Provided by: grass-doc_8.3.2-1ubuntu2_all 
NAME
i.landsat.toar - Calculates top-of-atmosphere radiance or reflectance and temperature for Landsat
MSS/TM/ETM+/OLI
KEYWORDS
imagery, radiometric conversion, radiance, reflectance, brightness temperature, atmospheric correction,
satellite, Landsat
SYNOPSIS
i.landsat.toar
i.landsat.toar --help
i.landsat.toar [-rnp] input=basename output=basename [metfile=name] [sensor=string] [method=string]
[date=yyyy-mm-dd] [sun_elevation=float] [product_date=yyyy-mm-dd] [gain=string] [percent=float]
[pixel=integer] [rayleigh=float] [lsatmet=string[,string,...]] [scale=float] [--overwrite]
[--help] [--verbose] [--quiet] [--ui]
Flags:
-r
Output at-sensor radiance instead of reflectance for all bands
-n
Input raster maps use as extension the number of the band instead the code
-p
Print output metadata info
--overwrite
Allow output files to overwrite existing files
--help
Print usage summary
--verbose
Verbose module output
--quiet
Quiet module output
--ui
Force launching GUI dialog
Parameters:
input=basename [required]
Base name of input raster bands
Example: ’B.’ for B.1, B.2, ...
output=basename [required]
Prefix for output raster maps
Example: ’B.toar.’ generates B.toar.1, B.toar.2, ...
metfile=name
Name of Landsat metadata file (.met or MTL.txt)
sensor=string
Spacecraft sensor
Required only if ’metfile’ not given (recommended for sanity)
Options: mss1, mss2, mss3, mss4, mss5, tm4, tm5, tm7, oli8
mss1: Landsat-1 MSS
mss2: Landsat-2 MSS
mss3: Landsat-3 MSS
mss4: Landsat-4 MSS
mss5: Landsat-5 MSS
tm4: Landsat-4 TM
tm5: Landsat-5 TM
tm7: Landsat-7 ETM+
oli8: Landsat_8 OLI/TIRS
method=string
Atmospheric correction method
Options: uncorrected, dos1, dos2, dos2b, dos3, dos4
Default: uncorrected
date=yyyy-mm-dd
Image acquisition date (yyyy-mm-dd)
Required only if ’metfile’ not given
sun_elevation=float
Sun elevation in degrees
Required only if ’metfile’ not given
product_date=yyyy-mm-dd
Image creation date (yyyy-mm-dd)
Required only if ’metfile’ not given
gain=string
Gain (H/L) of all Landsat ETM+ bands (1-5,61,62,7,8)
Required only if ’metfile’ not given
percent=float
Percent of solar radiance in path radiance
Required only if ’method’ is any DOS
Default: 0.01
pixel=integer
Minimum pixels to consider digital number as dark object
Required only if ’method’ is any DOS
Default: 1000
rayleigh=float
Rayleigh atmosphere (diffuse sky irradiance)
Required only if ’method’ is DOS3
Default: 0.0
lsatmet=string[,string,...]
return value stored for a given metadata
Required only if ’metfile’ and -p given
Options: number, creation, date, sun_elev, sensor, bands, sunaz, time
number: Landsat Number
creation: Creation timestamp
date: Date
sun_elev: Sun Elevation
sensor: Sensor
bands: Bands count
sunaz: Sun Azimuth Angle
time: Time
scale=float
Scale factor for output
Default: 1.0
DESCRIPTION
i.landsat.toar is used to transform the calibrated digital number of Landsat imagery products to
top-of-atmosphere radiance or top-of-atmosphere reflectance and temperature (band 6 of the sensors TM and
ETM+). Optionally, it can be used to calculate the at-surface radiance or reflectance with atmospheric
correction (DOS method).
Usually, to do so the production date, the acquisition date, and the solar elevation are needed.
Moreover, for Landsat-7 ETM+ it is also needed the gain (high or low) of the nine respective bands.
Optionally (recommended), the data can be read from metadata file (.met or MTL.txt) for all Landsat MSS,
TM, ETM+ and OLI/TIRS. However, if the solar elevation is given the value of the metadata file is
overwritten. This is necessary when the data in the .met file is incorrect or not accurate. Also, if
acquisition or production dates are not found in the metadata file then the command line values are used.
Attention: Any null value or smaller than QCALmin in the input raster is set to null in the output raster
and it is not included in the equations.
Attention: This module does not respect the current region settings, in order to have the largest
possible sample of pixels from where to get the darkest one of the scene and perform the DOS correction.
To limit the results to a custom region, the user is advised to clip the results (with r.clip, for
instance) or to define the region first, import the images with region cropping, and then running the
module.
