**Landsat Beta surface reflectance product - April, 2005**

**1. Algorithm Description**

The Landsat surface reflectance product is derived from Top of the
Atmopshere (TOA) reflectance by applying an atmospheric correction
scheme that assumes that: (a) the target is lambertian and infinite and
(b) the gaseous absorption and particle scattering in the atmosphere can
be decoupled. The TOA reflectance can be expressed as:

~TOA~ = T~g~(O3,O2,CO2,NO2,CH4) \[ ~R+A~ + T~R+A~ Tg(H2O) ~s~ / (1 -
S~R+A~ ~s~) \]

Where ~s~ is the surface reflectance, Tg is the gaseous transmission due
to the gases listed between parentheses, T~R+A~ is Rayleigh and aerosol
transmission, ~R+A~ is the Rayleigh and aerosols atmospheric intrinsic
reflectance, and S~R+A~ is the Rayleigh and aerosols spherical albedo.
The transmission, intrinsic reflectance and spherical albedo terms are
computed using the 6S radiative transfer code (Vermote et al., 1997).
The surface pressure, ozone concentration and water vapor content needed
in these computations are determined from the NCEP reanalysis data.

Most available radiative transfer methods for Landsat atmospheric
correction (Vermote et al., 1997; Ouaidrari and Vermote, 1999; Liang et
al., 1997) make use of the dark dense vegetation (DDV) method of Kaufman
et al. (1997) in order to extract aerosol optical thickness from the
imagery. Based on the physical correlation between chlorophyll
absorption and bound water absorption, the DDV method suggests a linear
relation between shortwave-infrared (SWIR) surface reflectance (nearly
unaffected by the atmosphere) and surface reflectance in the blue and
red bands. Using this relation to calculate surface reflectance for the
visible bands, and comparing the result to the TOA reflectance, we

may estimate aerosol optical depth.

Specifically, the aerosol optical thickness used in the LEDAPS
atmospheric correction process is retrieved from Landsat data using
simulated reflectance Look up tables (LUTs) and an estimate of the
surface reflectance in the blue band. A continental aerosol model is
then applied through the blue AOT retrieval. The LUTs are computed for
each scene using the 6S code, the scene geometry and NCEP ancillary
data. The estimate of the blue band reflectance is determined for a 1km
x 1km grid cell as a function of the reflectance in the2.2 m band (band
7) using the Kaufman et al (1997) approach. Figure 1 illustrates the
high correlation the surface reflectance in the blue band and the SWIR
reflectance. The blue band was corrected for atmospheric effects using
the aerosol optical thickness measured by AERONET.

![](media/image1.wmf){width="5.251388888888889in"
height="4.9222222222222225in"}

Fig.1: Relation between the ETM+ blue and SWIR reflectances.

**2. Validation**

Four approaches are being used to validate Landsat surface reflectance
(SR) products:

1.  comparison with near-simultaneous (15 minutes apart) MODIS 500m
    single-swath surface reflectance data.

2.  comparison of Landsat aerosol optical thickness with that obtained
    by simultaneous AERONET sun photometer network observations.

3.  comparison of Landsat surface reflectance with independent surface
    reflectance retrievals using helicopter or ultralight based
    radiometers, within10 days of Landsat acquisition (e.g. BOREAS, SNF
    helicopter MMR data).

4.  examination of temporal stability of invariant targets across
    multiple acquisitions.

For the Beta release of the Landsat surface reflectance product, only
the first two

validation tasks have been attempted, on a limited geographic basis.

[2.1. Comparison with Aeronet Aerosol Optical Thickness]{.underline}

Aerosol Robotic Network (AERONET) sites record aerosol properties
throughout the world, and several of these records extend back to the
early 1990's (Holben et al., 1998). The Beta SR dataset includes several
AERONET sites, and observations from 21 of these sites were compared
with simultaneous aerosol optical thickness obtained using the
image-based approach discussed above (Table 1, Fig. 2).

All AOT values reported are for the blue wavelengths. Results suggest
reasonable agreement with AERONET observations. Spatial patterns for the
sites suggest that land cover type may influence the aerosol retrievals
(Fig. 3), although this effect is suppressed compared to earlier
versions of the product.

