VIIRSLandDisciplineStatuspost-Terra/AquaSeniorReviewandROSESA.37

1

MiguelRomán(GSFC)withcontributionsfromthe

T/A/S-NPPLandDisciplinePIsandLandSIPSteams.

Background

The Earth Observing System (represented by Terra/Aqua/Aura) was intended toprovide global observations needed to advance Earth System Science and toinitiate a number of improved long- term global data sets.

Suomi-NPP (launched in 2011) extends more than 11 high-quality TerrestrialEarth System Data Records (ESDRs) initiated by earlier NASA satellites.

Productsselectedin2017ROSESTASNPPsolicitation(A.37)• SurfaceReflectanceandVegetation

Indices (Vermote)• LandSurfaceTemperatureandEmissivity• SnowCover,SeaIceCoverandIce

SurfaceTemperature(Riggs)• ActiveFires(SchroederandGiglio)• BurnedArea• LeafAreaIndex(LAI)&Fraction

AbsorbedPhotosyntheticallyActiveRadiation(FPAR)

• BRDF(Bi-directionalReflectanceDistributionFunction)/Albedo(Schaaf)

• VegetationContinuousFields• LandCover• VIIRSLandSurfacePhenology(Zhang)NewStandard/ExperimentalProducts:• MODISRadiation(Wang)• MAIAC(Lyapustin)• VIIRSBlackMarble(Román)

OrphanedProducts

2

NASAVIIRSLandProductInterdependencies

AncillaryInputsNCEP,NISE,LWMask,LandCover,DEM

L2DailySwathProductsCloudMask,AerosolOpticalThickness,Snow

Cover,Sea-Ice,SurfaceReflectance,ActiveFires,LandSurfaceTemperatureandEmissivity

L3TiledandClimateModelingGridProducts(DailyandMulti-date)SurfaceReflectance,SnowCover,Sea-ice,LandSurfaceTemp./Emissivity

ActiveFires,BurnedArea,VegetationIndices,BRDF/AlbedoLeafAreaIndex&FPAR,Phenology,NighttimeLights

L1SwathProductsCalibratedRadianceandReflectance,

GeolocationFields

DailyL2GTiledandIntermediateProductsSurfaceReflectance,Fire,SnowCover,Sea-Ice,Land

SurfaceTemperatureandEmissivity

L2GDailyTiledProductsGridPointer,GridAngularData

A.37OrphanedProducts

DownstreamProductImpacts• MissinginputstoLAIproduct:

• Level3LandCover• MissinginputstoPhenologyProduct:

• Level3LandCover• MissinginputstoNASABlackMarble

product(VNP46)• Level3LandCover• Level3LeafAreaIndex

ThroughTerra/Aquaendoflife,impactsonproductinterdependencieswillcontinuetobemitigatedusingMODIS-equivalentC6products.

3

V1.0 SNPP VIIRS Land Product Status

EOS ProductsAlgorithms

Delivered to Land SIPS

Product Integration and Testing ATBD Delivery

Delivery of User's Guide

Products Delivered to assigned DAAC

Surface Reflectance ✓ ✓ ✓ ✓ ✓

LAI/FPAR ✓ ✓ ✓ ✓ ✓

Snow Products ✓ ✓ ✓ ✓ ✓

MAIAC Qtr 4, 2018 Qtr 4, 2018 Qtr 3, 2018 Qtr 1, 2019 V2.0 - Qtr 1, 2019

BRDF/Albedo ✓ ✓ ✓ ✓ ✓

Burned Area Qtr 3, 2018 Qtr 4, 2018 ✓ Qtr 4, 2018 Qtr 1, 2019

Active Fires ✓ ✓ ✓ ✓ ✓

Vegetation Index ✓ ✓ ✓ ✓ ✓

LST&E ✓ ✓ ✓ ✓ Qtr 4, 2018

Ice Surface Temp ✓ ✓ ✓ ✓ ✓

Sea Ice Cover ✓ ✓ ✓ ✓ ✓

Phenology ✓ Underway ✓ ✓ Qtr 4, 2018

Black Marble ✓ Underway ✓ ✓ Qtr 1, 2019

DetailsinReportsattheLandBreakoutsession

5

VIIRSLandSIPSProcessingStatus:V1.0SNPPVIIRS• V1forwardprocessingofLandproductsaretypically1-2daysbehindreal

time.• MODISheritageVIIRSproductsgeneratedusingtheNASAscienceteam

deliveredalgorithms.• UsesV1L1BSDRgeneratedusingtheNOAA/IDPSMx8.11versionofthe

operationalsoftwareandNASAVCSTprovidedLUT.• L2productsareinHDF5/netcdf4andL3/L4productsareinHDF5-EOS

format.• Productscurrentlyinoperationalprocessingandavailabletopublicfrom

NASADAACs• LSR,VI,BRDF-Albedo,LAI-Fpar,L2Fire,L2SnowandSea-ice:Available

forthemissionperiod• L3Fire,LST:ReprocessinginprogressandtobecompletedinNov2018• BA,L3SnowandSea-ice,Phenology:ProductstobeavailablebyJan

