Atmospheric Correction of Visible to Middle-Infrared EOS-MODIS Da

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1-1-1997

Atmospheric correction of visible to middle-infrared EOS-MODIS data over land surfaces:

Background, operational algorithm and validationE. F. VermoteUniversity of Maryland

N. El SaleousUniversity of Maryland

C. O. JusticeUniversity of Maryland

Y. J. Kaufman

Goddard Space Flight Center

J. L. PriveeGoddard Space Flight Center

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Vermote, E. F.; El Saleous, N.; Justice, C. O.; Kaufman, Y. J.; Privee, J. L.; Remer, L.; Roger, J. C.; and Tanre, D., "Atmosphericcorrection of visible to middle-infrared EOS-MODIS data over land surfaces: Background, operational algorithm and validation"(1997).NASA Publications. Paper 31.hp://digitalcommons.unl.edu/nasapub/31
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Authors

E. F. Vermote, N. El Saleous, C. O. Justice, Y. J. Kaufman, J. L. Privee, L. Remer, J. C. Roger, and D. Tanre

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JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 102, NO. D14, PAGES 17,131-17,141, JULY 27, 1997

Atmospheric correction of visible to middle-infrared

EOS-MODIS data over land surfaces:

Background, operational algorithm and validation

E. F. Vermote, N. E1 Saleous, C. O. Justice, Y. J. Kaufman, 2 J. L. Privette,2

L. Remer,3 J. C. Roger, and D. Tanr6s

Abstract. The NASA moderate esolution magingspectroradiometerMODIS)

instrumentwill provide a global and improved sourceof information for the studyof land

surfaceswith a spatial esolutionof up to 250 m. Prior to the derivationof various

biophysical arametersbasedon surface eflectances,he top of the atmosphere ignals

need to be radiometrically alibratedand corrected or atmospheric ffects.The present

paper describesn detail the state of the art techniques hat will be used for atmospheric

correctionof MODIS bands 1 through 7, centered at 648, 858, 470, 555, 1240, 1640, and

2130 nm, respectively. reviousoperationalcorrectionschemes ave assumed standard

atmospherewith zero or constantaerosol oading and a uniform, Lambertian surface.The

MODIS operationalatmospheric orrectionalgorithm,reported here, usesaerosoland

water vapor information derived from the MODIS data, corrects or adjacency ffects and

takes nto account he directionalpropertiesof the observed urface.This paper also

describeshe operational mplementationof these echniques nd its optimization.The

techniques re applied o remote sensing ata from the LandsatThematic Mapper (TM),

the NOAA advanced ery high resolution adiometer AVHRR), and the MODIS

airbornesimulator MAS) and validatedagainstground-based easurementsrom the

Aerosol Robotic Network (AERONET).

1. Introduction

The use of MODIS data for retrieval of land parameters,

such as the bidirectional reflectance distribution function

(BRDF), albedo, egetationndices VIs), fractionof absorbed

photosyntheticallyctive adiation FPAR), and leaf area in-

dex LAI), requires hat the top of the atmosphereadiancebe

converted o surface reflectance.The processnecessary or

that conversions called atmospheric orrection.By applying

the proposed lgorithms nd associated rocessing ode,mod-

erate esolutionmaging pectroradiometerMODIS) level B

radiances re corrected or atmospheric ffects o generate he

surface eflectanceproduct.Atmosphericcorrection equires

inputs hat describehe variableconstituentshat influence he

signalmeasured t the top of the atmosphereseeFigure 1 and

Tables a and lb) and a correctmodelingof the atmospheric

scattering nd absorption i.e., a band absorptionmodel and

multiple-scatteringectorcode). n addition,an accurate or-

rection requiresa correction or the atmospheric oint spread

function for highspatial esolution ands)and coupling f the

surfaceBRDF and atmosphere ffects.

Department f Geography, niversity f Marylandand NASA

GoddardSpaceFlight Center, Greenbelt,Maryland.

2NASAGoddard pace lightCenter,Greenbelt, aryland.

3Science,ystem nd Applicationsnc., NASA GoddardSpace

Flight Center, Greenbelt,Maryland.

4Laboratoire e Physique ppliqufieaux Milieux Oceaniques

C6tiers, Station Marine-Universitfi du Littoral, France.

SLaboratoire'Optique tmosphfirique,niversitfiesSciencest

Techniques e Lille, Villeneuved'Ascq,France.

Copyright 997by the AmericanGeophysical nion.

Paper number 97JD00201.

0148-0227/97/97 JD-00201 $09.00

Over the past few years, considerable ffort has been put

into the modeling of atmospheric ffects at the Laboratoire

d'Optique Atmospheriqueof Lille, France. Recently, he Sec-

ond Simulationof the Satellite Signal n the Solar Spectrum

(6S) radiativecodewas released Vermote t al., 1997] and is

well suited or various emote sensing pplications nd is fully

documented. It includes simulation of the effects of the atmo-

sphericpoint spread function and surfacereflectancedirec-

tionality.We are currentlyusing he 6S code as the reference

to enable ntercomparison f algorithms nd to verify the cor-

rect implementation of the MODIS atmosphericcorrection

algorithm.For example,Tables la and lb illustrate the appli-

cationof the code to show he relative atmospheric ffectson

examplesof existingenvironmentalsensors.