For comparison, uncertainties in MODIS land AOT retrievals is (0.05 +
0.2\*AOT), which have also been plotted on Fig. 2.

  ----------------------- ------------- ----------- ----------- ----------
  **AERONET Site**        **TM Scene**  **Date**    **AOT blue  **AOT blue
                                                    Aeronet**   ETM**

  Howland                 p011r029      2002253     0.4         0.1767

  GSFC                    p015r033      2001278     0.25        0.257

  MD_Science_Center       p015r033      2001278     0.29        0.414

  SERC                    p015r033      2001278     0.25        0.294

  BSRN_BAO_Boulder        p033r032      2000261     0.05        0.024

  Sevilleta               p034r036      2000130     0.12        0.135

  Bratts_Lake             p035r025      2000208     0.2         0.161

  Bratts_Lake             p036r025      2001217     0.08        0.026

  Maricopa                p036r037      2000167     0.09        0.1889

  Tucson                  p036r037      2000167     0.11        0.056

  UCLA                    p041r036      2000122     0.2         0.275

  Shirahama               p109r037      2001105     0.3         0.344

  Anmyon                  p116r035      2001266     0.11        0.156

  Moscow_MSU_MO           p179r021      2002150     0.17        0.059

  Rome_Tor_Vergata        p191r031      2001215     0.49        0.384

  Ilorin                  p191r054      2000037     1.05        0.921

  Ouagadougou             p195r051      2001195     0.275       0.346

  Lille                   p199r025      2000237     0.29        0.38

  Palaiseau               p199r026      2000237     0.22        0.156

  Thompson                p033r021      2001260     0.06        0.033

  HJAndrews               p045r029      1999275     0.08        0.033
  ----------------------- ------------- ----------- ----------- ----------

Table 1: AERONET and ETM+ AOT comparisons

![](media/image2.wmf){width="4.686111111111111in"
height="3.415277777777778in"}

Fig. 2: ETM+ AOT values regressed against simultaneous AERONET AOT
values for the blue band. Solid red line is the one-to-one line, dashed
lines represent MODIS AOT uncertainties of (0.05+0.2\*AOT).

![](media/image3.jpeg){width="1.3271653543307087in"
height="1.3271653543307087in"}![](media/image4.jpeg){width="1.3271653543307087in"
height="1.3271653543307087in"}![](media/image5.jpeg){width="1.3271653543307087in"
height="1.3271653543307087in"}![](media/image6.jpeg){width="1.3271653543307087in"
height="1.3137795275590551in"}![](media/image7.jpeg){width="1.3251968503937008in"
height="1.3251968503937008in"}![](media/image8.jpeg){width="1.3251968503937008in"
height="1.3251968503937008in"}![](media/image9.jpeg){width="0.21181102362204723in"
height="1.3263779527559054in"}![](media/image10.jpeg){width="1.3251968503937008in"
height="1.3251968503937008in"}![](media/image11.jpeg){width="1.3271653543307087in"
height="1.3236220472440945in"}![](media/image12.jpeg){width="1.3244094488188976in"
height="1.3251968503937008in"}![](media/image13.jpeg){width="1.3236220472440945in"
height="1.3271653543307087in"}![](media/image14.jpeg){width="1.3251968503937008in"
height="1.3251968503937008in"}![](media/image15.jpeg){width="1.3236220472440945in"
height="1.3271653543307087in"}

Fig. 3. TOA reflectance, atmospherically corrected surface reflectance,
and AOT (blue wavelengths) for the AERONET sites used in the study.

[2.2. Comparisons with MODIS]{.underline}

MODIS 500m Surface Reflectance (SR) products were processed from
individual swaths,and registered with Landsat-7 ETM+ SR products from
images acquired within 15 minutes. The Landsat SR products were
aggregated to 500m resolution by averaging blocks of pixels. For one
scene in Canada (BOREAS study region), three sub-windows from each
dataset were extracted and compared (Fig. 4).