2019• NRTprocessingofV1Land(usingV1L1B)iscompletedtypically2to2.5

hoursafteracquisitionofdata.• Productsinprocessing– LSR,Fire,BRDF-Albedo,SnowandSea-ice

6

VIIRSLandSIPSProcessingPlan:BeyondSNPPV1.0

• V2.0SNPPVIIRSLandReprocessing(Spring2019)• V2ReprocessingwillstartafterprocessingofproposedVIIRSland

productsiscompletedintheon-goingV1reprocessing.• ThisreprocessingwillusetheNASAL1Bgeneratedusingthelatest

versionoftheL1BcalibrationalgorithmandLUTdeliveredbytheNASAVCSTandGeoteam.

• WillusetheLandPGEsusedintheV1reprocessingwithNASAScienceTeamrecommendedchanges.

• V1.0/V2.0J1VIIRSLandReprocessing(Spring2019)• ExpectedtostartaftercompletionoftheSNPPV1Landreprocessing.• WillusetheSNPPVIIRSPGEsportedtoprocessJ1VIIRSdata• J1VIIRSNASAL1BtobegeneratedusingtheNASAcalibrationalgorithm

andpost-launchcalibrationLUTdeliveredbytheNASAVCST.

DetailsinReportsattheLandBreakoutsession

GeneratingconsistentandcontinuoussurfacereflectanceproductsuitefromSuomi-NPPVIIRSandEOSMODIS

E.Vermote,S.Skakun,RogerJC,FranchB.,J.Pinzón,C.Tucker

Cross comparison of the VIIRS and MODIS Aqua SRproducts for the BELMANIP2 sites (A). The plots show thatthe NASA reprocessing of VIIRS (C1.1) is in a goodagreement with MODIS (B). Continuous monitoring of VIIRSCollection V1 reprocessing ensures productstability/consistency.

(A)

(B)

(C)

Key Findings: VIIRS SR product secures the Long Term datacontinuity from the MODIS global Land record which iscrucial for the NASA Earth Science mission.

8

StatusofVIIRSSR

VIIRSSRProductCollection 1: (Released in 2017)

• VNP09(level2SurfaceReflectance),VNP09G1KI,VNP09GHKI,andVNP09GA(griddeddailyproductat500mand1km),VNP09A1andVNP09H1(gridded8daycompositeproductat500mand1km),VNP09CMG(thedailyglobalproductintheclimatemodelinggridat0.05deg).

StatusandUpdates:• AdaptedfromMODISLaSRC (LandSurfaceReflectance

Code)• ValidationstageIV(AERONET)andcross-comparisonwith

MODISison-going.KnownIssues:• NoneRecentPublications:• Skakun,S.,Justice,C.O.,Vermote,E.andRoger,J.C.,2018.

TransitioningfromMODIStoVIIRS:ananalysisofinter-consistencyofNDVIdatasetsforagriculturalmonitoring.InternationalJournalofRemoteSensing,39(4),pp.971-992.

• Pahlevan,N.,Sarkar,S.,Devadiga,S.,Wolfe,R.E.,Román,M.,Vermote,E.,Lin,G.,Xiong,X.(2016).ImpactofSpatialSamplingonContinuityofMODIS-VIIRSLandSurfaceReflectanceProducts:ASimulationApproach,IEEETransactionsonGeoscienceandRemoteSensing55.1(2017):183-196.