Our plan is to use MODIS atmospheric roductsand ancil-

lary data setsas nputs o the operationalatmospheric orrec-

tion. Collaboration n the area of aerosol etrieval has already

been nitiatedwith the MODIS aerosolgroup [Kaufmanet al.,

this ssue].An importantaspectof the operationalalgorithm s

to accommodate he large amount of input data and the nec-

essary ast turnaroundof products,without compromisinghe

scienceobjectivesor the accuracygoals.

2. Theoretical Background

The surface eflectance roductwill be computed rom the

MODIS calibrated adiancedata (level B) in bands1 through

7 (centeredat 648, 858, 470, 555, 1240, 1640, and 2130 nm,

respectively). he product s an estimateof the surface pectral

reflectance for each band as it would have been measured at

ground evel f there were no atmospheric cattering r absorp-

tion. The correction scheme includes corrections for the effect

of atmospheric ases, erosols, nd thin cirrusclouds,and it is

17,131

This article is a U.S. government work, and is not subject to copyright in the United States.


4/13

17,132 VERMOTE ET AL.: ATMOSPHERIC CORRECTION OF EOS-MODIS DATA

G2,

I 20km

IMoeculesRayleighcaterng)

Ozone,tat sphercAerosol

I H20,roposphericerosol

Ground Surface

Figure l. Descriptionof the components ffectinga satellite

remote sensingsignal n the 0.4-2.5/zm range.

applied to all noncloudy evel lB pixels hat pass he level lB

qualitycontrol.The surface eflectance roduct s the input for

generation or severaland products: egetation ndices VIs),

BRDF/albedo, thermal anomaly, snow/ice, and FPAR/LAI.

Therefore it is an important and essentialproduct. The at-

launch version will be fully operational.An Algorithm Theo-

retical BackgroundDocument ATBD) for the surface eflec-

tance product and the approach adopted for atmospheric

correctionof MEDIS data [Vermote t al., 1995] s availableon

Home Page of the EOS ScienceProjectOffice (SPO) (http://

eospso.gsfc.nasa.gov/atbd/pgl.html,TBD-MeD08).

Rather than reproducing he ATBD contents, his paper

focuseson several mportant and recent improvements o the

algorithm,namely, he atmospheric oint spread unctioncor-

rection and an atmosphereBRDF couplingcorrection.One

critical aspectof MEDIS algorithmdevelopment s the need to

optimize the algorithm for efficient global processing.n the

sections hat follow, the practical aspectsof global data pro-

cessingor the algorithmare described.

2.1. Atmospheric Point Spread Function Correction

The case of nonuniform ground boundary conditionshas

been addressed y several esearchersTanr et al., 1981;Kauf-

man, 1982; Mekler and Kaufman, 1980]. The correction ap-

proach is to assume hat the signalreceivedby the satellite s

a combinationof the reflectanceof the target pixel and reflec-

tances from surroundingpixels, each weighted by their dis-

tance rom the target. Because he apparentsignalat the top of

the atmosphere f a pixel comesalso rom adjacentpixels, his

effect is also called adjacency ffect. The correction nvolves

inverting he linear combinationof reflectanceso solve or the

reflectanceof the target pixel.

We presenthere the proposedoperational mplementation.

It shouldbe noted that this effect will be less mportant for

MEDIS with a 250-500 m pixels han it is for higher spatial

resolutiondata, for example,30 m pixel from Thematic Map-

per. The correctionprocedurestems rom the modelingwork

by Tanr et al. [1981] and is simplified n this code for opera-

tional application.

In the caseof an infinite uniform Lambertian target of re-

flectance ps, the reflectanceat the top of the atmosphere,

PTOAcould be written as

PTR+A(s) R+A(Iv)

PTOA-- R+A'- 1 -psUSRA (1)

Table la. Order of Magnitude of AtmosphericEffects

for AVHRR Bands 1 and 2 and NDVI =

(Band 2 - Band 1)/(Band 2 + Band 1)

Ozone Water Vapor Aerosol V:

0.247-0.480, 0.5-4.1, Rayleigh, 60-10 km

cm/atm g/cm 1013mbar Continental

Pl

620 _+ 120 nm 4.2-12%

P2

885 _+ 195 nm

NDVI

(bare soil)

pl = 0.19,

P2 = 0.22

NDVI

(deciduous

forest)

p = 0.03

P2 = 0.36

0.02-0.06

0.7-4.4% 0.02-0.06 0.005-0.12

7.7-25% 0.006-0.02 0.003-0.083

0.011-0.12 0.036-0.094 0.006-0.085

0.006-0.017 0.036-0.038 0.086-0.23 0.022-0.35

The proportional ffect transmission)s givenaspercentage%) of

increase ) or reduction ) of the signal.All othereffects swell as

the effect on the normalizeddifference ndex (NDVI) are given n

absoluteunits;p is the reflectanceobserved n the advanced ery high

resolution adiometer (AVHRR) band 1; /92 s the reflectanceob-

served in AVHRR band 2.

