1
MODISSRProductsuiteCollection6:(Releasedin2015)Bands1through7250m,500m,0.05deg.Daily,8daysStatusandUpdates:• MODISSRcollection6(LaSRC:LandSurfaceReflectance
Code)isthebasisforavarietyofSRproduct(VIIRS,AVHRR,Landsat,Sentinel2)assuringconsistencyandtraceabilityintheSRproductsfrommultiplesatellites/instruments.
• ValidationstageIV(AERONET)andcross-comparisonwithMODISison-going.
KnownIssues:• NoneRecentPublications:• Doxani,G.,Vermote,E.,Roger,J.C.,Gascon,F.,Adriaensen,S.,
Frantz,D.,Hagolle,O.,Hollstein,A.,Kirches,G.,Li,F.andLouis,J.,2018.Atmosphericcorrectioninter-comparisonexercise.RemoteSensing,10(2),p.352.
• Skakun,S.,Franch,B.,Vermote,E.,Roger,J.C.,Becker-Reshef,I.,Justice,C.andKussul,N.,2017.Earlyseasonlarge-areawintercropmappingusingMODISNDVIdata,growingdegreedaysinformationandaGaussianmixturemodel.RemoteSensingofEnvironment,195,pp.244-258.
• Breon F.M.,Vermote E.F.,MurphyE.,Franch B.,(2015)Measuringthedirectionalvariationsoflandsurfacereflectances fromMODIS,IEEEtransactionsonGeoscienceandRemoteSensing,53(8),4638-4649.
StatusofMODISSR
“Contrarytopopularopinion,treecoverincreasedby2.24millionsquarekilometers(morethan850,000squaremiles),anincreaseofabout7percentduringthetimeperiod.”
DevelopmentofaGlobalBurnedAreaEarthSystemDataRecord
LouisGiglio1,LuigiBoschetti2,DavidRoy3,Varaprasad Bandaru1,ChrisJustice11UniversityofMaryland,2UniversityofIdaho,3SouthDakotaStateUniversity
December2003MODISBurnedAreaProduct
3
MODISBurnedAreaProductCollection6:(released2017)
•MCD64A1: MonthlyL3500mSINGrid•MCD64CMH: MonthlyCMG(released2018)
StatusandUpdates:• Stage-2validationcomplete.• Stage-3validationinpreparation.
KnownIssues:• Edgefixfor26tiles(patch6.0.8).RecentPublications:• Giglio,L.,Boschetti,L.,Roy,D.P.,Humber,M.L.,andJustice,C.O.,2018,TheCollection6MODISburnedareamappingalgorithmandproduct.RemoteSensingofEnvironment,217:72–85.
• Humber,M.L.,Boschetti,L.,Giglio,L.,andJustice,C.O.,2018,Spatialandtemporalintercomparison offourglobalburnedareaproducts,InternationalJournalofDigitalEarth.
• Andela etal.,2017,Ahuman-drivendeclineinglobalburnedarea.Science,356:1356-1362.
StatusofMODISBurnedArea
4
MODISActiveFireProductsCollection6:(released2015)•MOD14/MYD14: Terra/AquaL2Swath•MOD14A1/MYD14A1:L3Daily500-mSINGrid•MOD14A2/MYD14A2:L38-day500mSINGrid•MCD14ML: Monthlyfirelocations
StatusandUpdates:• Widelyusedmatureproduct.• Stage-2validated.
KnownIssues:• None.RecentPublications:• Giglio,L.,Schroeder,W.,andJustice,C.O.,2016,Thecollection6MODISactivefiredetectionalgorithmandfireproducts.RemoteSensingofEnvironment,178,31-41.