Uncorrected at-sensor values (method=uncorrected, default)
The standard geometric and radiometric corrections result in a calibrated digital number (QCAL = DN)
images. To further standardize the impact of illumination geometry, the QCAL images are first converted
first to at-sensor radiance and then to at-sensor reflectance. The thermal band is first converted from
QCAL to at-sensor radiance, and then to effective at-sensor temperature in Kelvin degrees.
Radiometric calibration converts QCAL to at-sensor radiance, a radiometric quantity measured in W/(m² *
sr * µm) using the equations:
• gain = (Lmax - Lmin) / (QCALmax - QCALmin)
• bias = Lmin - gain * QCALmin
• radiance = gain * QCAL + bias
where, Lmax and Lmin are the calibration constants, and QCALmax and QCALmin are the highest and the
lowest points of the range of rescaled radiance in QCAL.
Then, to calculate at-sensor reflectance the equations are:
• sun_radiance = [Esun * sin(e)] / (PI * d^2)
• reflectance = radiance / sun_radiance
where, d is the earth-sun distance in astronomical units, e is the solar elevation angle, and Esun is the
mean solar exoatmospheric irradiance in W/(m² * µm).
Simplified at-surface values (method=dos[1-4])
Atmospheric correction and reflectance calibration remove the path radiance, i.e. the stray light from
the atmosphere, and the spectral effect of solar illumination. To output these simple at-surface radiance
and at-surface reflectance, the equations are (not for thermal bands):
• sun_radiance = TAUv * [Esun * sin(e) * TAUz + Esky] / (PI * d^2)
• radiance_path = radiance_dark - percent * sun_radiance
• radiance = (at-sensor_radiance - radiance_path)
• reflectance = radiance / sun_radiance
where, percent is a value between 0.0 and 1.0 (usually 0.01), Esky is the diffuse sky irradiance, TAUz is
the atmospheric transmittance along the path from the sun to the ground surface, and TAUv is the
atmospheric transmittance along the path from the ground surface to the sensor. radiance_dark is the
at-sensor radiance calculated from the darkest object, i.e. DN with a least ’dark_parameter’ (usually
1000) pixels for the entire image. The values are,
• DOS1: TAUv = 1.0, TAUz = 1.0 and Esky = 0.0
• DOS2: TAUv = 1.0, Esky = 0.0, and TAUz = sin(e) for all bands with maximum wave length less than
1. (i.e. bands 4-6 MSS, 1-4 TM, and 1-4 ETM+) other bands TAUz = 1.0
• DOS3: TAUv = exp[-t/cos(sat_zenith)], TAUz = exp[-t/sin(e)], Esky = rayleigh
• DOS4: TAUv = exp[-t/cos(sat_zenith)], TAUz = exp[-t/sin(e)], Esky = PI * radiance_dark
Attention: Output radiance remain untouched (i.e. no set to 0.0 when it is negative) then they are
possible negative values. However, output reflectance is set to 0.0 when is obtained a negative value.
NOTES
The output raster cell values can be rescaled with the scale parameter (e.g., with 100 in case of using
reflectance output in i.gensigset).
On Landsat-8 metadata file
NASA reports a structure of the L1G Metadata file (LDCM-DFCB-004.pdf) for Landsat Data Continuity Mission
(i.e. Landsat-8).
NASA retains in MIN_MAX_RADIANCE group the necessary information to transform Digital Numbers (DN) in
radiance values. Then, i.landsat.toar replaces the possible standard values with the metadata values. The
results match with the values reported by the metada file in RADIOMETRIC_RESCALING group.
Also, NASA reports the same values of reflectance for all bands in max-min values and in gain-bias
values. This is strange that all bands have the same range of reflectance. Also, they wrote in the web
page as to calculate reflectance directly from DN, first with RADIOMETRIC_RESCALING values and second
divided by sin(sun_elevation).
This is a simple rescaling
• reflectance = radiance / sun_radiance = (DN * RADIANCE_MULT + RADIANCE_ADD) / sun_radiance
• now reflectance = DN * REFLECTANCE_MULT + REFLECTANCE_ADD
• then REFLECTANCE_MULT = RADIANCE_MULT / sun_radiance
• and REFLECTANCE_ADD = RADIANCE_ADD / sun_radiance
The problem arises when we need ESUN values (not provided) to compute sun_radiance and DOS. We assume
that REFLECTANCE_MAXIMUM corresponds to the RADIANCE_MAXIMUM, then
• REFLECTANCE_MAXIMUM / sin(e) = RADIANCE_MAXIMUM / sun_radiance
• Esun = (PI * d^2) * RADIANCE_MAXIMUM / REFLECTANCE_MAXIMUM
where d is the earth-sun distance provided by metadata file or computed inside the program.