Table lb. Order of Magnitude of AtmosphericEffects

for TM Bands 1-5 and 7 and NDVI --

(Band 4 - Band 3)/(Band 4 + Band 3)

Ozone Water Vapor Aerosol V:

0.247-0.480, 0.5-4.1, Rayleigh, 60-10 km

cm/atm g/cm 1013mbar Continental

Pl

P2

P3

P4

P5

P7

490 _+ 60 nm

575 _+ 75 nm

670 _+ 70 nm

837 _+ 107 nm

1692 +__ 78 nm

2190 _+ 215 nm

NDVI

(bare soil)

P3 = 0.19,

/94 ' 0.22

1.5-2.9% ". 0.064-0.08 0.007-0.048

5.2-13.4% 0.5-3% 0.032-0.04 0.006-0.04

3.1-7.9% 0.5-3% 0.018-0.02 0.005-0.034

" 3.5-14% 0.007-0.009 0.003-0.023

. 5-16% 0.000-0.001 0.001-0.007

. 2.5-13% "' 0.001-0.004

0.015-0.041 0.015-0.06 0.03 0.006-0.032

The proportional ffect transmission)s givenaspercentage%) of

increase r reductionof the signal.All other effects swell as he effect

on the NDVI are given n absoluteunits.


5/13

VERMOTE ET AL.: ATMOSPHERIC CORRECTION OF EOS-MODIS DATA 17,133

where PR+A is the intrinsic atmospheric eflectancedue to

Rayleigh and aerosol scattering,TR+A(l%) (respectively

T + ( v)) is the total downwardrespectivelypward)atmo-

spheric ransmission, + is the sphericalalbedo of the at-

mosphere,% (respectively/Zv)s the cosineof the Sun (re-

spectively iew) zenith angle.

When taking nto account he adjacency ffect, the signalat

the top of the atmosphere an be rewritten by decoupling he

photonsoming irectlyrom he target e /v) from hose

coming rom areasadjacent o the target and then scattered o

the sensor t d(v) ):

psTa+A(s)-/v + {ps} a+A(s)td(v)

/'TOA IR+A 1 - (ps)S+ ' ""

r is the atmospheric pticaldepth, a(/, v) is the diffuseupward

transmission, is the pixel reflectance, nd {p} is the contri-

bution of the pixel background o the top of the atmosphere

signal hat is computedas

(Ps) = f(r(x, y))p(x, y) dx dy,

(3)

wherex, y denotes he coordinate o a local referencecentered

on the target, and (r) is the atmospheric oint spread unc-

tion.

We can see hat if we considerhat 1/(1 - (9s)S+)

1/(1 - p}'S+), then Ps and p}' (from (1)) are related

through he followingequation:

e-'/ v td(p,O

Os= Os +a(l(Os>+a(lv)' (4)

Thereforewe cancorrect he reflectance, btained rom (1), p}'

for the adjacency ffect using

psUT+n(v) (ps)td(tXv)

Ps e-,/v (5)

In practice, Ps} s computedrom a subzone f (2n + 1) x

(2n + 1) pixelsof the original magecenteredon the pixel to

be corrected sing p}' i, j) is used nsteadof Ps i, j) since he

latter is not available; he error introducedcan be reducedby

usingsuccessiveterationsbut is small [Putsay, 992])

(Ps) f(r(i, ))psU(i,), (6)

j=-n i=-n

with r(i, j) representinghe distance etween he pixels i, j)

and the center of the zone.

As part of a NASA-funded collaborationwith the National

ScienceFoundation NSF) Long-TermEcologicalResearch

(LTER) sitenetworkon atmosphericorrection alidation,we

applied the techniquepreviouslypresented or correction of

the atmosphericpoint spread function. This techniquewas

applied to the LandsatTM data (30 m resolution)up to a

distanceof 20 pixels around the viewed pixel. Two optimiza-

tionswere necessaryo arrive at an acceptable rocessingime

(about wice he amountof time of a simplecorrection). irst,

we generated over the range of expected alues)a look-up

table of the product (r(i,/))p}'(i, j). By using he look-up

table,we do not performanymultiplicationo compute 6) and

reduce he processingime significantly. econdly, he compu-

tation for the pixel of coordinate k, l)(ps(k, l)) was com-

puted from its neighborat coordinate k, l - 1)(ps(k, l -

1), the advantagehere being that the atmospheric oint

spread unction s rather smoothand that the differencematrix

between wo adjacentpixelscontainsmany zeroes.By sorting

the differencematrixvaluesand eliminating he zero elements,

we were further able to reduce he number of operations o be

performed by roughly a factor of 10. Figure 2 illustrates he

resultsof the adjacency ffect correction or TM band 1. The

scenewas acquired over a coastalarea in the eastern United

States.On the left side s the corrected mage;on the right side

is the originaldigital count mage.The top part represents he

full subset1000 x 1000pixels); he bottompart represents n

enlargementof a part of the scene.The correctedsceneap-

pears o showmore contrast han the uncorrected cenedue to

the correction of atmospheric eflectance and transmission

terms.The enlargeddetail shows he impactand correctionof

the adjacency; he small dark area in the original scenewas

previously essvisiblebecause t was surrounded y brighter

pixels.

