NASA Technical Reports Server (NTRS) 20120013693: Thermal Infrared Radiometric Calibration of the Entire Landsat 4, 5, and 7 Archive (1982-2010)

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RSE-08186;NoofPages9
RemoteSensingofEnvironmentxxx(2012)xxx–xxx
ContentslistsavailableatSciVerseScienceDirect
Remote Sensing of Environment
journal homepage: www.elsevier.com/locate/rse
Thermal infrared radiometric calibration of the entire Landsat 4, 5, and
7 archive (1982–2010)
John R. Schott a,⁎, Simon J. Hook b, Julia A. Barsi c, Brian L. Markham d, Jonathan Miller e,
Francis P. Padula f, Nina G. Raqueno a
aRochesterInstituteofTechnology,UnitedStates
bJetPropulsionLab,CaliforniaInstituteofTechnology,NASA,UnitedStates
cScienceSystemsandApplications,Inc.,NASA,UnitedStates
dGFSC,NASA,UnitedStates
eUSAF,UnitedStates
fScienceApplicationsInternationalCorporation,UnitedStates
a r t i c l e i n f o a b s t r a c t
Articlehistory: Landsat'scontinuingrecordofthethermalstateoftheearth'ssurfacerepresentstheonlylongterm(1982
Received11March2011 tothepresent)globalrecordwithspatialscalesappropriateforhumanscalestudies(i.e.,tensofmeters).
Receivedinrevisedform20June2011 Temperaturedrivesmanyofthephysicalandbiologicalprocessesthatimpacttheglobalandlocalenviron-
Accepted18July2011
ment.Asourknowledgeof,andinterestin,theroleoftemperatureontheseprocesseshavegrown,the
Availableonlinexxxx
valueofLandsatdatatomonitortrendsandprocesshasalsogrown.ThevalueoftheLandsatthermaldata
archivewillcontinuetogrowaswedevelopmoreeffectivewaystostudythelongtermprocessesandtrends
Keywords:
affectingtheplanet.However,inordertotakeproperadvantageofthethermaldata,weneedtobeable
Infrared
Radiometriccalibration to convert the data to surface temperatures. A critical step in this process is to have the entire archive
Landsat completelyandconsistentlycalibratedintoabsoluteradiancesothatitcanbeatmosphericallycompensated
Residualuncertainty tosurfaceleavingradianceandthentosurfaceradiometrictemperature.Thispaperaddressesthemethods
andproceduresthathavebeenusedtoperformtheradiometriccalibrationoftheearliestsizablethermal
datasetinthearchive(Landsat4data).Thecompletionofthiseffortalongwiththeupdatedcalibrationof
theearlier(1985–1999)Landsat5data,alsoreportedhere,concludesacomprehensivecalibrationofthe
Landsatthermalarchiveofdatafrom1982tothepresent.
©2012ElsevierInc.Allrightsreserved.
1.Introductionandsummary thermaldataarchivewillcontinuetogrowaswedevelopmoreeffec-
tivewaystostudythelongtermprocessesandtrendsaffectingthe
Landsat'scontinuingrecordofthethermalstateoftheearth'ssur- planet. However, in order to take proper advantage of the thermal
facerepresentstheonlylongterm(1982tothepresent)globalrecord data,weneedtobeabletoconvertthedatatosurfacetemperatures.
withspatialscalesappropriateforhumanscalestudies(i.e.,tensof Acriticalstepinthisprocessistohavetheentirearchivecompletely
meters). Note, AVHRR data span from 1978 to the present and and consistently calibrated into absolute radiance so that it can be
Modisdataspanfrom2000tothepresentwith1kmpixels.Temper- atmospherically compensated to surface leaving radiance and then
aturedrivesmanyofthephysicalandbiologicalprocessesthatimpact to temperature. This paper addresses the methods and procedures
theglobalandlocalenvironment.Asourknowledgeof,andinterest thathavebeenusedtoperformtheradiometriccalibrationoftheear-
in,theroleoftemperatureontheseprocesseshasgrown,thevalue liestsizablethermaldatasetinthearchive(Landsat4data).Thecom-
ofLandsatdatatomonitortrendsandprocesshasalsogrown.Areas pletionofthiseffortalongwiththeupdatedcalibrationoftheearlier
ofstudythatuseLandsatderivedthermaldataincludelakehydrody- (1985–1999)Landsat5data,alsoreportedhere,concludesacompre-
namicprocess(Schott,1986;Schottetal.,2001),monitoringevapo- hensivecalibrationoftheLandsatthermalarchiveofdatafrom1982
transpiration(Allenetal.,2008;Anderson&Kustas,2008),regional tothepresent.Thedifferentmethodologiesusedtoaccomplish the
water resources (Thenkabail et al., 2009, 2010), and the impact of entire calibration/validation update are reviewed in Section 2. The
localclimatetrends(Schneideretal.,2009).ThevalueoftheLandsat newresultsforLandsat4andearlyLandsat5aswellasthepreviously
reportedresultsforLandsats5and7(Barsietal.,2003;Hooketal.,
2004)areincludedinSection3.Inparticular,thissectionincludesa
⁎ Correspondingauthor.Tel.:[phone];fax:[phone]. discussionofthesmallresidualuncertaintyinthedataarchiveasso-
E-mailaddress:[email protected](J.R.Schott). ciated with each data set. This uncertainty in the collective archive
0034-4257/$–seefrontmatter©2012ElsevierInc.Allrightsreserved.