Plotting histograms before and after correction for each sub-window
suggests that, for most spectral bands, differences between MODIS and
ETM+ SR values are negligible (Figs. 5,6,7). One exception is the blue
band, where ETM+ SR values trend \~1% higher than the comparable MODIS
band.

For two sub-windows, some differences also exist for the shortwave
infrared (1.m) band, although the spread of the data distribution makes
it difficult to detect a consistent trend.

**3. Evaluation and Known Issues**

As noted elsewhere, Beta products are intended primarily for users to
become familiar with data formats and general product characteristics,
and to feed further validation efforts. Without further validation, it
is not recommended to use Beta products for scientific use.
Nevertheless, the initial results presented here suggest that the
atmospheric correction approach is producing reasonably accurate surface
reflectance values, and is certainly improving the radiometric accuracy
and stability of the data compared to top-of-atmosphere products.

Known issues to emerge from our analyses (to be corrected in future
releases) include:

1.  Cloud/snow/ice mask is prone to errors. For the Beta release the
    snow/ice bits in the QA mask have been zeroed.

2.  Landsat AOT retrievals are prone to adjacency effects (scattered
    radiance into dark target locations from surrounding bright
    targets).

3.  Landsat blue band SR too high (undercorrected)

4.  The calibration of bands 1 and 2 of Landsat 5 is suboptimal.

![](media/image16.jpeg){width="2.8625in" height="2.5993055555555555in"}

Fig. 4. BOREAS ETM+ scene (top-of-atmosphere Œ TOA and SR) with
locations of sub-windows for comparison with MODIS surface reflectance.

![](media/image18.png){width="1.9015748031496063in"
height="1.7992125984251968in"}![](media/image19.png){width="1.9015748031496063in"
height="1.800787401574803in"}![](media/image20.png){width="1.9019685039370078in"
height="1.800787401574803in"}![](media/image21.png){width="1.9015748031496063in"
height="1.800787401574803in"}![](media/image22.png){width="1.9019685039370078in"
height="1.800787401574803in"}

Fig. 5: Histograms of Landsat TOA reflectance (red), MODIS surface
reflectance (blue) and Landsat surface reflectance (green) for the
following bands: blue (upper-left), green (upper-center), red
(upper-right), near-infrared (lower-left), mid-infrared (lower-right)

![](media/image23.png){width="1.9366141732283464in"
height="1.8338582677165354in"}![](media/image24.png){width="1.9362204724409449in"
height="1.8338582677165354in"}![](media/image25.png){width="1.9366141732283464in"
height="1.8338582677165354in"}![](media/image26.png){width="1.9362204724409449in"
height="1.8338582677165354in"}![](media/image27.png){width="1.9362204724409449in"
height="1.8334645669291338in"}

Fig. 6: Same as Fig 5, for Subwindow 2

![](media/image28.png){width="1.9366141732283464in"
height="1.8326771653543308in"}![](media/image29.png){width="1.9362204724409449in"
height="1.8326771653543308in"}![](media/image30.png){width="1.9366141732283464in"
height="1.8326771653543308in"}![](media/image31.png){width="1.9362204724409449in"
height="1.8334645669291338in"}![](media/image32.png){width="1.9362204724409449in"
height="1.8334645669291338in"}

Fig. 7: Same as Fig. 5, for Subwindow 3

**4. References**

Kaufman, Y.J., Wald, A.E., Remer, L.A. et al., 1997, The MODIS
2.1-micron channel Œ correlation with visible reflectance for use in
remote sensing of aerosol, IEEE Trans. Geosci. Remote Sens., 35,
1286-1296.

Liang, S., Fallahdal, H., Kalluri, S., et al., 1997, An operational
atmospheric correction algorithm for Landsat Thematic Mapper imagery
over the land, J. Geophys. Res., 102, 17,173-17,186.

Ouaidrari, H., and Vermote, E.F., 1999, Operational atmospheric
correction of Landsat TM data, Remote Sens. Environ., 70, 4-15.

Vermote, E.F., et al., 1997, Atmospheric correction of visible to
middle-infrared EOS-MODIS data over land surfaces: Background,
operational algorithm, and validation, J. Geophys. Res., 102, 17131-
17141.