For MODIS the surfaceadjacency ffect correctionwill be

made up to a distanceof 10 pixelsusing he same technique

developed or the TM. Because he atmospheric oint spread

functionvaries with the view angle as illustratedby Figure 3,

we will use precomputed ablesas a functionof view angle.

2.2. BRDF Atmosphere Coupling Correction

If the surface is not Lambertian, the result of the correction

using 1) is inexactdue to the couplingbetween he surface

BRDF and the atmosphereBRDF [Lee and Kaufman, 1986]

which the equationdoesnot take into account.For example,

Figure 4 shows he differencebetween he true ground reflec-

tance (9s), and the reflectance omputedwithout coupling

(psa) can each .02 or off-nadir iews.

An approach to model/correct his effect stems from the

work of TanrE t al. [1983].The contribution f the target o the

signalat the top of the atmospheres decomposed s the sum

of four terms: (1) the photonsdirectly ransmitted rom the

Sun o the targetand directly eflectedback o the sensor, 2)

the photonsscatteredby the atmosphere hen reflectedby the

target and directly ransmittedo the sensor, 3) the photons

directly transmitted o the target but scatteredby the atmo-

sphereon their way to the sensor, nd finally (4) the photons

havingat least two interactionswith the atmosphereand one

with the target. The equation is written as [Vermoteet al.,

1997]:

PTOA(s, -Lv,Os- 0v) = PR+A

(1)

+ e-'/'e-'/Sps(tZs,Zv,Os- Ov)

(2) (3)

+ + '

(4)

+ +

(v)S (b)

1 -Sb

(7)

with Os (resp.0v) the Sun (resp.view) azimuthangle,and


6/13


..

.

:"' ? ''. .:" ...

:. : . =======================================================:.:::,:...;:::::..............:.:...::.::::::::::.::=====================

....'-;:i::'::i::ii4..,,.......-.i:,

..... ......

.:. :::..:..::.:

..........

....::::::::::::::::::::::::::::::::::::::::

Figure2. Comparisonf ThematicMapper TM) band1 datacorrectedor atmosphereleft side) o

uncorrectedountsrightside).The correctionncludes djacencyffectcorrection.

L+,(-,, R, ,, , qb')ps(,,, qb'- ck)dldck'

fo2L+,(,,,s,,'dz k'O

(8a)

where - (resp. .q) are the Rayleigh resp.aerosol) ptical

depth, and

p' (s, , q,) = (, m, q),

(8b)

= p'(s, , ), (8c)

1f2*rfs([l,,.1,',[}.l,.l,did'arkl

0 J0

. (8d)

1f2*rf[I,LI,'[l,'([l,

0 J0

In our approach, we use the ratio between the estimated

BRDF (p}n) coupledwith the atmospherend the actualsur-

face BRDF (p) to correct he measured alues; hat is,

iOTOA(/- 's,- 'v,) = PR+A-e-'/e-*/*ps(ts,, rk)

+ ps(s, , )

with

(9a)

pm([- ,s,- ,v, )

P*(s,, rk) psm(s,, rk) (9b)

P'*(s, , rk)= p*(, s, rk), (9c)

= : pm(ldl's'dl,,

P*(s,, rk) psm(s,, rk)' (9d)

The solving f (9a) for p is doneby solving second-order

equation hat only has one positivesolution.The rationale

behind his approachs that only the "shape"of the BRDF

influenceshe correction rocess nd not the actual"magni-

tude" of the estimatedBRDF. This approachgivesmore

weight to the actual observation han to the estimatedBRDF

used.Both the surfaceBRDF (p) and the atmosphereou-

pledBRDF terms 1o , i0m) canbe precomputedndstored n

tables.

We are currently nvestigatingwo alternativeapproaches

for obtainingmodeledBRDF inputs.One approachs to use

the inearBRDF modelparameterserivedrom he previous

16 dayperiod,generated spartof the MODIS BRDF product

[Strahler t al., 1995].The otherapproachelieson the BRDF


7/13

VERMOTE ET AL.' ATMOSPHERIC CORRECTION OF EOS-MODIS DATA 17,135

associated ith land covercategories sed n the MODIS LAI/ o.35 .

FPAR product [Running t al., 1994] and simulatedusing a

three-dimensionalanopy odelMynenital., 1992].n the 0.3-

latter case,BRDF and coupling ermsare stored n tablesas a

0.25

functionof Sun-viewgeometry,atmospheric ptical depth, bi-

ome type,and LAI. The biome s determinedby the land cover o.2

map,and he LAI is selectedy minimizinghe difference a.

betweenhespectralependencef observedndmodeled 0.5

reflectance n MODIS bands 1, 2, 3, and 4. The advantage n

usinghe irstapproachs hat heBRDF shapesmore inked 0.

