A fast atmospheric correction algorithm applied to landsat tm images

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A fast atmospheric correction algorithm applied to
Landsat TM images
RUDOLF RICHTER a
a DLR, German Aerospace Research Establishment, Institute for Optoelectronics , D-8031
Wessling, F.R, Germany
Published online: 07 May 2007.
To cite this article: RUDOLF RICHTER (1990) A fast atmospheric correction algorithm applied to Landsat TM images,
International Journal of Remote Sensing, 11:1, 159-166, DOI: 10.1080/01431169008955008
To link to this article: http://dx.doi.org/10.1080/01431169008955008
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INT. J. REMOTE SENSING, 1990, VOL. II, NO. 1,159-166
A fast atmospheric correction algorithm applied to Landsat TM images
RUDOLF RICHTER
DLR, German Aerospace Research Establishment, Institute for Optoelectronics,
D-8031 Wessling, F.R. Germany
(Received 6 June 1989; injinalform 28 July 1989)
Abstract. A fast atmospheric correction algorithm for the reflective bands
(0·4-2·Slim) of remote sensing instruments is presented. It proceeds in two steps:
(1) calculation of the ground reflectance of each pixel based on precomputed
planetary albedo functions for different standard atmospheres, aerosol types and
optical depths, or actual atmospheric measurement data (e.g. radiosonde), (2)
approximate correction of the adjacencyeffectby taking into account the average
reflectance in an N x N pixel neighbourhood and using appropriate weighting
functions for the difference in reflectance. The correction functions are provided
by the models LOWTRAN-7 and SENSAT-3.
I. Introduction
Spaceborne optical sensors recording from the visible to the short wave infrared
spectrum (0·4-2·5/lm) receive solar radiance reflected at the Earth's surface and
scattered by the atmosphere. The task of land and ocean observing sensors is the
mapping of surface reflectance. Since the atmosphere modifies the radiance reflected
at the ground and contributes an additive path radiance term, it is necessary to correct
the atmospheric effect to retrieve the surface reflectance.
Atmospherically corrected surface reflectance images improve the accuracy of
surface type classification (Kaufman 1985) and Earth reflectance data are also a basis
for estimating the radiation budget of the Earth (Kimes and Sellers 1985).
Similar aspects as discussed here are also treated by Kaufman (1985) and Kim
(1988). However, they are working with the monochromatic centre band wavelength,
whereas this Letter takes into account the wavelength dependence of atmospheric
parameters and the sensor spectral response function. The correction functions of the
algorithm are precomputed by using the models LOWTRAN-7 (Kneizys et al. 1988,
Isaacs et al. 1987) and SENSAT-3 (Richter 1989).
To enable the immediate processing of Landsat Thematic Mapper (TM) images a
catalogue of atmospheric correction functions for TM bands 1-5 and 7 has been
compiled for different standard atmospheres, aerosol types, solar zenith angles and
ground altitudes (0, 0·5, I km above sea level). These ground altitudes (corresponding
to pressure levels of 1013, 956, and 902 mbar, respectively, of LOWTRAN standard
atmospheres) were selected to account for the pressure dependence of the Rayleigh
optical depth for places of different elevation. The catalogue is especially useful, when
no atmospheric data are available and one has to resort to average climatological
atmospheres, e.g. a mid-latitude summer atmosphere. If the TM scene contains
known reference targets (e.g., lakes, concrete runways) different types of aerosol can
be selected (e.g., rural, urban, based on LOWTRAN) and the visibility (i.e. aerosol
concentration) can be varied until the reflectance of the target is matched.
0143-1161/90 $3.00 © 1990 Taylor & Francis Ltd
Downloaded by [University of Leeds] at 08:15 19 August 2014