StatusofMODISActiveFire
5
MODISGPP/NPPandET/PETproducts.Collection6:
• MOD17A3H: MODIS/TerraAnnuallyL4500mSINGrid• MYD17A3H: MODIS/AquaAnnuallyL4500mSINGrid• MOD17A2H: MODIS/Terra8-dayL4500mSINGrid• MYD17A2H: MODIS/Aqua8-dayL4500mSINGrid• MOD16A3: MODIS/TerraAnnuallyL4500mSINGrid• MYD16A3: MODIS/AquaAnnuallyL4500mSINGrid• MOD16A2: MODIS/Terra8-dayL4500mSINGrid• MYD16A2: MODIS/Aqua8-dayL4500mSINGrid
StatusandUpdates:• CreationofanoptimizedFPAR/LAIclimatology.• ThisclimatologywillbeusedtoobtaingapfreeGPP/NPPandET/PET
productsfortheupcomingcollection6.1.
KnownIssues:• Importantgapsduetocloudcontaminationinheavilycloudedareas.RecentPublications:• AlvaroMoreno,Gustau Camps-Valls,JensKattge,NathanielRobinson,
MarkusReichstein,…,StevenW.Running(2018).Amethodologytoderiveglobalmapsofleaftraitsusingremotesensingandclimatedata,RemoteSensingofEnvironment,218,69-88.
• Madani,N.,Kimball,J.S.,Ballantyne,A.P.,Affleck,D.L.,Bodegom,P.M.,Reich,P.B.,...&Zhao,M.(2018).Futureglobalproductivitywillbeaffectedbyplanttraitresponsetoclimate.Scientificreports,8(1),2870.
• He,M.,Kimball,J.S.,Maneta,M.P.,Maxwell,B.D.,Moreno,A.,Beguería,S.,&Wu,X.(2018).RegionalCropGrossPrimaryProductivityandYieldEstimationUsingFusedLandsat-MODISData.RemoteSensing,10(3),372.
• Jones,M.O.,Running,S.W.,Kimball,J.S.,Robinson,N.P.,&Allred,B.W.(2018).TerrestrialprimaryproductivityindicatorsforinclusionintheNationalClimateIndicatorsSystem.ClimaticChange,1-14.
• DavidJ.Mildrexler,Maosheng Zhao,WarrenB.Cohen,StevenW.Running,Xiaopeng Song,MatthewO.Jones.2018,ThermalAnomaliesDetectCriticalGlobalLandSurfaceChanges.J.AppliedMeteorologyandClimatology,57,391-411.
StatusofMODISGPP/NPP,ET/PETproductsandanLSTforfun.
6
MODISBRDFAlbedoNBARProductsCollection V006:
• MCD43A:500mSINgrid• MCD43A1:BRDF/AlbedoModelParameters• MCD43A2:BRDF/AlbedoQuality• MCD43A3:Albedo• MCD43A4:NBAR• MCD43C:0.05degreeCMG• MCD43C1:CMGBRDF/AlbedoModelParameters• MCD43C2:CMGBRDF/AlbedoModelSnow-FreeParameters• MCD43C3:CMGAlbedo• MCD43C4:CMGNBAR• MCD43D:30Arc-SecondCMG(1– 40)• MCD43GF:CMGGap-FilledSnow-Free
StatusandUpdates:• Newdailyretrievalsarebeingusedextensivelyfor
phenologystudies.• SnowfreeGapFilledV006products
(MCD43GF)areunderproduction
KnownIssues:• None
RecentPublications:• Wang,Z.,Schaaf,C.B.,Sun,Q.,Shuai,Y.,&Román,M.O.