doi:10.1016/j.rse.2011.07.022
Pleasecitethisarticleas:Schott,J.R.,etal.,ThermalinfraredradiometriccalibrationoftheentireLandsat4,5,and7archive(1982–2010),
RemoteSensingofEnvironment(2012),doi:10.1016/j.rse.2011.07.022
2 J.R.Schottetal./RemoteSensingofEnvironmentxxx(2012)xxx–xxx
of approximately 0.6K means that, with good knowledge of the whereDN andDN aretheaveragedigitalnumberfromasampleof
BB S
atmosphereandemissivity,surfacetemperaturescanberetrievedto imagedatatakenfromtheblackbodyandtheshutterrespectivelyand
^ ^
better than 0.7K (one sigma) using standard analytical approaches. LBBλandLSλarethespectralradianceinthepassbandassociatedwith
Theseresultsmeanthatforthefirsttimeuserscanaccessandanalyze ablackbodyatthetemperatureoftheblackbody(BB)andshutter(S)
theentire30yearrecordwithconfidenceintheradiometricintegrity respectively,i.e.
ofthethermaldata.
2.Background L^BBλ¼∫L∫BBRλðRλðÞλdÞλdλ ð2Þ
ThissectionwillintroducetheLandsatsensorsfromthethermal whereLBBλisthespectralradiancefromablackbodyattemperature
infrared perspective and then briefly review the approaches that BB [W m−2 sr−1 μm−1] and R(λ) is the relative spectral response
have been used over time for vicarious radiometric calibration of ofthesensorwithwavelengthλ.
theLandsatthermalinstruments. Theactualsensoroutput(DN)canthenberelatedtotheradiance
fromthescene(Lλ)as
2.1.Instruments
DN¼gfðgiLλþbiÞþbf ð3Þ
Landsat3wasthefirstLandsatsatellitetoincludeathermalsens-
ingcapability.However,thethermalsensorfailedquiteearlyinthe wherebiisaninternalbiaslevelrelatedtotheshutterradiance(i.e.
missionandnosignificantefforthasyetbeenexpendedtocharacter- shuttertemperature)andgfandbfaregainandbiastermsassociated
ize its post launch performance. Therefore,this paper will focus on withmultiplicativeandadditiveeffectsnotcapturedbytheinternal
the thermal sensors on the Landsat 4 Thematic Mapper (TM4), the calibrationprocess(e.g.transmissionlossesfromtheopticsforward
Landsat5ThematicMapper(TM5)andtheLandsat7EnhancedThe- oftheshutterandadditiveradiancefromtheopticsforwardofthe
maticMapperplus(ETM+).Fromthe thermal infraredperspective shutter).Notethattheactualequationsusedinthesoftwareforthe
these three instruments were nearly identical with the exception different instruments vary slightly from instrument to instrument
being that ETM+ had eight thermal detectors instead of the 4 on butcanbegeneralizedtotheformshowninEq.(3).
the TM instruments resulting in a 60m ground instantaneous field Values for the remaining calibration coefficients (i.e. bi, gf and bf
of view (GIFOV) instead of 120m for the TM instruments. Each in this representation) were determined from pre-launch laboratory
instrumenthadasinglespectralbandnominallycoveringthe10.5– calibrationwithexternalradiancesources.Giventhesecalibrationcoef-
12.5μmspectralwindow(seeFig.1)withtwoeightbitgainsettings. ficients,thesensorreachingradiancecanbecalculatedfromtherecorded
Fig.2showsagenericoptomechanicalschematicoftheinstruments DNforeachpixelbyinversionofEq.(3).Someofthesecoefficientsare
highlightingtheelementsrelevanttothethermalband.Inparticular, dependent on the operating temperatures of the forward optics. In
notethatontheTMinstrument4detectorsaresweptacrossthefield practice,coefficientsappropriatefortheexpectedoperatingtempera-
ofview(FOV)forming4120mlinesofdatapersweepofthescan tures were calculated empirically pre-launch, however, no trusted
mirror and that on ETM+ 8 detectors sweep 8 60m lines of data. fore-opticcalibrationmodelwasdevelopedwhichwouldallowadjust-
Alsonotethatasthescanmirroristurningaround,acalibrationshut- ment of the coefficients based on the recorded temperatures of the
terisinsertedintothelineofsight.Theshutterhasahighemissivity opticalelements.Thus,when significantchanges totheinstrument's
surface with a monitored temperature and a mirror that reflects a operating temperatures occur (either planned or unplanned), or if
cavityblackbodyintothelineofsight.Thus,astheshutterisswept thereisdegradationoftheforwardoptics,newvaluesforthecalibration
into the line of sight, the detectors “see” first the known radiance coefficientsmustbedeterminedandappliedtothecalibrationequation
fromtheshutterandthentheknownradiancefromtheblackbody. (Eq. 3) to maintain the calibration of the data. Because there is no
This provides a two point calibration at the beginning and end of onboardsystemtoadequatelymonitoranyradiometricchangesinthe
eachlineofdata.Thesetwopointsareusedtocalculatetheinternal forward optics, vicarious calibration procedures have been regularly
gain(g)accordingto usedtoverifythestabilityofthecalibrationafterlaunchandthen(at
i
leastsince1999)tomonitorthecalibrationonorbit.
