Note: This document is for an older version of GRASS GIS that will be discontinued soon. You should upgrade, and read the current manual page.
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
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.
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).
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.
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).
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).
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
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
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.
- 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.
i.atcorr,
i.colors.enhance,
r.mapcalc,
r.in.gdal
Landsat Data Dictionary by USGS
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)
Latest change: Thursday Feb 03 11:10:06 2022 in commit: 547ff44e6aecfb4c9cbf6a4717fc14e521bec0be
Note: This document is for an older version of GRASS GIS that will be discontinued soon. You should upgrade, and read the current manual page.
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GRASS Development Team,
GRASS GIS 8.2.2dev Reference Manual