160 R. Richter
Ofcourse, the error in the retrieved surface reflectance will be less, when measured
atmospheric data (e.g., radiosonde) are available. However, even in the worst case,
when the scene contains no reference target and climatological average atmospheric
parameters are taken, a first rough estimate of surface reflectance can readily be
obtained with the proposed algorithm and might be a valuable information.
2. Atmospheric correction algorithm
The first step of the algorithm compares measured and model-derived planetary
(Earth/atmosphere) albedos to calculate the surface reflectance. The measured
planetary albedo Ppis related to the digital number (DN) in channel i (Markham and
Barker 1985):
7tL(Ai)d
2
pp(Measurement)
Es(A,) cos Os
(I)
where L(A,), Es(Ai ) , co(i) and c1(i) are spectral radiance, extraterrestrial solar irradiance,
offset and slope of calibration coefficients, respectively, Ai is the centre
wavelength, Os is the solar zenith angle and d is the Earth-Sun distance in astronomical
units.
The model-derived planetary albedo is given below (equations (4)-(6». The model
first calculates the solar radiance reflected from a uniform Lambert surface of
reflectance p(A), which is received by a spaceborne sensor (Kaufman 1985)
(2)
where Lo, Ea, Tdir, Tdir are path radiance for a black ground (p = 0), global irradiance
on the ground and direct and diffuse transmittance (ground to sensor), respectively.
Model LOWTRAN-7 calculates the path radiance Lp in the form
Lp(A) = Lo(A)+Ea(A) p(A)Tdir(A) (3)
7t
Thus, Lo(A) can be obtained by a LOWTRAN run with p = O. The term Tdir, which is
needed in the second step of the algorithm, can then be evaluated from equation (3).
The model-derived planetary albedo is now calculated with band-integrated
terms:
pp(Model)= ao(Atm, 0., OS' cp)+a,(Atm, 0., Os) x P (4)
(5)
(6)
d 2 fA' (A)Lo(A)dA
7t A,
a
o
cos«""'f""::=--(-A)-E-s(A-)-dA-d?
fA' (A)EiA)[Tdi,(A) +Tdir(A)]dA
A,
a
l
= cos e, fA' (A) Es(A)dA
A,
where p is the average in-band surface reflectance (p "'" Jp(A)(A)dA), Atm indicates
the dependence on atmospheric parameters, 0. is the sensor view angle, cp is the
relative azimuth angle and is the normalized spectral response function of the

Remote Sensing Letters 161
sensor. If the measured planetary albedo (equation (I» agrees with the model-derived
value (equation (4)-(6) the first step of the algorithm yields the surface reflectance p(l):
(7)
(8)
(9)
(II)
p(l)=I_ [ Cn)d? () {co(i)+c,(i)xDN}-a ] a o l E, A.i cos s
2.1. Approximate correction of the adjacency effect
The second step of the algorithm computes the average reflectance in an N x N
pixel window centred on the considered pixel:
I N2
P(l)=-2 2: p?)
N j~l
The model-derived reflectance pel) of equation (7) is based on the assumption of a
Lambertian ground (see equation (2», whereas the measurement (equation (1»
actually consists of the direct reflected radiance from the pixel with surface reflectance
p and the diffuse background reflectance pel) from the neighbourhood
L(A) = Lo(A)+E.(A) P(,()'di.(A) +E.(A) p(l)(,()'dif(,()
n n
Comparing equations (2) and (9) one obtains p(l)('di'+'dif) =P'di'+P(l)'dif, from
which the final surface reflectance p=p(2) results:
p(2)=p(I)+q(p(l)_p(l)) (10)
where
q=f.2 'dif(,() ('()d'(
., 'di'(,()
The appropriate window size, N, in equation (8) depends on the pixel size, the
atmospheric parameters, the spectral band and the spatial frequencies of the scene
itself (Kaufman 1985). This aspect is discussed in §4.
3. TM version of the atmospheric correction algorithm
Two simplifying assumptions were made for the TM version of the algorithm:
(I) The relative azimuth angle dependence of the path scattered radiance is
neglected for the standard catalogue, because the largest off-nadir angle of
TM is 7'5°. All radiances of the catalogue are evaluated for the nadir view.
The evaluation of Landsat TM subscenes with actual atmospheric data is
made with the sensor view angle and relative azimuth angle corresponding to
the centre of the image.
(2) The function a, of equation (6) depends on the global irradiance E., which
itself depends to some extent on the ground albedo. The subsequent results are
based on a ground albedo of 30 per cent for al to minimize reflectance errors
in the 10-40 per cent region.
Table I summarizes the absolute surface reflectance errors for the TM bands due
to these assumptions, assuming the standard mid-latitude summer atmosphere with
an urban aerosol content.
All bands are treated independently using the same atmospheric parameters. The
choice of the ground albedo to calculate E. can be selected independently for each