DN −DN 2.2.Vicariouscalibrationapproaches
gi¼ L^BBBλB−L^SλS ð1Þ
Fourdifferentvicariouscalibrationtechniqueshavebeenusedto
supportthecalibrationoftheLandsatthermalbands.Eachofthese
willbeintroducedinthissection.Allofthemethodsusewaterasa
target. Water is an ideal target because of its high thermal inertia,
highemissivityandasaliquiditishardtomaintainthermalgradi-
ents, so large regions of uniform temperature are common (Schott
etal.,2004;Tonokaetal.,2005).Allofthemethodsalsousetheradi-
ationpropagationcodeMODTRAN(Berketal.,1999)topropagatethe
radiationtothesensor.Thegoverningradiometryequationsandthe
useofMODTRANwillthereforebeintroducedinSection2.2.1before
thediscussionofthedifferentmeasurementtechniques.
2.2.1.Atmosphericpropagation
The governing equation for radiation propagation to the sensor
canbeexpressedas
L^λ¼∫½ðεðλÞLTλþð1−ε∫ðλRðÞλÞLÞddλλÞτðλÞþLuλ(cid:2)RðλÞdλ≅L^obsλτþL^uλ ð4Þ
Fig.1.PlotsoftherelativespectralresponseoftheTM4,TM5andETM+instruments.
Pleasecitethisarticleas:Schott,J.R.,etal.,ThermalinfraredradiometriccalibrationoftheentireLandsat4,5,and7archive(1982–2010),
RemoteSensingofEnvironment(2012),doi:10.1016/j.rse.2011.07.022
J.R.Schottetal./RemoteSensingofEnvironmentxxx(2012)xxx–xxx 3
Fig.2.OptomechanicalschematicofTMandETM+instrumentsshowingthethermalfeatures.
whereεistheemissivityofthetarget,LTλisthespectralblackbodyra- 2.2.2.Underflightapproach
dianceassociatedwithatargetattemperatureT,Ldλisthespectral SchottandVolchok(1985)describethemethodthatwasusedin
downwelled radiance, Luλ is thespectral upwelledradiance, τ(λ) is themid1980sinanattempttocalibrateTM4andTM5immediately
thetransmissionfromthetargettothesensorandingeneralallthe after they were launched. The method involved flying a well-
termsareafunctionofwavelength(λ).Inpracticetheemissivityof calibratedinfraredlinescannerunderneaththespacecraftandimag-
waterisessentiallyconstantovertheLandsatbandpassat approxi- ing water targets simultaneously (i.e. ±30min) with the Landsat
mately 0.986. In addition, the emissivity is independent of water acquisition(seeFig.3a).Theinfraredlinescannerwasspectrallyfil-
condition and surface roughness for the Landsat fields of view tered to match the Landsat spectral response and calibrated such
(Schottetal.,2004).NotethatLobsλistheeffectivespectralradiance thattheeffectivespectralradiancecouldbecalculatedforanypixel
^
intheLandsatbandobservedatthegroundorattheaircraftaltitude intheimage.ThisyieldsvaluesforLobsλwhichcanbepropagatedto
for the aircraft underflight calibration approach, τ is the effective the spacecraft using MODTRAN and the righthand side of Eq. (4).
transmission over the Landsat passband from the observation loca-
tiontothesensorandLuλistheeffectivespectralupwelledradiance
inthepassbandforthepathbetweentheobservationandthesensor.
Theseeffectivepassbandvaluesareusedwhensurfaceoraerialradio-
metricmeasurementsorestimatesofthetargetareavailable.
MODTRANcanbeusedtosolveforallofthetermsinEq.(4)if
theatmospherehasbeencharacterizedandthesurfacetemperature
andemissivityaresupplied.Inpractice,fortheRochesterInstitute
of Technology (RIT) analysis (Sections 2.2.3 and 2.2.5), the atmo-
sphereischaracterizedusingtheclosestavailableradiosondedata
typically adjusted in the boundary layer (0 to approximately
0.5km)forobservedsurfaceconditions(temperatureandrelative
humidity). This surface correction accounts for variation in the
lowest layers of the atmosphere that may exist because of spatial
andtemporaloffsetsbetweenthetargetlocationandsampletime
andtheradiosonde/upper-air-samplinglocationandtime(Padula,
et al., 2011). The Jet Propulsion Laboratory (JPL) analysis uses an
atmospheric profile from the nearest atmospheric reanalysis grid
point(seeSection2.2.4).
In order to take advantage of Eq. (4) to predict the expected
sensorreachingradiancewemusteitherknowthetemperatureand
emissivityofthetarget(leftformofEq.4)ortheradiancefromthe
target (right form of Eq. 4). In the next subsections we will briefly
Fig. 3. Illustration of methods used to measure surface temperature/radiance. a.
reviewfourmethodsthathavebeenusedtomeasurethetempera-
Aircraftapproach—Section2.2.2,b.surfacekinetictemperatureapproach—Section2.2.3,
ture or radiance (recall that emissivity is known and constant for c.surfacetemperatureapproachusingradiometers—Section2.2.4andd.NOAAbuoy
theLandsatobservationconditionsoverwaterbodies). approach—Section2.2.5.