• Vermote E.,JusticeC.,Csiszar I.,EarlyevaluationoftheVIIRScalibration,cloudmaskandsurfacereflectanceEarthdatarecords,RemoteSensingofEnvironment,Volume148,25May2014,Pages134-145,ISSN0034-4257,http://dx.doi.org/10.1016/j.rse.2014.03.028

NDVIanomaliesat0.05° spatialresolutionforthestateofIowa(US)derivedfromMODIS/Aqua(a),andadjustedVIIRS(b)dataonAugust21,2012.AnomalieswerecomputedbysubtractingNDVIvaluesfromthemedianNDVIvaluesfor2002–2016derivedfromMODIS/Aqua

Thederiveduncertainties(forsurfacereflectanceandVIs)relatedtothecombineduseofMODISandVIIRSproductsarebeingestimatedandreportedtousercommunitytofurtherquantifyuncertaintiesforhighlevelproducts,(e.g.cropyieldmodels).

9

StatusofVIIRSBurnedArea

VIIRSVNP64A1ProductCollection 1: (2019release)

• VNP64A1: S-NPPMonthlyL3500mSINGrid• VNP64CMH: MonthlyCMG

StatusandUpdates:• AdaptedfromMODISburnedarea

sciencecode.• UpstreamVNP64A0intermediate

productintegratedintoLandSIPSinSeptember2017.

• VNP64A1codedeliveryawaitingsufficientupstreaminputdatafortestingandtuning.

S-NPP/VIIRSActiveFireProductSuite:BridgingEOSandJPSSLouisGiglio1,WilfridSchroeder2,JoanneHall1

1UniversityofMaryland,2NOAANESDIS

S-NPP/VIIRS375mAqua/MODIS1km

1-km Aqua MODIS (left) and near-coincident 375-m S-NPP VIIRS (right) mapping of fire progressionduring the 2014 King Fire event in California. Colored polygons describe the active fire pixel footprintsof MODIS and VIIRS. The black polygon outlines the fire-affected area mapped using the backgroundLandsat-8/OLI image acquired on 5 October 2014

11

StatusofVIIRSActiveFire

VIIRSVNP14ProductFamilyCollection 1: (2017release)

• VNP14: L2750-m• VNP14IMG: L2375-m• VNP14A1:DailyL31kmSINGrid

StatusandUpdates:• AdaptedfromMODISactivefire

detectionalgorithm.• 375-mproductmuchmoresensitiveto

smallfires.• NRTversionof375-mproductproduced

inLANCEanddistributedbyFIRMS.

KnownIssues:• M13atmosphericabsorption• Properflaggingofuncalibratedand/or

poorlycalibratedradiancedata

Yellow perimeter: VIIRS fire perimeter used for model initialization. Red perimeter: VIIRS fire perimeter 12 h later.

VIIRS375-mfireproductnowallowsrobustpredictivefiremodelingtobeperformedinNRTusingCAWFEmodel(J.Coen,NCAR).

ConsistentBRDF,Albedo,andNBARproductsfromSuomi-NPPVIIRSandTerra/AquaMODISCrystalSchaaf`1,ZhuosenWang2,3 QingsongSun2,4, YanLiu1,ZhanLi1,

AngelaErb1,ArthurElmes1,JiaTian11SchoolfortheEnvironment,UniversityofMassachusettsBoston,BostonMA,USA

2TerrestrialInformationSystemsLab,NASAGoddardSpaceFlightCenter,Greenbelt,MD,USA3 EarthSystemScienceInterdisciplinaryCenter,UniversityofMaryland,CollegePark,MD,USA

4ScienceSystemsandApplications,Inc.,Lanham,MD,USA

VIIRS BRDF, Albedo and NBAR are providing products consistentwith the corresponding MODIS products. New narrow tobroadband conversion coefficients have been developed toproduce the broadband values most commonly measured by fieldinstruments and used in modeling studies.Figure (a) VIIRS shortwave broadband WSA, 9 May 2015, (b) Truecolor NBAR M5-Red, M4-Green, and M3-Blue: 0-0.4, (c) QA

TheMODISandVIIRSproductsrelyonhighqualitymulti-date,multi-anglesurfacereflectances toretrieveadailysurfaceBRDFforeachgridpoint.ThisBRDFisthenusedtoproduceWhiteSkyAlbedo(bihemispherical albedounderisotropicillumination),BlackSkyAlbedo(directionalhemisphericalalbedounderlocalsolarnoonillumination)andNadirBRDF-AdjustedReflectance(NBAR).ExtensiveQAfieldsareprovided.Albedoisretrievedaseitherasnowalbedoorasnowfreealbedodependingontheconditionofthedailydayofinterest.