(2018).CapturingRapidLandSurfaceDynamicswithCollectionV006MODISBRDF/NBAR/Albedo(MCD43)Products.RemoteSensingofEnvironment,207(February),50–64.https://doi.org/10.1016/j.rse.2018.02.001
• Sun,Q.,Wang,Z.,Li,Z.,Erb,A.,&Schaaf,C.B.(2017).EvaluationoftheGlobalMODIS30Arc-SecondSpatiallyandTemporallyCompleteSnow-FreeLandSurfaceAlbedoandReflectanceAnisotropyDataset.InternationalJournalofAppliedEarthObservationandGeoinformation,58,36–49.https://doi.org/10.1016/j.jag.2017.01.011
StatusofTerra/AquaMODISBRDF,AlbedoandNBAR
MCD43D61:DOY250,2010ShortwaveBroadbandWSA
MCD43GF:DOY250,2010ShortwaveBroadbandWSA 1.0 0.0
GeneratingcontinuoustimeseriesofdailysnowcoverwiththeMODISCloud-Gap-Filled(CGF)Product
DorothyHall1 andGeorgeRiggs21ESSIC/UniversityofMaryland,2SSAI
Thecloud-gapfilled(CGF)MODISproductprovidesaconsistentandcontinuouscloudfreesnowcovermap(A)comparedtothedailysnowcoverproduct(B)thathascloudswhichcausegapsinatimeseriesofsnowobservations.TheCGFmapsareabletocapturesnowbuildupanddepletion(C),forexampleinWindRiverRange,
Wyoming,1Febto30April2012 (C).
Cloud-GapFilledDailySnowMap DailySnowMapwith Cloud
Cloud
(A) (B)
(C)
19March2012
ComparisonofTerraCGFandthestandardTerrasnow maps
8
MODISSnowCoverProductCollection6.1:
• New-- M*D10A1F: DailyCloud-gap-filledproductMODIS/Terra/AquaL3500mSINGrid
• M*D10_L2revisedalgorithmanddatacontent,improvedsnowcoverdetection
StatusandUpdates:• Snowcoveralgorithm:revisedlowvisiblereflectance
screenandaddedtwoalgorithmQAbitflags• ProductuserguidesupdatedforC6.1KnownIssues:• Investigatingcloud/snowconfusionandaffectof
aerosolsonthesnowcoveralgorithm
RecentPublications:• Hall,D.K.,R.I.Cullather,J.C.Comiso,N.E.DiGirolamo,S.M.Nowicki
andB.C.Medley,2018:AmultilayerIST– albedoproductofGreenlandfromMODIS,RemoteSensing[SpecialIssue:RemoteSensingofEssentialClimateVariablesandtheirApplications].FeaturePaper.10(4),555;https://doi:10.3390/rs10040555.
• Hall,D.K.,A.FreiandN.E.DiGirolamo,2018:Onthefrequencyoflake-effectsnowfallintheCatskillMountains,PhysicalGeography,https://doi:10.1080/02723646.2018.1440827.
• Riggs,G.A.,D.K.HallandM.O.Román,2017:OverviewofNASA’sMODISandVisibleInfraredImagingRadiometerSuite(VIIRS)snow-coverEarthSystemDataRecords,EarthSystemDataRecords,9:765-777,https://www.earth-syst-sci-data-discuss.net/essd-2017-25/.
StatusofMODISCryosphereProductsDorothyHall1 andGeorgeRiggs2
1ESSIC/UniversityofMaryland,2SSAI
AuniqueMODISmulti-layerGreenlandISTandsurfacealbedoproductwasgeneratedbyourteam
andisarchivedatNSIDC.
9
MODISVISuite(inits19thyear)Collection5:(Suspendedin2018)Collection6:(Releasedin2015)Collection7: (Inprep)StatusandUpdates:• ImprovedQAcompositingscheme• Multipleandongoingalgorithmadjustmentstodealwithchangesin
upstreamproductsand/orissues• Ongoingopportunisticvalidation(usingNEONdata)
KnownIssues:• The2010(C6)decisiontousepre-composited8-daysurfacereflectance
inputsiscausingspatialconsistencyissuesthatwillbeaddressedinC6.1/C7
RecentPublications:• Jarchow,C.J.,Didan,K.,Barreto-Muñoz,A.,etal.(2018).Applicationand
ComparisonoftheMODIS-DerivedEnhancedVegetationIndextoVIIRS,Landsat5TMandLandsat8OLIPlatforms:ACaseStudyintheAridColoradoRiverDelta,Mexico. Sensors, 18(5),1546.