Pleasecitethisarticleas:Schott,J.R.,etal.,ThermalinfraredradiometriccalibrationoftheentireLandsat4,5,and7archive(1982–2010),
RemoteSensingofEnvironment(2012),doi:10.1016/j.rse.2011.07.022
4 J.R.Schottetal./RemoteSensingofEnvironmentxxx(2012)xxx–xxx
Becausetheaircraftwastypicallyflownat3–5kmabovegroundlevel theradiometersarenotfilteredtomatchtheLandsatspectralpass-
the observed radiance incorporated the largest and most variable band, the surface temperature corrected for the cool skin effect is
effectsduetotheatmosphere,therebyreducinganyerrorsduetoless computedusingacombinationoftheobservedradiometrictemper-
thanperfectatmosphericpropagation.MODTRANwasonlyusedtocor- ature, the near surface contact temperature and the downwelled
rect for the atmosphere above the aircraft. Any small error in these radiancecomputedfromMODTRAN(Hooketal.,2003;Hooketal.,
smallcorrectionsresultsinverysmallerrorsinthepredictedsensor 2004). The data are acquired every 2 to 5min and transmitted to
reachingradiance. JPLforprocessing.Theoutputfromtheprocessingisanestimateof
Inaddition,becausetheaerialsystemhasamuchsmallerground thesurfacekinetictemperaturewhichcanbecombinedwiththesur-
sample distance (GSD) than the satellite, many pixels of a uniform faceemissivityandMODTRANgeneratedradiativetransferparameters
^
regionof thewatercanbeaveragedtoestimate Lobsλ.This reduces togeneratethepredictedsensorreachingradiance(seeEq.4).The
noise in the estimate by the square root of the number of samples atmospheric profile data used for input to MODTRAN come from
^
(typically25to100)resultinginverypreciseestimatesofLobsλ.The the nearest National Center for Environmental Prediction (NCEP)
uncertaintyofthismethodistypicallylimitedonlybythecalibration reanalysispointinterpolatedtotheLandsatacquisitiontime(Hook
uncertaintyoftheaerialinstrument(seeSection3.4). etal.,2007).
Theobviousdrawbackstothisapproacharethecostandlogistical Regrettablynoneofthemethodsdiscussedsofarcouldbeusedto
difficulties associated with acquiring significant amounts of aerial assess temporal gaps in the calibration of the Landsat instruments
datacoincidentwiththespacecraftaswellasdifficultiesassociated duringaperiodwhenNASAwasnotfundingLandsatthermalband
with maintaining the calibration knowledge of the airborne instru- vicarious calibration programs (1985–1999). Thus, a method was
ment. On the positive side, one can often fly over different water neededtofillthislongknowledgegap.
regionswithsomerangeoftemperaturesandtherebyobtainseveral
calibration points from a single successful flight. Nevertheless, this
method is difficult to justify operationally and so other methods 2.2.5.Estimationofsurfacetemperaturefromsubsurfacemeasurements
mustbeconsidered. byNOAAbuoys
The National Oceanic and Atmospheric Administration (NOAA)
2.2.3.Surfacekinetictemperaturemeasurementapproach operates a fleet of moored buoys in U.S. coastal waters and in the
Toaugment,orinlieuoftheaerialapproach,surfacekinetictem- Great Lakes. These buoys record hourly subsurface temperatures
peraturemeasurementscanbeemployed.Toavoidnearsurfacegra- (0.6mor1.5m)aswellasweatherdataandarchiveitintheNational
dients this approach should be limited to well mixed waters and DataBuoyCenter(NDBC).The archiveincludes buoyrecordsspan-
measurements should be taken very close to the surface. RIT uses ningtheentireperiodofinterest(1982–present).Temperaturefrom
thermistorsattachedundersmallblocksofStyrofoamthatarefloated buoys has been used previously to validate atmospheric retrieval
onthesurfaceonthewindwardsideoftheboat(seeFig.3b).Thetar- algorithms and instrument calibration for the Advanced Very High
getshaveusuallybeenthewatersofLakeErieorLakeOntariowhich Resolution Radiometer (AVHRR) (Emery et al., 2001; Walton et al.,
haveverylongfetch(i.e.alongstretchofopenwaterintheupwind 1998). Padula and Schott (2010) describe an improved technique
direction) and are rarely still. This method has been extensively for estimation of surface temperature from the subsurface buoy
used by RIT since 2001 to support calibration of ETM+ and TM5 temperatures.Themethodutilizesthe24hoftemperaturemeasure-
(Barsietal.,2003).Thetemperaturesobtainedbythismethodalong mentsbeforethesatelliteoverpassalongwithsurfacemeteorological
with the emissivity of water and the radiative transfer values from datatocomputesurfacetemperaturefromthesubsurfacevalues.The
MODTRAN allow the use of Eq. (4) to predict the sensor reaching method accounts for the diurnal temperature cycle, the temporal
radiance. While this method has a slightly higher error associated phase shift in the diurnal cycle with depth, thermal gradients with
witheachindividualmeasurement(seeSection3.4)thantheaerial depththatareafunctionofwindspeedandfinallythecoolskineffect.
approach,thelargernumberofpointsthatcanbeacquiredtendsto Thederivedsurfacetemperaturewasthenusedalongwithemissivity
compensateintheoverallinstrumentcalibrationuncertainty. values,localweatherdataandradiosondedataasinputtoMODTRAN
A limitation of the surface temperature approach is that the topredictsensorreachingradianceasdescribedinEq.(4).Bycompar-
temperaturemeasuredisveryslightlybelowthesurfaceandthein- ison to well-calibrated ETM+ and TM5 data post 1999, the sensor
frared sensors measure the true surface temperature i.e., the skin reachingradiancevaluespredictedbythismethodwereshowntobe
temperature.Undermostcircumstancewhencalibrationdatawould ingoodagreement(meanbiasdifferenceslessthan0.2K)withthepre-
be acquired (clear skies), radiational surface (top microns) cooling dictions made using the JPL and RIT surface temperature/radiance
lowersthesurfacetemperatureslightly(uptoafewtenthsKelvin) methodsdescribedabove.Therefore,thistechniquewasthesourceof
whencomparedtothetemperatureimmediatelybelowthesurface datafortheperiod1982–1999andisthebasisfortheTM4andearly
(fewmm).Generallyskintemperatureiscoolerforwellmixedwa- TM5calibrationresults.