to actualobservations;he advantage n the secondcase s that

0.05 _

the couplingcorrectioncan be estimated n real time. A com-

parisonof the relativemeritsof theseapproaches ill be made

0

in the near future. -0

3. Implementation for Global Processing

3.1. ProcessingScheme

As currentlydeveloped, he atmospheric orrectionprocess

ingests he MODIS-calibrated radiances nd estimates he sur-

face reflectances. In addition to the estimates of the surface

reflectance he data product contains he following quality

assuranceQA) information or eachpixel: 1) integrityof the

surface eflectance stimate; 2) successfulompletionof the

correction cheme;3) presence f cloud clear,cloudy,mixed,

shadow); 4) presence f cirruscloud no cirrus, ow, average,

high); 5) sourceof aerosol nf(rmation:MODIS aerosol, li-

matology; 6) presenceof aerosol low, average,high); (7)

sourceof water vapor information:MODIS water vapor, cli-

matology; 8) sourceof ozone information:MODIS ozone,

climatology;9) whether he datum s from land or water.

0.5

-- 50 km

Figure 3. Isolines of the pixel backgroundcontribution to

the signalat the top of the atmosphere or a pure molecular

case. he energy ources 10 W andeachpixel s considered

to have a Lambertian reflectance of 1. The contribution of the

backgrounds presented s the numberof watts coming rom

eachcell (201 cells x 201 cells).The plain lines are for nadir

viewing; he broken lines are for a view angle of 70 [from

Vermote t al., 1997].

[] p2(0,0, ) 'n.. ct

OTOA(0s,, b'qb

3=670nm, =0.23

a

SUN _

-t0 -2'0 0 2b 4b 6b

0 [deg]

v

Figure 4. Illustration of the atmosphere-bidirectional istri-

bution function BRDF) couplingeffect correction.The sur-

face reflectancePs is computedby the Hapke model (the

parameters are inverted from surface reflectance directional

data taken over a plowed field by Kimes et al. [1986]) and

correspondso the interrupted ine. The plain ine corresponds

to the top of the atmosphere ignal,P:o^,at 670 nm, assuming

average atmospheric urbidity. The surface reflectances e-

trieved singheLambertianypothesisr equation1), psa,

are representedby the open squares.

The current version of the software is the first that reads

MODIS synthetic ata (A. Fleig and K. Yang, personalcom-

munication, 995) andwritesMODIS products sing he HDF

(hierarchical ata format) structure.n this codewe were able

to successfullymplement the correction or the atmospheric

point spread function and the coupled atmospheresurface

BRDF. Each of these corrections an be selectively ctivated.

Figure 5 givesa global overviewof the current software unc-

tionality, data volumes,and central processing nit (CPU)

requirements.

3.2. Developing Aerosol Climatology

Because he aerosolproductbeinggeneratedby the MODIS

atmospheregroup is a critical input to the atmospheric or-

rectionscheme Tanr et al., 1992],validationand prototyping

of the aerosolproduct and correctiondeservespecialcooper-

ation between he atmosphereand the land groups.Software

developmentactivities are currently focused on the aerosol

climatology.We need to understand on a global basis the

impactof aerosols.We have thereforebasedour approachon

the advanced eryhighresolution adiometer AVHRR) data.

This activity s important for MODIS for three different rea-

sons: 1) it provides he default nput to the atmospheric or-

rection algorithm should he MODIS aerosolproduct be un-

available, 2) it can contribute o the validationof the aerosol

algorithm or MODIS, and (3) it validates he aerosolatmo-

spheric correction process or AVHRR data. We have cur-

rently developeda prototypeapproach o generate his clima-

tology.Plate 1 shows ver the tropicalbelt area a composite f

the aerosoloptical depth during irst week of September1993.

Smoke rom biomass urning Brazil and SouthAfrica) and

dust from arid area (Red Sea and East Africa) aerosolcan

clearlybe observed.An important sourceof perturbation or

vegetationmonitoring s the stratospheric erosols fter a sig-

nificantvolcaniceruption.The stratospheric erosols ave ong

lifetime and thereforecouldbe eliminated n monthlycompos-


8/13


- ...... -;, .... . ;, . ' ,. . ,-. _. ....

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r:,,' . ?:- .-.' ," " . :.;. " *" . ', 7

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} - ..' '&'/ '. 5, 'S'.l. " ... : ,. ;--

i i

';: .....

Plate 1. Maximum aerosoloptical hickness t 550 nm during the week September3-9, 1993, derived rom

NOAA AVHRR global area coverage GAC) data.

ites aswell as ropospheric erosols. ince1981, wo important

volcaniceruptionsaffected global vegetationmonitoring, El

Chichonand Mount Pinatubo,as illustratedby Plate 2.

4. Validation Plan

Validation activities anbe divided nto prelaunch alidation

of the algorithmand postlaunch alidationof the product.The

MODIS surface eflectanceproductvalidationwill use acom-

bination of ground-basedmeasurements, irborne measure-

ments,comparisonwith other sensordata, and imageanalysis.