00.050.10.150.20.250.30.35

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13

StatusofSuomi-NPPVIIRSBRDF,AlbedoandNBAR

VIIRSBRDF,Albedo,NBARProductCollection V001: (Released in 2018)

• VNP43A: VIIRS/S-NPPDailyL4500mSINGrid–• VNP43IA1/VNP43MA1:BRDF/AlbedoModelParametersforImagery(IA)andModerate(MA)bands• VNP43IA2/VNP43MA2:BRDF/AlbedoQuality• VNP43IA3/VNP43MA3:Albedo• VNP43IA4/VNP43MA4:NBAR• VNP43DNBA1:DNBBRDF/AlbedoModelParameters• VNP43DNBA2:DNBBRDF/AlbedoQuality• VNP43DNBA3:DNBAlbedo• VNP43DNBA4:DNBNBAR

StatusandUpdates:• CMGproductsareintegratedandbeingtestedand

reviewed.• Albedoproductcomparedtotoweralbedos,e.g.from

SURFRAD:DesertRockandFortPeck,andNEON:HarvardForest

KnownIssues:• NoneRecentPublications:• Liu,Y.,Wang,Z.,Sun,Q.,Erb,A.M.,Li,Z.,Schaaf,C.B.,Zhang,X.,

Román,M.O.,Scott,R.L.,Zhang,Q.,Novick,K.A.,SyndoniaBret-Harte,M.,Petroy,S.,&SanClements,M.(2017).EvaluationoftheVIIRSBRDF,AlbedoandNBARproductssuiteandanassessmentofcontinuitywiththelongtermMODISrecord.RemoteSensingofEnvironment,201(February),256–274.https://doi.org/10.1016/j.rse.2017.09.020

• Liu,Y.,Hill,M.J.,Zhang,X.,Wang,Z.,Richardson,A.D.,Hufkens,K.,Filippa,G.,Baldocchi,D.D.,Ma,S.,Verfaillie,J.,&Schaaf,C.B.(2017).UsingdatafromLandsat,MODIS,VIIRSandPhenoCams tomonitorthephenologyofCaliforniaoak/grasssavannaandopengrasslandacrossspatialscales.AgriculturalandForestMeteorology,237–238,311–325.https://doi.org/10.1016/j.agrformet.2017.02.026

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FortPeck2016

HarvardForestNEON2016

DesertRock2016

l VIIRSAlbedo l SurfaceAlbedol MODISAlbedo

14

StatusofVIIRSCryosphereProductsGeorgeRiggs1,DorothyHall2 andMarkTschudi3

1SSAI,2ESSIC/UniversityofMaryland,3UniversityofColorado,Boulder

VNP10A1.A2018001.h10v04.SnowCover

VIIRSISTproductisapotentialcontributiontoperformanceelement3.1.4oftheArcticresearchplanoftheInteragencyArcticResearchPolicyCommittee(IARPC).

VIIRSProducts:L2• SnowCover• SeaIceExtent• SeaIceSurfaceTemperature(IST)L3• SnowCover

StatusandUpdates:• L3snowcovercode delivered,intest• VIIRScloud-gap-filledsnowcoverproduct,similar

toMODIS,willbedeveloped• RevisedcodestouseNASAVNPL1Binputproducts• Investigatingcloud/snowconfusionandaerosol

effects• ISTvalidated• ProductsuserguideisbeingupdatedKnownIssues:• ChangetousingtheUniversityofWisconsinVIIRS

cloudmaskproductasinput.• Collection2– evaluatechangetousingNASAVNP

L1BinputsintheL2algorithms.RecentPublications:

NDSISNOWCOVER

1 100

CLOUD

LAKE/RIVER

NODECISION

ArcticSeaIceLeadPropertiesfromMODIS/VIIRS

Leadsfrequencymapbyyear.Legendisatbottomofthefigure.

SeasonisJanuary- April

Sea ice leads play a critical role in theexchange of mass and energy between theocean and atmosphere in the polar regions,particularly in the Arctic. We are developinga methodology to detect and characterizesea ice leads applied to MODIS and VIIRSdata to identify lead characteristics,including width, orientation, and spatialdistribution, which can aid in navigation andis essential to investigate any correlationswith observed chances in the Arctic Sea Ice.

16

StatusofVIIRSMAIAC

VIIRSMAIACProduct• N/AStatusandUpdates:• AdaptedfromMODISMAIACC6.1

operationalcode.• Theinputarea-weightedgridding

algorithmhasjustbeendelivered(V.Kalb,R.Wolfe).

• DeliveryoftestedVIIRScodeexpectedlate2018.