ters,however,ifthewaterisstillthentheskintemperaturecanbe
warmerthanthetemperatureimmediatelybelowthesurface.Surface
radiometerscanbeusedtoavoidthislimitation. 3.Results
2.2.4.Surfacetemperaturemeasurementapproachusingfieldradiometers Thissectionreviewshowthemethodsdescribedintheprevious
Since 1999, NASA's Jet Propulsion Lab (JPL) has operated four sectionhavebeenusedtocalibratethecompletearchiveofTMand
instrumentedbuoysinLakeTahoeCA/NV,andsince2008asimilarly ETM+thermaldata.Theformationofthecalibrationteam,thatled
instrumentedplatformintheSaltonSeaCA.Note,theSaltonSeasite to the effort to assess and update the calibration of the archive,
wasaddedtoallowacquisitionofhighertemperature/radiancetar- beganwiththelaunchofLandsat7.Therefore,wehadthediscussion
getstoallowbetterassessmentofsmallgainerrorsinthesatellites beginthereandworkbackintimethroughtheinstruments.
being calibrated. The instrumentation on each platform includes Because Padula and Schott (2010) and Barsi et al. (2003) show
nearsurfacecontactthermistors,nearnadirviewingcalibratedradi- thatallthemethodsintroducedintheprevioussectionpredictsensor
ometers and weather stations. The JPL suite of field sensors has reaching radiance values that are in agreement with each other to
been used to perform thermal calibration assessment of a number within the errors in the methodology (see Section 3.4), all of the
ofsensorsincludingMODISandASTERandthereforeusesradiome- methods will be considered as trusted unbiased sources of sensor
terswithawidepassband(Hooketal.,2003,2005,2007).Because reachingradiance.
Pleasecitethisarticleas:Schott,J.R.,etal.,ThermalinfraredradiometriccalibrationoftheentireLandsat4,5,and7archive(1982–2010),
RemoteSensingofEnvironment(2012),doi:10.1016/j.rse.2011.07.022
J.R.Schottetal./RemoteSensingofEnvironmentxxx(2012)xxx–xxx 5
3.1.Landsat7—ETM+ 3.2.LandsatTM5results
AtlaunchRITandJPLwereindependentlychargedwithassessing SchottandVolchok(1985)andSchottetal.(1987),usingtheRIT
thethermalcalibrationofLandsat7.RITusedaerialunderflightsand aerialtechnique,obtainedasmallnumberofTM5calibrationpoints
surfacetemperaturemeasurementsontheGreatLakes,andJPLused shortly after launch in 1985. They reported a small bias of 0.58K,
the automated sites at Lake Tahoe and later at the Salton Sea. whichwaswithintheapproximately1Kuncertaintyofthevicarious
Bothteamsquicklyidentifiedasignificantconstantbiasinthedata instrumentationavailableintheearly1980s,andnoadjustmentwas
of 3.1 (W m−2 sr−1 μm−1) or 0.31K at 300K, where bias will be recommended. There was no significant effort to evaluate the TM5
expressedasradianceobservedbytheinstrumentminusatsensorra- calibrationfrom1985untiltheRITandJPLteamsweretaskedtoin-
diancepredictedfromthegroundtruthmeasurements.Thebiaswas vestigateitinapproximately2001.
calculatedastheweightedaverageofalloftheindividualestimates Byusingitsautomatedsites,theJPLteamwasabletogobackto
availableatthetime.Theweightswereproportionaltooneoverthe 1999whentheywereinitialized.In2006,basedonceagainonthecom-
standard error about the mean bias estimate obtained by each of binedJPLautomatedsitedataandRITsurfacetemperaturedata,itwas
the teams. The bias correction was implemented by USGS EROS on determinedthatasmallbiaserrorof−0.092[W m−2sr−1 μm−1]or
12/20/2000,andlikeallothercorrectionsdiscussedhereitwasap- −0.68Kat300Kwaspresentin alloftheavailabledatafrom1999
pliedtoallimpacteddatasuchthatanydataprocessedafter12/20/ on.On4/1/2007USGS,basedontherecommendationoftheLandsat
2000 should be unbiased, including all data acquired before that calibrationteam,implementedacorrectiontothedataprocessingto
date.Notethisbiaswaseventuallydeterminedtobetheresultofan removethebiasfromalldataprocessedafterthatdateapplicableto
error in coefficients in the processing system and not due to any imageryacquiredafter 4/1/1999. Because noRITorJPLcalibration
changestotheinstrumentonlaunch. datawereavailablefortheperiod1985–1999itwasnotclearhow,
The calibration team continued to monitor the ETM+ thermal orif,tocorrectdatapriortoApril1999sonochangewasmadeto
performanceaddingmoredataeachyearwithanemphasisonhigh theearlierdataatthattime.
andlowtemperaturevaluesasthelargeamountofdatabegantoindi- O'Donnelletal.(2002)describeanefforttoevaluatethe(1985–1999)
catethataslighterroringainhadbeenpresentsincelaunch.Because calibrationgapusingcoldwatertemperatures,fromthecenterofthe
theerrorwassmallitcouldonlybeidentifiedwithconfidencewhen GreatLakesinwinter,asgroundtruth.Theassessmentindicatedthat
significantamountsofwarmandcolddatawereaddedtothedataset. therewasnodiscernablecalibrationerroroverthe1985–1999period.