4.1. Methodology

Validation of the reflectanceproductwill be undertaken or

selected lobal est sitesaspart of the proposedEOS Test Site

Program,where a suite of measurementsor atmosphere, ur-

face reflectance,and other surfaceparameterssuch as LAI,

FPAR, and net primary production NPP) will be collected

I I

outh El Chichon

50

1990

Pinatubo

1981

Plate 2. Monthly averageof the stratospheric erosoloptical depth deduced rom the advanced ery high

resolution adiometer AVHRR) data showingmajor eruptionsof E1 Chichon 1982) and Pinatubo 1991)


9/13


220 '

" I uniform surface I

[Climatology

j ft ompton7minutesPU

VI computation 3 minutes CPU

249

Figure 5. Current moderateresolution magingspectroradi-

ometer (MODIS) atmospheric orrectionprocessing hread

flowchart.

[Runninget al., 1994]. These measurementswill be made at

different temporal frequencies s appropriate or the param-

eters. t is important to considerseveral actorswhen evaluat-

ing the atmosphericcorrection, or example under changing

Sun/sensor eometry,atmospheric tate, and surfacestate.As

part of the surface eflectance alidation,we propose o con-

duct a maximum of four campaigns year correspondingo

seasonal hangesn surfacestate and Sun geometry.For each

of these campaigns,we will collect surface reflectance and

atmosphericstate data with simultaneous atellite coverage.

Both clear and turbid atmospheres re desirable or eachcam-

paign as well as data gatheredat four or five different viewing

geometries nadir, backscattering,orward scattering).Dark

and bright surface measurementswill be collected for each

campaign,given that the success f the correction or a dark

surfacedependsmainly on the correctestimateof the intrinsic

atmospheric eflectance,whereas or a bright surface t de-

pendson the correctestimateof the transmittance.Critical to

this plan is the continuation and expansionof AERONET

[Holbenet al., 1997],whichprovidesdata on opticaldepth and

aerosolas well as size distributionon a continuous asis see

Figure 6 for current locations).The total number of sites

needed or validation s related to two requirements: 1) the

expected ariabilityof atmospheric onditions;2) spectral ig-

naturesand anisotropic ropertiesof the different and covers.

We expect o need approximately -3 sites n the polar envi-

ronment polar regions),7-8 sites n the boreal environment

(Canada, Greenland, Norway-Sweden,Russia), 5-6 sites in

North America, 5-6 sites n western Europe, and 5-6 sites n

easternEurope. More siteswill be needed n the tropical areas

becauseof the importanceof aerosolvariability and transport

and the rapid temporal change n land cover (e.g., at desert

boundaries).There are currently 18 Sun photometers nstalled

in the tropics hat mainlycoverBrazil (12) with some n Africa

(6). Ideally,we need at least12 more n Africa and 12 more for

the rest of the tropics o coverAsia. The southernhemisphere,

includingSouthAmerica, southernAfrica, and Australia, will

need at least 7-8 sites with 2-3 sites n the southern polar

region.On the basisof this allocation he total number of sites

is between 69 and 74. Further details on validation methods

and sites are available on the internet through the EOS Vali-

dation Office MODIS summarycharts.

Limiting errors n surface eflectance o less han 0.005 rms

for clear conditions nd 0.01 rms for turbid conditions 5 km

visibility) will be considered a success or the atmospheric

correction.To meet this goal, MODIS radiometriccalibration

(relative o the Sun) shouldhaveat least2% accuracy. ecause

finite cloud fields modify the downward radiation field, we

expect a decrease n the performanceof the algorithm under

these conditions. Cloud situations should be included in the

validation data collection to assess he change n algorithm

performance.

4.2. Prototyping Activities

Two tasksneed to be addressedwhen generating/validating

a global "product"before launch. The first task is to validate

how the algorithmperformswith a similar data set ("science

validation"). For this product he approachwill be to continue

and expandon the LTER atmospheric orrectionproject. The

LTER project is particularly relevant as the TM data used in

this study ncludesseveral of the spectralbands planned for

MODIS. AERONET Sun photometer data are collected at

these sites simultaneouslywith the satellite data. Figure 7a

illustrates he validationof the aerosol etrieval algorithmwith

TM data. In this case,optical depth deduced rom band 1 and

3 "dark targets" eflectances re compared o Sun photometer

measurements. he "dark targets" are selectedby using the

pixelswhose eflectance t 2.14/m are between0.015 and 0.05

and whosenormalizeddifferencevegetation ndex (NDVI) is

greater than zero (to eliminate water bodies). The average

"dark target" reflectance n band 1 is computedon a 50 km x

50 km area around the Sun photometer, and the surfacere-

flectance in band 1 is assumed to be one third of the reflec-

-1......... [ . I 89.50

... ' .... ....

..... :*'.' ...' "$"':.....**.... 45.00

-.-- - -;- . 0.50

' .a -.

;= .. ,:-44.00

0.50 S0.75 1812 50

Figure 6. Sun photometernetwork ocations source,B. N.

Holben, NASA GSFC). The vertical axis is the latitude in

degree south s negative,north s positive), he horizontalaxis

is the longitude n degree west s negative,east s positive).