• EL-Vilaly,M.A.S.,Didan,K,etal.(2018).CharacterizingDroughtEffectsonVegetationProductivityintheFourCornersRegionoftheUSSouthwest. Sustainability, 10(5),1643.
• El-VilalyMA,DidanK,etal.VegetationproductivityresponsestodroughtontriballandsinthefourcornersregionoftheSouthwestUSA.FrontiersofEarthScience.2017May:1-5.DOI10.1007/s11707-017-0646-z
• PengD,ZhangX,WuC,HuangW,etal.IntercomparisonandevaluationofspringphenologyproductsusingNationalPhenologyNetworkandAmeriFluxobservationsinthecontiguousUnitedStates.Agriculturalandforestmeteorology.2017Aug15;242:33-46.
StatusofMODISLongTermVITimeSeries
MODIS NDVI/EVI product suitecontinues to lead and drive scienceand applications with more than12,000 publications mentioningand/or using the MODIS NDVI/EVItime series, with multiple high endjournal articles appearing annually.
Jin,Q.,&Wang,C.(2018).ThegreeningofNorthwestIndiansubcontinentandreductionofdustabundanceresultingfromIndiansummermonsoonrevival. Scientificreports, 8(1),4573.
AdvancingMODIS-VIIRSClimateDataRecordswithAlgorithmMAIAC
AlexeiLyapustin1,YujieWang2,SergeyKorkin3,DongHuang41NASAGSFC;2UMBC;3USRA;4SSAI
MAIAC MODIS algorithm improves the quality ofcloud/snow detection, aerosol retrievals andatmospheric correction. (A) Chen et al., (2017)showed improvement in LAI retrieval when usingMAIAC surface reflectance as input; (B) Di et al.(2017) shows the risk of mortality curve as afunction of air quality at PM2.5 levels well below theNational Ambient Air Quality Standards (35µg/m3).National daily 1km PM2.5 for this study (2000-2012)was obtained using MAIAC AOD from MODIS.
(A)
(B)
(C)
Riskofdeath(7.3%)at10µg/m3 increaseinPM2.5 (Dietal.,AirPollutionandMortalityintheMedicarePopulation,TheNewEnglandJournalofMedicine,doi:10.1056/NEJMoa1702747)
11
MCD19ProductSuiteCollection6:(ReleasedinSpringof2018)• MCD19A1: SurfaceReflectance
– DailyL31km:BRFinbands1-12;Snowgrainsizeandsnowfraction;– DailyL3500m:BRFinbands1-7;
• MCD19A2: Atmosphericproperties– DailyL31km:CM,AOD,CWV,PlumeInjectionHeight(fordetectedsmoke)
• MCD19A3: BRDF/Albedo– 8-DayL31km:RTLSBRDF,instantaneousalbedoinbands1-8;
StatusofMODISMAIAC(MCD19)
AODColumnWVRGBSRSnowFrac,1kmRGBKiso (RTLS)
DOY
230
DOY
60, 2
005
StatusandUpdates:• FixingknownissuesforC6.1KnownIssues:• RegionalaerosolmodelscauseAODdiscontinuity
in3regions(Sahel,SouthernAfrica,WestIndia)• Detectionofseaice• Seasonalityofaerosolmodels(toadd)• Missingsomebrightsaltpans
RecentPublications:• Lyapustinetal.,2018.MODISCollection6MAIACAlgorithm,Atm.Meas.Techniques,doi:10.5194/amt-2018-141.• Cooperetal.,2018.AssessingsnowextentdatasetsoverNorthAmericatoinformandimprovetracegasretrievalsfromsolar
backscatter,Atm.Meas.Techniques,doi:10.5194/amt-11-2983-2018.• LiangF.etal.,2018.MAIAC-basedLong-termSpatiotemporalTrendsofPM2.5inBeijingChina,ScienceofTheTotalEnvironment,doi:
10.1016/j.scitotenv.2017.10.155.• Chenetal.,2017.PrototypingofLAIandFPARRetrievalsfromMODISMulti-AngleImplementationofAtmosphericCorrection(MAIAC)
Data.RemoteSensing,doi:10.3390/rs9040370
12
MODISLAI/FPARProductCollection6:(Releasedin2015)
• MOD15A2H: MODIS/Terra8-DayL4500mSINGrid• MYD15A2H: MODIS/Aqua8-DayL4500mSINGrid• MCD15A2H: MODIS/Terra+Aqua 8-DayL4500mSINGrid• MCD15A3H: MODIS/Terra+Aqua 4-DayL4500mSINGrid
StatusandUpdates:• L2G–lite500metersurfacereflectanceusedasinput,
instead ofreflectanceat1kmresolutionMODAGAGG.• Newmulti-yearlandcoverproductat500mresolution,in
placeofthe1kmresolutionstaticlandcoverproduct.