KnownIssues:• N/ARecentPublications:• N/A

ExampleofMAIACprocessingoftheVIIRSmeasurementsovertheEastCoastUSAfor17May,2012illustratingMAIACcloudmask(CM),aerosolopticaldepth(AOD)at0.44µm,andRGBresultofatmosphericcorrection.

17

StatusofVIIRSLAI/FPAR

VIIRSLAI/FPARProductCollection 1: (Released in 2018)

• VNP15A2H: VIIRS/S-NPP8-DayL4500mSINGrid

StatusandUpdates:• AdaptedfromMODISLAI/FPARsciencecode.• Resultsarereviewedandvalidated.

KnownIssues:• Producthasbeenorphanedpost-A.37.RecentPublications:• Xuetal.,2018.AnalysisofGlobalLAI/FPARProductsfromVIIRSandMODISSensorsforSpatio-TemporalConsistencyandUncertaintyfrom2012–2016.Forests,doi:10.3390/f9020073

• Yanetal.,2017.GeneratingGlobalProductsofLAIandFPARFromSNPP-VIIRSData:TheoreticalBackgroundandImplementation.IEEETGRSS.,doi:10.1109/TGRS.2017.2775247

MODIS/VIIRSLST&EContinuity

• LandSurfaceTemperatureandEmissivity(LST&E)arekeyvariablesusedinawiderangeofstudiesincludingclimatevariability,landcoveruse/change,andtheenergybalancebetweenlandandatmosphere.

• NewNASALST&EproductsforMODIS(MxD21)andVIIRS(VNP21)beingproducedin2017useaconsistentalgorithm(TES)thatphysicallyretrievesbothLSTandemissivityandaddressesdiscrepanciesbetweenthecurrentsuiteofMODISandVIIRSLSTsplit-windowbasedproducts(MYD11,VLSTO).

• ContinuitybetweenthenewMYD21/VNP21LSTdatarecordswasdemonstratedatthe

19

StatusandUpdates:• NewLST&EproductinVIIRSCollection1• FinalsciencetestcompleteandevaluationatLDOPE.ReprocessingtobegininFall2018

VNP21LST&EProducts:Collection1:(ReleaseFall2018)

• VNP21L2:Daily5-minL2Swath750m• VNP21A1:DailyL3Global750m• VNP21A28-dayL3Global750m

Productsstillindevelopment:• VNP21C1:Daily0.05degreeClimateModelingGrid(CMG)• VNP21C2:8-day0.05degreeClimateModelingGrid(CMG)• VNP21C3:Monthly0.05degreeClimateModelingGrid(CMG)

KnownIssues:• Limitedsupportthroughnextfundingcycleresultinginsemi-orphanedproductsandlimited

supportforvalidationanduncertaintyquantification.Publications/Documentation:• Hulley,G.C.,Malakar,N.,Islam,T.,Freepartner,R,(2017),NASA’sMODISandVIIRSLandSurfaceTemperatureandEmissivityProducts:AConsistentandHighQualityEarthSystemDataRecord,IEEETGRS,DOI:10.1109/JSTARS.2017.2779330.

• Islam,T.,G.C.Hulley,N.Malakar,R.Radocinski,S.Hook,P.Guillevic (2016),Aphysics-basedalgorithmforthesimultaneousretrievaloflandsurfacetemperatureandemissivityfromVIIRSthermalinfrareddata,IEEETransactionsonGeoscienceandRemoteSensing,55,563-576

• UserguideandATBDavailableat:https://lpvs.gsfc.nasa.gov/LSTE/LSTE_home.html

StatusofVIIRSLST&E

20

StatusofVIIRSVITimeSeries

VIIRSVIProductSuitejustreleasedVIIRSVIProductCollection1Collection 1: (Released in 2018)

• ConsistentwithMODISproductsuite(16-dayandmonthly500m,1km,andCMG)

StatusandUpdates:• SolidQA-drivencompositingapproachadoptedfromthe

MODISC5ScienceAlgorithmandbasedondailyinputs• ThefullVIIRStimeseriesisregularlycomparedtoMODISAqua

(Terra)• TimeseriesfullycharacterizedwithexplicitMODIST/A

continuitytransferfunctions

KnownIssues:• Algorithm/Productsuiteorphanedandnolonger

supported/funded(postA.37)whilethePI/SCFcontinuestosupporttheAlgorithm&timeseriesduetoitscriticalvaluetothesciencecommunity(therearethousandsofusersandtensofglobalagenciesandprivatecompaniesthatdependonoureffortandcontinuedsupport).