In 2009 with data ranging from 6.3 to 9.6 [W m−2 sr−1 μm−1] or However,thiswaslimitedbyuncertaintyintheknowledgeofthelake
275to305Kitwasdeterminedthata5.8%erroringainexisted.The temperatures to 1 to 2K uncertainty in apparent temperature at the
gainerrorisexpressedas sensor.
Intheearly2000sRIThadbeguntoinvestigatewhetherdatafrom
! theNOAAbuoyscouldbeusedtoaccuratelydeterminesurfacetem-
Sg¼ 1−ΔΔL^L^Saλtλ ⋅100 ð5Þ upseirnagtudrea.taPafdroumla aandfewSchboutoty(s20(1G0re)adteLsacrkiebseaanpdaiorffoftheexpDeerlimmaernvtas
Peninsula) propagated to sensor reaching radiance. They first com-
paredthepredictedradiancetothecalibratedradianceobservedby
whereΔL^Sat=ΔL^λistheslopeofthesatelliteobservedspectralradiance theETM+sensorfor32pointsfrom2000to2007.Thegainandbias
versus thepredictedradiance values for all ofthe calibration points. valuesestimatedfromthebuoydata(nearunityandzero,respectively,
Fig.4showsthecalibrationdataforthetwoteamsthatindicatedthe asexpected)wereshowntobestatisticallythesameasthevaluesesti-
need for a small gain correction. Note that for most of the radiance matedusingthe acceptedRITand JPL measurementtechniques.The
rangethecorrectioncausesonlysmallchangesintemperature.Howev- second experiment compared the buoy-based calibration results for
er,forhottargets(300K)thechangecouldbeaslargeas0.8K.Thegain TM5totheresultsobtainedbythesurfacetemperatureapproachfor
correction wasimplemented in the USGS processing system on 1/1/ thetimeperiodafterfieldcampaignshadresumed(1999).Theresults
2010. weresimilarto theETM+results leading to theconclusion thatthe
BasedontheearlysuccessoftheETM+vicariouscalibrationcam- NOAA buoy archive could be used to provide a source of “ground
paigns, NASA tasked the calibration team to assess the radiometric truth”forcalibrationofthedataduringthe1985–1999gap.
calibrationoftheTM5instrument. PadulaandSchott(2010)reportthatusing7buoys,198calibra-
tionpointswereobtainedspanningtheperiod1984–2007.Thesere-
sultssuggestedthatasmallbutstatisticallysignificantgainerrorhad
been present in the data since launch and a bias shift of approxi-
mately −0.69K occurred sometime in the late nineties (consistent
withtheresultsreportedaboveforthe1999+data).Byaddingaddi-
tionalbuoys,moredatawereaddedinanattempttobetterestimate
the date when the bias change occurred (see Fig. 5). In addition,
significant amounts of new TM5 data from all the methodologies
werecombinedtoestimatethecalibrationerrorfortheentireTM5
dataset.Usingthecompositedatasetitwasdeterminedthatabias
shift of −0.11 [W m−2 sr−1 μm−1] occurred in the early part of
1997(nosourcefortheshiftinbiashasbeendetermined)andthat
a small gain error of 5.0% was present in all of the TM5 data. This
smalldeviationfromaunityslopeinthepredictedtoobservedradi-
anceplotshadbeensuggestedbytheearlierdata,however,theaddi-
tion of a larger volume and range of data increased the statistical
confidencetoapointwherecorrectionwaswarranted.Basedonthe
recommendationofthecalibrationteam,USGSimplementedchanges
totheTM5dataprocessingtoimplementthesecalibrationupdates
Fig.4.PlotofpredictedversusobservedatsensorradianceforETM+showingtheneed
forasmallgaincorrection. fordataprocessedafter4/1/2010.
Pleasecitethisarticleas:Schott,J.R.,etal.,ThermalinfraredradiometriccalibrationoftheentireLandsat4,5,and7archive(1982–2010),
RemoteSensingofEnvironment(2012),doi:10.1016/j.rse.2011.07.022
6 J.R.Schottetal./RemoteSensingofEnvironmentxxx(2012)xxx–xxx
Fig.5.TM5temporalplotshowingbiasestimatesbydateaswellasthemeanbiaslinefortheperiodspreandpost1/1/1997.
3.3.LandsatTM4results corrector(SLC)).Thisdiscussionleadsustoanassessmentoftheun-
certaintyremaininginthecalibrationofthedatanowcomingfrom
TheTM4instrumentwaslaunchedin1982andoperatedfornearly theUSGSarchive.