162 R. Richter
Table I. Maximum absolute reflectance errors for TM due to model approximations as a
function of surface reflectance.
Absolute reflectance error (per cent)
Ground Band I Band 2 Band 3 Band 4
reflectance
(per cent) 0' 7' 0' 7' 0' 7' 0' 7'
5 0·5 3 0·5 1·5 0·5 0·5 0·5 0·5
30 0 2·5 0 0·5 0 0·5 0 0
70 3 3 2 2 2 2 2 2
Angle 0'; nadir view, angle 7'; off-nadir view.
Atmospheric parameters: mid-latitude summer (LOWTRAN) atmosphere, urban aerosol
content, visibility range 5-40km, solar zenith angle range 30'-60'.
For TM bands 5 and 7 the reflectance error is <0·7 and 0·5 per cent, respectively.
band. It can thus be adapted to the reflectance level of a particular scene and will
improve the accuracy of the ground reflectance image. Of course, the method also
depends on the sensor calibration accuracy, i.e. on the correct values coU), cIU) for
each band i(Slater et af. 1987).
Due to the simplifying assumptions, a fast atmospheric correction algorithm is
created. For an image size of 512 x 512 pixels the first step of the algorithm requires
one minute execution time per channel on a personal computer with a 386 processor.
The second step of the algorithm also requires one minute execution time per channel
(without the low pass filter image of p(l).
Figure 1 shows the functions ao, a l and q for TM bands 1 and 5 for the midlatitude
summer atmosphere, an urban aerosol (6 visibilities) and a range of solar
zenith angles. Function ao (the planetary albedo for the ground reflectance zero,
ranging from 0 to I) is about an order of magnitude lower in band 5 than the
corresponding values in band I, which is to be expected. The same applies to the
function q, which is a measure of the strength of the adjacency effect. Thus, the
adjacency effect plays a minor role in TM bands 5 and 7 and can usually be neglected
in these bands (Tame et af. 1987).
4. Atmospheric correction of a TM scene of Munich
A single date scene is selected to keep this Letter within the page limits. The full
potential of the method can best be exploited for multitemporal scenes (radiometric
normalization), which will be the topic of a forthcoming paper.
Figure 2 shows the results of processing Landsat-5 TM bands 1,2 and 3 of a scene
of Munich dated 9 July 1984. Atmospheric data were measured by a radiosonde up to
an altitude of 13km. Data of the altitude region 13-IOOkm were taken from the
LOWTRAN mid-latitude summer atmosphere. The urban boundary layer aerosol
type was selected at a visibility of 15km. This choice is the result of several visibility
iterations: for dark targets (e.g. lakes) an incorrect visibility can lead to negative
reflectance values. The rural aerosol was also tested and found to be inadequate, since
its higher path radiance leads to negative reflectance values for dark targets of the
scene. The selected aerosol type is in accord with the wind direction (blowing from
south on this day), thus providing an urban type of aerosol to the centre and north of
the city..

1.2 f----=~
1.0 ,"'=::=-I-o--P~-t-----1
O.B
",-~o...
q 0.6 f==t=:::Jc):::::i'~
0.4 r--~-+==f:::::-9
0.14
0.12
0.10
O.OB
q 0.06
0.04
1 - r----
2 ~
3 ~=::::::::
_4 _I ----r--- 5 I I
6 I I
G,
30 40 50 60 70
SOLAR ZENITH ANGLE (DEGREE) --
0.6 r----t-=-..k
0.2 f-------F"'--.ol:::
30 40 SO 60 70
SOLAR ZENITH ANGLE (DEGREE) -
30 40 50 60 70
0.7 r====t--=P",---J;::::O--c--I
0, 0.5 f------I-------;f"-..~-l_'~~
0.4 ----I----!----""-.---i '-_---'---_----.J'-_---'---_---"JI
30 40 50 60 70
0.1 4 1----j---f-------t-~y71
0.1 2 f---I---f--::7'7"7-'-
O.OB
I::::::;:::d=:::::::
30 40 50 60 70
0.015 f---I---f---I--r-----7I
Figure I. Atmospheric correction functions for TM band 1 (left) and band 5 (right).
Atmosphere, mid-latitude summer; aerosol, urban; ground at sea level. Visibilities: (I)
=5 km, (2)=7 km, (3)= IOkm, (4)= 15km, (5)=23 km, (6)=40km.
Figure 2 (a) shows the original image and figure 2 (b) the colour-coded reflectance
image of the first step of the algorithm using the TM band i( i = 1, 2, 3) calibration
coefficients co(i) and c, (i) (Price 1989). Figure 2 (c) displays a reflectance image which
approximatley accounts for the adjacency effect. It is distinctly superior to figure 2 (b).
The appropriate window size, N, for the correction of the adjacency effect was found
to be in the range 7-35 pixels; i.e. about 100-500 m to either side of a pixel. At the first
glance, this is a surprising result since the aerosol scale height (and thus the effective
scattering range) is about 1-2 km (Kaufman 1985). However, this is based on the
assumption of a large homogeneous surface (several times the length of the scale
height). Since the Munich scene consists of many small fields of different reflectances,
the effective range of the adjacency effect is reduced to about 100-500 m. Reflectance
values of the pixels in the Munich scene generally change less than I per cent, when
the N = 7 window is used instead of the N = 35 window, which saves computer time
for the calculation of the low pass filter image.
An exception is demonstrated by the 6 per cent reflectance of a lake target in
band 4 (see table 2) at a 7 x 7 pixels window size. The 35 x 35 pixels window, i.e. about