RecentPublications:• Jarchow,C.J.,Didan,K.,Barreto-Muñoz,A.,Nagler,P.L.,&Glenn,

E.P.(2018).ApplicationandComparisonoftheMODIS-DerivedEnhancedVegetationIndextoVIIRS,Landsat5TMandLandsat8OLIPlatforms:ACaseStudyintheAridColoradoRiverDelta,Mexico. Sensors, 18(5),1546.

• EL-Vilaly,M.A.S.,Didan,K.,Marsh,S.E.,Crimmins,M.A.,&Munoz,A.B.(2018).CharacterizingDroughtEffectsonVegetationProductivityintheFourCornersRegionoftheUSSouthwest. Sustainability, 10(5),1643.

AquaandS-NPPVIIRSNDVI/EVITimeSeriesOpportunisticValidationwithNEONData.StrongVIIRSPerformance

ValidationEfforts..

Committee on Earth Observation Satellites

Working Group on Calibration and ValidationLand Product Validation (LPV)

Miguel Román (NASA Goddard)Jaime Nickeson (NASA Goddard)Laura Duncanson (Univ. Maryland)Zhuosen Wang (Univ. Maryland)

CARB-19:Landproductvalidationlistingandframework

Q42017 SummarizecurrentlistofvalidatedlanddataproductsrelevanttoCarbonStrategy.

Documentvalidationframeworkandprotocols

Provideguidanceforonlineplatformforintercomparisonofterrestrialcarbonproducts.

WGCV

2017-2019 Work Plan

3.2ProgressontheimplementationoftheCEOSStrategyforCarbonObservationsfromSpace

CARB-19: Global Surface Albedo Product validation protocol (draft released!)

Authors: Z. Wang, C. Schaaf, A. Lattanzio, D. Carrer, I. Grant, M. Román, F. Camacho, Y. Yu.

CEOS-LPV Plenary (Frascati, May, 2018)

CARB-19: CEOS LPV Super Sitesendorsed at CEOS-WGCV-43

CEOS-LPVSuperSitepageaddedtoLPVwebsite:

• Definition:Well-characterized(canopystructureandbio-geophysicalvariables)sitefollowingwell-establishedprotocolsusefulforthevalidationofsatellitelandproductsandforradiativetransfermodelingapproaches.Activelongtermoperations(fundingandinfrastructuresupport).

• Interactivemapofsites,colorcodedbynetwork(10networksincluded).Clickonsiterendersapop-upwindowwithsitename,landcovertype,andalinktositenetworkpage.

• Pageincludesalinktospreadsheetofsitedetails.

• Linktoselectionreport: https://goo.gl/Mw7RMz).

• ObjectivesiteselectionprocesshelpsinformCEOSAgencyfieldexperiments(e.g.,ESAFiducial ReferenceMeasurementframework:https://earth.esa.int/web/sppa/activities/frm).

Crosssensorsvalidation

Landsat8

MODIS

VIIRS

VIPLab Drone

NEONAOP

a)Directsensorvalidation

b)CalibrationusingNEONsimulateddatasets

Convolution

NDVIMODISsimulated

NDVIVIIRSsimulatedNDVILandsat8simulated

Convolutionisprocessingintensive.Fornowonlysmallwindowsusingonlineapplication.

Outputcontainsensorbands+NDVI/EVI2/EVI

28

MALIBUMultiAngLeImagingBrdfUnmannedaerialsystem

https://viirsland.gsfc.nasa.gov/Campaigns.html

Working

Group

onCa

libration

and

Validation

Summary:JointGSFC618/619efforttodevelopmulti-angularreferencedatasetsfortheassessmentofBOAreflectance-basedproducts(e.g.,BRDF,albedo,NBAR,VI,PRI,LAI/FPAR,snowcover,andphenologymetrics).

Benefits:Acosteffective($300× FlightHour),exempted(FAA-S.333&TCAN)platform,thatfollowsCEOS-WGCVgoodpracticeprotocols.

MALIBUSuperswiftDeploymentatTableMountain,CO

MALIBU’s‘abilitys’ (KeyPerformanceCharacteristics)Working

Group

onCa

libration

and

Validation TraceabilityMobility

AdaptabilityScalability

CLARREOProjectIntegratingSphere

Flat-fieldcharacterizationandapplicationoftraceableradiometryfromacalibratedASDthatservedasaspheremonitor(B5-W090).

ASD