ayearbeforebeingputinon-orbitstoragebecauseofsolararrayand
direct downlink failures. It was returned to operation three years 3.4.Residualuncertaintyinthecalibrateddatabase
later, using the Tracking and Data Relay Satellite System (TDRSS) to
downlinkdata,andsuccessfullyoperatedforanother6years.During Byimplementingthecalibrationadjustmentsdescribedabove,all
itsshortearlylifenorigorousvalidationofthecalibrationwasaccom- knownsystematicerrorsassociatedwiththeLandsatthermalbands
plishednorwasavalidationattemptedwhenitwasreturnedtoopera- shouldbereducedtoinsignificantlevelscomparedtotheprecision
tion. Based on the successful use of the NOAA buoys in filling the errorsassociatedwiththecalibrationproceduresandtheinstrument
calibrationgapintheTM5calibrationhistory,asimilareffortwasun- noise.Thus,intheorytheoveralluncertaintyintheradiancevalues
dertaken for TM4. The problem with the TM4 database was that it generatedfromthedatainthearchivecanbeexpressedas
wasmoresparselypopulatedbecauseoftheshortperiodofinitialuse (cid:2)
andsomewhatlimiteduseovertheU.S.afterthestorageperiod. S ¼ S2þS2(cid:2)12 ð6Þ
Todealwiththisissue,asignificantlylargersetofbuoysandcor- L p i
responding radiosonde sites were used to find simultaneous buoy,
radiosonde and clear TM4 image dates. In all, 17 buoy sites were whereS istheuncertaintyinthe“calibrated”data,S istheuncer-
L p
used in the TM4 calibration resulting in 9 calibration points from taintyintheradiancepredictedatthesensorthroughthevariouscal-
1982to1983and19pointsfrom1987to1992.Theresultsshowed ibration procedures (assumed to be unbiased (i.e. accurate) at this
that there was no significant bias error apparent in the early TM4 point)andS isthenoiseintheinstrumentmeasurements(note:allun-
i
databutthatalargeconsistentbiasof−0.43[W m−2 sr−1 μm−1] certaintiesareexpressedas1standarddeviationvalues).Assumingall
or−3.3Kat300Kwaspresentpoststorage(seeFig.6).
Thepoststoragedatashowednosignificantgainerror(lessthan
0.5%) so all the error was attributed to and corrected with a bias
adjustmenttobeimplementedin2011andappliedtoallTM4post
storage data processed after that date. In analyzing the TM4 data
thevariabilityofthebiasestimatesprestoragewasobservedtobe
significantlylarger(factoroftwo)thanpoststorageandalsosignifi-
cantly larger than the variability in the bias estimates observed for
TM5orETM+.Inanefforttounderstand/explainthesourceofthis
variabilityandthebiaschangepoststorage,theinstrumentoperating
temperatures were analyzed by plotting some telemetry records of
the forward optical element temperatures available from the NASA
LandsatImageAssessmentSystem(IAS)(seeFig.6).Thesedataindi-
catetwothings.Thefirstisthedramaticchangeinoperatingtemper-
aturepoststoragewhichisalikelysourceofthebiasshift(recallthat
noacceptedforeopticsradiationmodelexistssonomodel-basedtest
canberuntoassessthisassumption)andthesecondistherelatively
largevariationinoperatingtemperaturesearlyinthelifetime(i.e.pre
storage)whichisalikelysourceofthelargerthanexpectedbiasvar-
iation pre storage (note: this large variation in temperature is only
Fig.6.AtimeseriesofTM4biasestimatesandcorrespondingtemperaturesofthescan
partiallycapturedinthesmallsampleshownhereforthescanline linecorrector(SLC)duringthesameperiodfromtheIAS.
Pleasecitethisarticleas:Schott,J.R.,etal.,ThermalinfraredradiometriccalibrationoftheentireLandsat4,5,and7archive(1982–2010),
RemoteSensingofEnvironment(2012),doi:10.1016/j.rse.2011.07.022
J.R.Schottetal./RemoteSensingofEnvironmentxxx(2012)xxx–xxx 7
theradianceuncertaintiesareshowninequivalentapparenttemper-
ature(typicallyat300Ktomakethemmoreintuitive).
TheS valuesinTable1aremeasuredvaluesforeachinstrument
i
andinallcasestheyshownosignificantchangeoverthelifetimeof
theinstruments.However,thevaluesforTM4and5dochangewithin
anoutgassingcyclebecausetheinternalgaindecaysasicebuildsup
onthefiltersresultinginworseerrorduetoelectronic/quantization
noise as the transmission decreases. The uncertainties in the pre-
dicted radiances (S ) for the NOAA buoy and surface temperature
p
methods(RIT)aredrawnfromtheresultsofanextensiveerrorprop-
agation study that cascades the uncertainties in the temperature
measurementswiththeuncertaintiesintemperaturepropagationto
the surface skin temperature, uncertainties in the meteorological
and radiosonde measurements and uncertainties in the radiation
propagation models (Padula et al., 2011). The uncertainties in the
predictedradiancesfortheaerialtechniquearedrawnfromasimilar
Fig.7.Plotofradiancepredictedatthesensorversusradiancemeasuredatthesensor analysis reported in Schott et al. (2004). Finally the errors in pre-
forTM5dataforthetwotimeperiods(preandpost1/1/1997).TheRMSdeviation
aboutthebestfitlinesprovidesanestimateoftheresidualuncertaintyaboutthe dicted radiance for the surface radiometer/near surface thermistor
datainthearchive. technique(JPL)areestimatedfromsurfacetemperatureuncertainty
estimatesdrawnfromHooketal.(2007)andestimatesoftheradia-
tionpropagationuncertaintiesbasedontheautomateduseofunfil-
systematic variation in the instrument signals is accounted for teredNCEPdata.Note,allthedataleadingtotheestimatesofS in
L
through the onboard calibration processes, S should just be the Table1areassumingsinglepixelmeasurements.Ifmultipleuniform
i
standarddeviationofthesignalaboutthemeanwhenobservinga points are averaged, the instrument noise can be significantly re-
constantflux(e.g.fromtheonboardblackbody).Theoveralluncer- ducedsuchthatS shouldapproachS .
