA EuropeanSpaceAgencyETM+ EnhancedThematicMapperPlus,asensoronboardtheLandsat7satelliteFGDC FederalGeographicDataCommitteeGeoTIFF GeoreferencedTaggedImageFileFormat,apublicdomainmetadatastandard

whichallowsgeoreferencinginformationtobeembeddedwithinaTIFFfileL1 Level-1Landsatproductswiththebestavailableprocessinglevelforeach

particularsceneL1G Level-1Landsatradiometricallycalibratedwithsystematicgeometriccorrections

usingspacecraftephemerisL1T Level-1Landsatradiometricallycalibratedandorthorectifiedusingground

controlpointsanddigitalelevationmodeldatatocorrectforreliefdisplacementLAG LandsatAdvisoryGroupLCMAP LandChangeMonitoring,Assessment,andProjection,aUSGSinitiative

implementedatEROSLIDAR(Lidar,LiDAR) LightDetectionandRanging,aremotesensingandsurveyingmethodthat

measuresdistancetoatargetbyilluminatingthetargetwithpulsedlaserlightandmeasuringthereflectedpulseswithasensor

MSS Multi-spectralscanner,linescanningdevicesobservingtheEarthperpendiculartotheorbitaltrackonthefirstfiveLandsats

NASA NationalAeronauticsandSpaceAdministrationOGC® OpenGeospatialConsortiumOLAP Onlineanalyticalprocessing,useofdataorganizedmulti-dimensionallytoallow

comparisonsfromdifferentperspectivesOLI OperationalLandImager,apushbroomscanneronLandsat8thatusesafour-

mirrortelescopewithfixedmirrorsSAR Synthetic-apertureradar,atechniqueforproducingfineresolutionimagesfrom

anintrinsicallyresolution-limitedradarsystemSDC SwissDataCube

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TIRS ThermalInfraredSensor,asystemonLandsatthatmeasureslandsurfacetemperatureintwothermalbands

TOA Top-of-atmosphereUSGS U.S.GeologicalSurveyUTM UniversalTransverseMercator,acoordinatesystemwhichdividestheEarthinto

60zones,each6°oflongitudeinwidthWCPS WebCoverageProcessingService,aprotocol-independentlanguageforthe

extraction,processing,andanalysisofmulti-dimensionalcoveragesrepresentingsensor,image,orstatisticsdata

WELD WebEnabledLandsatDataWRS TheWorldwideReferenceSystem,aglobalnotationsystemforLandsatdataAcknowledgementsThispaperwasapprovedbytheNGACLandsatAdvisoryGroup(LAG)onMarch20,2018andadoptedbytheNGACasawholeonApril3,2018.TheLAGteamdevelopingthispaperincludedRobertaLenczowski,RobertaE.LenczowskiConsulting(TeamLead);FrankAvila,NationalGeospatial-IntelligenceAgency;PeterBecker,ESRI;StevenBrumby,DescartesLabs;RebeccaMoore,GoogleInc.;andTonyWillardson,WesternStatesWaterCouncil.MatthewHancher(Google,Inc.)andSaraLarsen(WesternStatesWaterCouncil)alsocontributedtothispaper.