10/13


1.00

0.80 -

0.60 -

0.40 -

0.20-

0.00 -

0.0

y -0.11831.2937x= .96417OG-ISLAND,2 ul

M SON, Jun

I

0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80

Sunhotometer470nm)

Figure 7a. Retrieval of opticaldepth n TM band 1 using he

"dark targets"approach band 7 at 2.14/xm is used or "dark

targets"detection)comparedwith Sun photometerdata.

0.5... .......

.4 ..........

0.2 ..................................................---- ..................................................................................

i i i

0.1-

0

0 0.1 0.2 0.3 0.4 0.5

unphotomete/670nm)

Figure 8a. Retrieval of aerosolopticaldepth using he dark

target techniquewith the 2.14/xm from MODIS airbornesim-

ulator (MAS) data during he SCAR A experiment Roger t

al., 1994].

tanceobserved t 2.14/xm. Figure 7a shows omparisonsf the

derivedopticaldepthusinga continentalaerosolmodelversus

the measured pticaldepth.Despitesomevery ow and slightly

negative values observed or the Sevilleta, New Mexico, site

that may be due to the topography f the area, the agreement

is encouraging.More encouragings the comparison hown n

Figure 7b. These histograms f band 1 reflectance or the Hog

Island, Virginia, LTER site for clear and hazy daysshow hat

Histogram of the reflectanceobservedover Hog Island

20.00 .... I .... I .... I .... I ....

..... Turbid day (corrected)

..... Clear day (Corrected)

Turbid day (top of the atmosphere)

15.00 ClearayTopfhetmosphere)

10.00

0.00 .... "',"''-,'.r--=--_.,-- ..... I ....

0.0 0.050 0.10 0.15 0.20 0.25

TM band I reflectance

Figure 7b. Test of the result of the atmospheric orrection

procedure includingaerosol etrieval and atmospheric oint

spread unctioncorrection) or a 1000 x 1000TM pkels area

of the Hog Island site for the clear and ha day.

the atmospheric orrectionprocess learly removed he arti-

facts ntroducedby the aerosol emporalvariability.

A further approach o validation s to use high-altitude ir-

borne data from MAS as we did during the Sulfate Cloud

AerosolReflectance-AtlanticSCAR A) experiment Roger t

al., 1994]. Using the MODIS airbornesimulator MAS), we

tested he 2.14/xm approach or detecting dark targets"over

six estsitesusing he same est as describedor TM. In Figure

8a, aerosol etrievalwasperformed or "dark targets"using he

0.67/xm MAS band (a reflectanceof 0.015 was assumedor

dark targetsat 0.67/xm) and a continental erosolmodel.The

Table 2. Resultsof the Inversionof Top of the

Atmosphereand Top of the CanopyUsing

SCAR A MAS Data Set

Leaf

Area Leaf Leaf Angle

Index Reflectance Distribution

rms

Green band top of 0.4 0.010

atmosphere

reflectance

Green band top of 9.2 0.105

canopy

reflectance

Red band top of 1.2 0.150

atmosphere

reflectance

Red band top of 2.7 0.070

canopy

reflectance

Green band >3 0.05-0.25

expected alues

Red band >3 0.03-0.16

expected alues

planophile 0.26X 10 3

erectophile0.44X 10 4



erectophile

erectophile

SCAR A MAS, Sulfate Cloud Aerosol Reflectance-Atlantic MODIS

airborne simulator.


11/13


- , .NT

........q%:;.........

_P}T

.....?,-;{.

Figure 8b. Grey level image of the MAS scene 0.87

used n the BRDF inversion Figure 8c and 8d). Annotations

on the imagespoint to the foresthot spot and water sunglint

features.

optical depth measurementsrom AERONET comparedwell

to MAS retrievals. In that case, the effect of the aerosol model

is more sensitive han for TM as the scatteringangle of the

differentobservationsaries from 10 o 150).For SCAR A

MAS data, strongdirectionalsurface eflectanceeffectscould

be observedover forest with a particularly sharp hot spot

phenomenon Figure 8b). We were able to fit the MAS data

using physically asedmodel Myneni t al., 1992].The results

are shown in Figures 8c and 8d. In the green band, where

at..mosphericcattering s larger, the atmosphericcorrection

definitely mproves he fit of the data both in backscatter nd

0.10

0.08

0.06

0.04

0.02

0.00

-40

Canopy Reflectance Model Fit of MAS Band 1

0.14...................................................

Top of Atmosphere Reflectance

O. 2 a /*' 0 Atmospherically....edeflect...

x - Vegetationodelit

-Vegetationodelit

-__

................................................

-30 -20 -10 0 10 20

View Zenith Angle (deg)

Figure 8c. Fits of MAS principal plane data usingMyneni et

al. model [1992] usingcorrected plain lines, diamonds)and

top of the atmosphere dashed ine, triangles) or the green

band (0.55/xm).

in forward scatteringdirections Figure 8c). In the red band,

both corrected and uncorrected data are fit well. The differ-

ence s important or the retrieved surfaceparameters Table

2), whether the top of the atmosphere eflectanceor the sur-

face estimated reflectanceor top of the canopy s used. The

parametersderived from top of the canopy eflectancevalues

are closer o the expectedvalues than the ones derived from

top of the atmosphere eflectance or this orestcase.The LAI

is higher n the greenband than in the red band,but it is quite

difficult to retrieve LAI values above 3 because of the satura-

tion of the signal,and therefore LAI errors are commonwith

densecanopies.