L p
tainty(S)canalsobemeasuredempiricallybycalculatingtheroot AnalysisofTable1indicatesthattheS andS valuesareingen-
L L RMS
meansquareerror(S )intheobservedradiancevaluesfromthe eralagreementwiththeexceptionoftheearlyTM4results.Solving
RMS
bestfitorfinalcalibrationlinegeneratedfromthecalibrationdata for the magnitude of the uncertainty unaccounted for by the error
(see for example, Fig. 7). This empirical measurement is the best modelas
estimateoftheresidualuncertaintyinthedatafromthearchive.Fur-
(cid:3) (cid:4)
thermoreanydifferencebetween themodeleduncertainty(Eq. 6) S ¼ S2 −S2 12 ð7Þ
andtheobserveduncertainty(S )suggeststhatourestimatesof u RMS L
RMS
S orS areinerrororthatthereareunaccountedsourcesofvariabil-
p i
ityintheprocess. yieldsavalueof0.86K.Asindicated,abovewebelievethatmuchof
Table1includesestimatesoftheexpecteduncertainty:insensor thisunaccountedvariabilityisduetothelargevariationsininstru-
reachingradianceforeachmethodology(S ),duetonoiseineachin- mentoperatingtemperaturesduringitsfirst yearofoperation.It is
p
strument(S),aswellasthemodeled(S)andmeasured(S )esti- alsopossiblethatthemuchsmallervariabilityinoperatingtempera-
i L RMS
mates of the overall uncertainty. In some cases where significantly turesforTM4afterstorageandfortheotherinstrumentsisstillasig-
differentmethodswereusedforcalibrationordifferentuncertainties nificant contributor to the smaller unaccounted uncertainties from
measured,multiple results are shown per instrument. Note that all theseinstruments.
Table1
ResidualuncertaintiesinthedatafromtheUSGSLandsatarchiveexpressedinapparenttemperature[K].Valuesinparenthesisarethenumberofpointsincludedintheanalysis.
Uncertainlyinpredicted Instrument Modeleduncertainty Observedvariabilityabout Observedvariability
radianceSp noiseSi insensedradianceSL bestfitcalibrationlineSRMS unaccounteduncertaintySu
Aerial(A) 0.31
Surfacetemperature(RIT) 0.34
Surfaceradiometersand 0.35
thermistors(JPL)
Subsurfacetemperature 0.41
(NOAAbuoys)
Landsat7(composite)(324) 0.21a 0.41 0.48b 0.25
RIT(51) 0.40 0.32
JPL(234) 0.41 0.48
NOAAbuoys(39) 0.46 0.59
Landsat5 0.17–0.3
1984–1998NOAAbuoy 0.44–0.51 0.53b 0.24
(102)
1997–2010composite(285) 0.41–0.48 0.66b 0.49
RIT(29) 0.38–0.45 0.48
JPL(149) 0.39–0.46 0.73
NOAAbuoy(107) 0.44–0.51 0.60
Landsat4 0.22–0.32
1982–2983NOAAbuoy(9) 0.47–0.52 0.98b 0.86
1987–1992NOAAbuoy(19) 0.47–0.52 0.43b
a NEΔΤforthelowgainis(0.26K).
b Thesearethebestvaluestousefortheexpecteduncertaintyintheradiancevalues(i.e.theyarebasedontheaverageofallavailablepointsfortherespectivedataera).
Pleasecitethisarticleas:Schott,J.R.,etal.,ThermalinfraredradiometriccalibrationoftheentireLandsat4,5,and7archive(1982–2010),
RemoteSensingofEnvironment(2012),doi:10.1016/j.rse.2011.07.022
8 J.R.Schottetal./RemoteSensingofEnvironmentxxx(2012)xxx–xxx
4.Impactonusercommunity could provide ongoing monitoring of Landsats5 and 7. In addition,
the use of many NOAA buoys augmented with the JPL buoy data
With the implementation by USGS of the Landsat 4 results couldquicklyprovidemanydatapointsforcalibrationofLDCMim-
reported here, all of the Landsat 4, 5 and 7 thermal data produced mediately after launch. To take advantage of the opportunity, RIT
fromthearchiveafterApril1,2011shouldbefreeoffirstordersys- plans to develop tools to use the NOAA buoys in an operational
tematic errors. This, for the first time, will allow users to process mode.
anyofthesedatawithconfidenceintheirintegrity.Thesedatanow Finally with the demonstration reported here, that the Landsat
represent one of the longest well-calibrated records of the thermal thermal archive is calibrated in radiance to acceptable levels, the
historyoftheearth'ssurface.Thiswillallowthesciencecommunity opportunityexiststoconsiderdevelopmentoflandsurfacetempera-
tostudythetemporaltrendsinthermalbehaviorofrelativelysmall ture(LST)mapsfromtheLandsatradiancedata.USGSNASAGoddard,
landscapefeatures(Schneideretal.,2009).Coupledwiththeparallel JPL,andRITareinitiatingaproofofconceptefforttodemonstratethat
work to radiometrically calibrate the reflective data in the Landsat LST maps can be operationally produced from the Landsat thermal
archive(Markham&Helder,2012),thiscalibrationeffortallowsthe archive.
Landsatarchivetotrulyliveuptoitsgoaltoserveasthelong-term
recordoftheplanetathumanscales.
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RemoteSensingofEnvironment(2012),doi:10.1016/j.rse.2011.07.022
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Pleasecitethisarticleas:Schott,J.R.,etal.,ThermalinfraredradiometriccalibrationoftheentireLandsat4,5,and7archive(1982–2010),
RemoteSensingofEnvironment(2012),doi:10.1016/j.rse.2011.07.022