164 R. Richter
(a)
(b) (c)
Figure 2. Landsat-S Thematic Mapper scene of Munich (9 July 1984), bands I, 2 and 3.
(a) original scene, (b) ground reflectance image (step I) and (e) ground reflectance image
(step 2) corrected for adjacency effect. RGB colour coding: red = band 3, green= band
2, blue=band I.
I x I km", reduces the reflectance at the centre of the lake to I per cent. This reflectance
value is also confirmed by the following consideration: the lake (diameter 0·5 km) is
surrounded for several kilometres by agricultural fields with reflectance values of
30-50 per cent in TM band 4. A calculation with models SENSAT-3 and
LOWTRAN-7, using the approximate equations of Tanre et al. (1981), shows a 5 per
cent increase in TM band 4 reflectance for a target (diameter 0·5 km) of I per cent
reflectance, which is surrounded by a homogeneous background of 40 per cent
reflectance. Thus a I per cent reflectance value of the lake in TM band 4 is increased to
an apparent 6 per cent by the adjacency effect.

Table 2. Surface reflectance calculated for several targets.
Surface reflectance (per cent) in TM bands
Target 2 3 4 5 7
Lake 4 6 2 6 I 1
Meadow 4 8 5 41 24 13
Coniferous 4 5 3 26 9 4
Concrete (runway) 20 20 20 31 31 30
A window of 7 x 7 pixels is assumed for the adjacency correction.
Table 2 shows retrieved reflectance values for several targets. The comparison
with values given in the literature is difficult, since the reflectance range of natural
targets (e.g., meadow) is rather large and there is the possibility of mixed signatures.
Therefore, a comparison with simultaneous ground measurements is planned for the
future.
5. Summary
A fast atmospheric correction algorithm for the reflective solar spectrum is
presented, which approximately accounts for the adjacency effect. The algorithm
transforms the original radiance image into a reflectance image.
A catalogue of atmospheric correction functions has been compiled for Landsat
TM for different standard atmospheres, solar zenith angles, ground altitudes,
aerosol types and visibilities. In many cases the catalogue enables the quasioperational
conversion of TM radiance images into reflectance images. If the scene
contains reference targets of known reflectance, a check of the correctness of the
selected atmospheric parameters is possible. The catalogue will be extended to include
the SPOT HRV (High Resolution Visible) sensor (Begni 1982).
Acknowledgment
I thank the referees for their helpful comments.
References
BEGNl, G., 1982, Selection of the optimum spectral bands for the SPOT satellite. Photogrammetric
Engineering and Remote Sensing, 48,1613-1620.
ISAACS, R. G., WANG, W. c., WORSHAM, R. D., and GOLDENBERG, S., 1987, Multiple scattering
LOWTRAN and FASCODE models. Applied Optics, 26, 1272-1281.
KAUFMAN, Y. J., t985, The atmospheric elTect on the separability offield classes measured from
satellites. Remote Sensing ojEnvironment, 18, 21-34.
KIM, H. H., 1988, Atmospheric Effect Removal from Space Imagery, ESA SP-287, 193-196
(Paris: European Space Agency).
KIMES, D. S., and SELLERS, P. J., 1985, Inferring hemispherical reflectance of the Earth's surface
for global energy budgets from remotely sensed nadir or directional radiance values.
Remote Sensing of Environment, 18,205-223.
KNElZYS, F. X., SHElTLE, E. P., ABREU, L. W., CHETWYND, J. H., ANDERSON, G. P., GALLERY,
W.O., SELBY, J. E. A., and CLOUGH, S. A., 1988, Users' Guide to LOWTRAN-7.
AFGL-TR-88-0177, Air Force Geophysics Laboratory, Bedford, Massachusetts, U.S.A.
MARKHAM, B. L., and BARKER, J. L., 1985, Spectral characterization of the LANDSAT
Thematic Mapper sensors. International Journal ojRemote Sensing, 6, 697-716.
PRICE, J. C,; 1989, Calibration comparison for the Landsat 4 and 5 multispectral scanners and
thematic mappers. Applied Optics, 28,465-471.

166 Remote Sensing Letters
RICHTER, R., 1989, Model SENSAT-3, DLR-IB 552/06-89, German Aerospace Research
Establishment, Wessling, F.R. Germany.
SLATER, P. N., BIGGAR, S. F., HOLM, R. G., JACKSON, R. D., MAO,Y., MORAN, M. S., PALMER,
J. M., and YUAN, B., 1987, Reflectance- and radiance-based methods for the in-flight
absolute calibration of multispectral sensors. Remote Sensing ofEnvironment, 22,11-37.
TANRE, D., DESCHAMPS, P. Y., DUHAUT, P., and HERMAN, M., 1987, Adjacency effect produced
by the atmospheric scattering in Thematic Mapper data. Journal of Geophysical
Research,92, 12000-12006.
TANRE, D., HERMAN, M., and DF.5CHAMPS, P. Y., 1981, Influence of the background contribution
upon space measurements of ground reflectance. Applied Optics, 20. 3676-3684.

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