The second ask concerns alidating he global applicability

and robustnessof the algorithm. We can test the algorithm

data flow by using he MODIS syntheticdata set being devel-

oped by the MODIS sciencedata support eam (SDST), al-

though the sciencecannot be thoroughly ested using these

data becausewe are comparingone model output with an-

other. The globalprocessingssuehas o be addressed ith real

data. We plan to start to test the global applicabilityof the

MODIS algorithm using AVHRR time series data. Collabo-

ration will be developedwith the NASA EOS AVHRR Path-

Canopy Reflectance Model Fit of MAS Band 2

0.08.............................................

A Top of Atmosphere eflectance

.-Z x O Atmosphericallyorrectedeflectance

Vegetotlonodel it

0.06 ,,-. Vegetationodelit

-30 -20 -10 0 10 20

View Zenith Angle (deg)

c

0.02

0.00

-40

Figure 8d. Fits of MAS principal plane data usingMyneni et

al. model [1992] usingcorrected solid lines, diamonds)and

top of the atmospheredashed ine, triangles) or the red band

(0.67 m).


12/13


0.5

0.4

0.3-

0.2-

0.1-

0.0

0 0.1 0.2 0.3 0.4 0.5

'CSu (550nm)

hotometer

Figure 9a. Comparison of retrieved optical depth using

AVHRR data and the dark target approach and measured

optical depth from the Sun photometer network in August

1993 over eastern United States.

2.00

1.50-

1.00-

0.500-

0.00

0 0.5 1 1.5

: (630nm)

Sun photometer

Figure 9c. Same as Figure 9b but in 1993.

finder 2 Project, whose goal is to improve on the current

AVHRR Pathfinderby designing nd testingglobalprocessing

of AVHRR 1 km and 4 km land data as a pathfinder or

MODIS. This MODIS prototyping using the AVHRR will

include operationalcorrection or Rayleigh,ozone,water va-

por, and stratospheric erosoland will investigatehe possibil-

ity of correcting or tropospheric erosols.These corrections

will be conducted at a global scale over a range of actual

atmosphericand surface conditions.As an example of the

tropospheric erosolcorrectioneffort, we obtainedsomevery

encouraging esultsby usingAVHRR data to retrieve aerosol

at specific and sites. n these cases he 3.75 /am reflectance

[Rogerand Vermote,1996] was used n lieu of the 2.14/am to

detectdark targetsusinga thresholdof 0.03. Figures9a and 9b

show he resultsof AVHRR optical depth retrieval during he

SCAR A campaigns nd the 1992AERONET Brazil data set.

In both casesa continentalaerosolmodel was used.Figure 9c

shows the results of AVHRR retrieval over Brazil using

AERONET 1993August-September ata and a smokemodel

derived from AERONET aerosol size distribution.

0.8

0.4

0.2

i I

A A

0.2 0.4 0.6 0.8 1

Sunhotometer550nm)

Figure 9b. Same as Figure 9a but in 1992 over Brazil.

5. Conclusion

The presentpaper describeshe approach dopted or com-

puting the surface reflectance n MODIS visible to middle-

infrared land bands.The processing f the top of the atmo-

spheresignal o obtain surface eflectance s not perfect but

does ncorporatestateof the art techniques.We are currently

workingon operationalprototypes singexisting ata sources

for the prelaunchalgorithm and productvalidation phase. n

addition o AVHRR and LandsatTM we are planning o use

test data sets rom the polarizationand directionalityof the

Earth's reflectances POLDER) instrument and the sea-

viewingwide field-of-viewsensor SeaWiFS) nstrumentcor-

respondingo our selected est sites.Postlaunch,he advanced

spacebornehermal emissionand reflectionradiometer (AS-

TER), the multi-angle maging spectroradiometerMISR),

and the Landsat7 EnhancedThematicMapper Plus ETM+)

data will be used duringvalidationcampaigns.Moreover, the

limited numberof test siteswill make t practical o systemat-

ically cross-compare ifferent sensors.MISR will definitely

improve our knowledgeof BRDF and ASTER and Landsat

7/ETM+ shouldenable us to extrapolate ocal ground-based

measurementso the MODIS pixels.

References

Holben, B. N., et al., Automatic Sun and sky scanning adiometer

system or Network Aerosol Monitoring, RemoteSens.Environ., n

press,1997.

Kaufman, Y. J., Solution of the equation of radiative transfer for

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Kaufman, Y. J., D. Tanr6, L. Remer, E. F. Vermote, A. Chu, and B. N.

Holben, Operational remote sensing f tropospheric erosolover

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Kimes, D. S., W. W. Newcomb, R. F. Nelson, and J. B. Schutt, Direc-

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Sciences t Techniquesde Lille, Villeneuve d'Ascq,France.

(ReceivedMarch 21, 1996; revisedDecember3, 1996;

acceptedDecember 3, 1996.)

Documents

Atmospheric Correction of Visible to Middle-Infrared EOS-MODIS Da