KnownIssues:• N/A.RecentPublications:• Chenetal.,(underreview).ChinaandIndialeadingreeningoftheworldthroughland-usemanagement.NatureSustainability.
• Xuetal.,2018.Anintegratedmethodforvalidatinglong-termleafareaindexproductsusingglobalnetworksofsite-basedmeasurements.RemoteSens.Environ.,doi:10.1016/j.rse.2018.02.049
• Chenetal.,2017.PrototypingofLAIandFPARRetrievalsfromMODISMulti-AngleImplementationofAtmosphericCorrection(MAIAC)Data.RemoteSensing,doi:10.3390/rs9040370
StatusofMODISLAI/FPAR
MODISLSTDetectsRisingTemperaturesandHeatWaveTrendsinUrbanEnvironments
NewMOD21LSTproductcanpinpointcurrentandfuturecommunitiesthataremostvulnerabletothedetrimentaleffectsofheatwavesandextremeheatinurbanareas.Heatvulnerabilitymapsderivedfromthisdatacanadviselocalgovernmentsoneffectiveclimateadaptionandmitigationstrategies.
Hulley etal.2018,RSE
LosAngeles
14
StatusandUpdates:• NewLST&EproductinCollection6,reprocessingunderwayatMODAPS.ReleaseFall2018• Allissueswithproduct/coderesolved.Allattributes,metadata,browseimagesclearedbyLPDAAC
MOD21LST&EProducts:Collection6:(ReleaseFall2018)
• MxD21L2:Daily5-minL2Swath1km• MxD21A1:DailyL3Global1km• MxD21A28-dayL3Global1km
Collection6.1:(Release2019)• MxD21C1:Daily0.05degreeClimateModelingGrid(CMG)• MxD21C2:8-day0.05degreeClimateModelingGrid(CMG)• MxD21C3:Monthly0.05degreeClimateModelingGrid(CMG)
KnownIssues:• Limitedsupportthroughnextfundingcycleresultinginsemi-orphanedproducts.• LST&E(MxD11/MxD21)have10differentproducttypes!Resultsinuserconfusion,reducedusability.• NosupportorplanforwardtoretireMxD11suiteofproducts.Requiresanalyzingandcomparing
MxD11/MxD21products.Potentialtoreduceto5producttypesfromMxD21(JPLproduct).
Publications/Documentation:• Hulley,G.C.,Malakar,N.,Islam,T.,Freepartner,R,(2017),NASA’sMODISandVIIRSLandSurfaceTemperatureandEmissivityProducts:AConsistentandHighQualityEarthSystemDataRecord,IEEETGRS,DOI:10.1109/JSTARS.2017.2779330.
• Malakar,N.K.,andG.C.Hulley (2016),AwatervaporscalingmodelforimprovedlandsurfacetemperatureandemissivityseparationofMODISthermalinfrareddata,RemoteSensingofEnvironment,182,252-264
• UserguideandATBDavailableat:https://modis.gsfc.nasa.gov/data/dataprod/mod21.php
StatusofMODISLST&E