The i.landsat.toar reverts back the NASA rescaling to continue using Lmax, Lmin, and Esun values to
compute the constant to convert DN to radiance and radiance to reflectance with the "traditional"
equations and simple atmospheric corrections. Attention: When MAXIMUM values are not provided,
i.landsat.toar tries to calculate Lmax, Lmin, and Esun from RADIOMETRIC_RESCALING (in tests the results
were the same).
Calibration constants
In verbose mode (flag --verbose), the program write basic satellite data and the parameters used in the
transformations.
Production date is not an exact value but it is necessary to apply correct calibration constants, which
were changed in the dates:
• Landsat-1 MSS: never
• Landsat-2 MSS: July 16, 1975
• Landsat-3 MSS: June 1, 1978
• Landsat-4 MSS: August 26, 1982 and April 1, 1983
• Landsat-4 TM: August 1, 1983 and January 15, 1984
• Landsat-5 MSS: April 6, 1984 and November 9, 1984
• Landsat-5 TM: May 4, 2003 and April, 2 2007
• Landsat-7 ETM+: July 1, 2000
• Landsat-8 OLI/TIRS: launched in 2013
EXAMPLES
Metadata file examples
Transform digital numbers of Landsat-7 ETM+ in band rasters 203_30.1, 203_30.2 [...] to uncorrected
at-sensor reflectance in output files 203_30.1_toar, 203_30.2_toar [...] and at-sensor temperature in
output files 293_39.61_toar and 293_39.62_toar:
i.landsat.toar input=203_30. output=_toar \
metfile=p203r030_7x20010620.met
or
i.landsat.toar input=L5121060_06020060714. \
output=L5121060_06020060714_toar \
metfile=L5121060_06020060714_MTL.txt
or
i.landsat.toar input=LC80160352013134LGN03_B output=toar \
metfile=LC80160352013134LGN03_MTL.txt sensor=oli8 date=2013-05-14
DOS1 example
DN to reflectance using DOS1:
# rename channels or make a copy to match i.landsat.toar’s input scheme:
g.copy raster=lsat7_2002_10,lsat7_2002.1
g.copy raster=lsat7_2002_20,lsat7_2002.2
g.copy raster=lsat7_2002_30,lsat7_2002.3
g.copy raster=lsat7_2002_40,lsat7_2002.4
g.copy raster=lsat7_2002_50,lsat7_2002.5
g.copy raster=lsat7_2002_61,lsat7_2002.61
g.copy raster=lsat7_2002_62,lsat7_2002.62
g.copy raster=lsat7_2002_70,lsat7_2002.7
g.copy raster=lsat7_2002_80,lsat7_2002.8
Calculation of reflectance values from DN using DOS1 (metadata obtained from p016r035_7x20020524.met.gz):
i.landsat.toar input=lsat7_2002. output=lsat7_2002_toar. sensor=tm7 \
method=dos1 date=2002-05-24 sun_elevation=64.7730999 \
product_date=2004-02-12 gain=HHHLHLHHL
The resulting Landsat channels are named lsat7_2002_toar.1 .. lsat7_2002_toar.8.
REFERENCES
• Chander G., B.L. Markham and D.L. Helder, 2009: Remote Sensing of Environment, vol. 113
• Chander G.H. and B. Markham, 2003: IEEE Transactions On Geoscience And Remote Sensing, vol. 41,
no. 11.
• Chavez P.S., jr. 1996: Image-based atmospheric corrections - Revisited and Improved.
Photogrammetric Engineering and Remote Sensing 62(9): 1025-1036.
• Huang et al: At-Satellite Reflectance, 2002: A First Order Normalization Of Landsat 7 ETM+
Images.
• R. Irish: Landsat 7. Science Data Users Handbook. February 17, 2007; 15 May 2011.
• Markham B.L. and J.L. Barker, 1986: Landsat MSS and TM Post-Calibration Dynamic Ranges,
Exoatmospheric Reflectances and At-Satellite Temperatures. EOSAT Landsat Technical Notes, No. 1.
• Moran M.S., R.D. Jackson, P.N. Slater and P.M. Teillet, 1992: Remote Sensing of Environment, vol.
41.
• Song et al, 2001: Classification and Change Detection Using Landsat TM Data, When and How to
Correct Atmospheric Effects? Remote Sensing of Environment, vol. 75.
SEE ALSO
i.atcorr, i.colors.enhance, r.mapcalc, r.in.gdal
Landsat Data Dictionary by USGS
AUTHOR
E. Jorge Tizado (ej.tizado unileon es), Dept. Biodiversity and Environmental Management, University of
León, Spain
SOURCE CODE
Available at: i.landsat.toar source code (history)
Accessed: Monday Apr 01 03:09:12 2024
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© 2003-2024 GRASS Development Team, GRASS GIS 8.3.2 Reference Manual
GRASS 8.3.2 i.landsat.toar(1grass)