Provided by: grass-doc_6.4.3-3_all 
NAME
i.atcorr - Performs atmospheric correction using the 6S algorithm.
6S - Second Simulation of Satellite Signal in the Solar Spectrum.
KEYWORDS
imagery, atmospheric correction
SYNOPSIS
i.atcorr
i.atcorr help
i.atcorr [-frabo] iimg=name [iscl=min,max] [ialt=name] [ivis=name] icnd=name oimg=name
[oscl=min,max] [--overwrite] [--verbose] [--quiet]
Flags:
-f
Output raster is floating point
-r
Input map converted to reflectance (default is radiance)
-a
Input from ETM+ image taken after July 1, 2000
-b
Input from ETM+ image taken before July 1, 2000
-o
Try to increase computation speed when altitude and/or visibility map is used
--overwrite
Allow output files to overwrite existing files
--verbose
Verbose module output
--quiet
Quiet module output
Parameters:
iimg=name
Name of input raster map
iscl=min,max
Input imagery range [0,255]
Default: 0,255
ialt=name
Input altitude raster map in m (optional)
ivis=name
Input visibility raster map in km (optional)
icnd=name
Name of input text file
oimg=name
Name for output raster map
oscl=min,max
Rescale output raster map [0,255]
Default: 0,255
DESCRIPTION
i.atcorr performs atmospheric correction on the input raster map using the 6S algorithm (Second
Simulation of Satellite Signal in the Solar Spectrum). A detailed algorithm description is available at
the Land Surface Reflectance Science Computing Facility website.
Important note: Current region settings are ignored! The region is adjusted to cover the input raster map
before the atmospheric correction is performed. The previous settings are restored afterwards.
Because using a elevation and/or visibility raster map makes execution time much longer, it is advised to
use the optimization flag -o. This flag tells i.atcorr to try and speedup calculations. However, this
option will increase memory requirements.
If flag -r is used, the input raster data are treated as reflectance. Otherwise, the input raster data
are treated as radiance values and are converted to reflectance at the i.atcorr runtime. The output data
are always reflectance.
Note that the satellite overpass time has to be specified in Greenwich Mean Time (GMT).
An example 6S parameters:
8 - geometrical conditions=Landsat ETM+
2 19 13.00 -47.410 -20.234 - month day hh.ddd longitude latitude ("hh.ddd" is in decimal hours GMT)
1 - atmospheric mode=tropical
1 - aerosols model=continental
15 - visibility [km] (aerosol model concentration)
-0.600 - mean target elevation above sea level [km] (here 600m asl)
-1000 - sensor height (here, sensor on board a satellite)
64 - 4th band of ETM+ Landsat 7
If the position is not available in longitude-latitude (WGS84), the m.proj conversion module can be used
to reproject from a different projection.
6S CODE PARAMETER CHOICES
A. Geometrical conditions
| Code | Description | Details
| 1 | meteosat observation | enter month,day,decimal hour (universal time-hh.ddd)
n. of column,n. of line. (full scale 5000*2500)
| 2 | goes east observation | enter month,day,decimal hour (universal time-hh.ddd)
n. of column,n. of line. (full scale 17000*12000)c
| 3 | goes west observation | enter month,day,decimal hour (universal time-hh.ddd)
n. of column,n. of line. (full scale 17000*12000)
| 4 | avhrr (PM noaa) | enter month,day,decimal hour (universal time-hh.ddd)
n. of column(1-2048),xlonan,hna
give long.(xlonan) and overpass hour (hna) at
the ascendant node at equator
| 5 | avhrr (AM noaa) | enter month,day,decimal hour (universal time-hh.ddd)
n. of column(1-2048),xlonan,hna
give long.(xlonan) and overpass hour (hna) at
the ascendant node at equator
| 6 | hrv (spot) | enter month,day,hh.ddd,long.,lat. *
| 7 | tm (landsat) | enter month,day,hh.ddd,long.,lat. *
| 8 | etm+ (landsat7) | enter month,day,hh.ddd,long.,lat. *
| 9 | liss (IRS 1C) | enter month,day,hh.ddd,long.,lat. *
| 10 | aster | enter month,day,hh.ddd,long.,lat. *
| 11 | avnir | enter month,day,hh.ddd,long.,lat. *
| 12 | ikonos | enter month,day,hh.ddd,long.,lat. *
| 13 | RapidEye | enter month,day,hh.ddd,long.,lat. *
| 14 | VGT1 (SPOT4) | enter month,day,hh.ddd,long.,lat. *
| 15 | VGT2 (SPOT5) | enter month,day,hh.ddd,long.,lat. * * NOTE: for HRV, TM, ETM+, LISS and ASTER
experiments, longitude and latitude are the coordinates of the scene center. Latitude must be > 0 for
northern hemisphere and < 0 for southern. Longitude must be > 0 for eastern hemisphere and < 0 for
western.
B. Atmospheric model
| Code | Meaning
| 0 | no gaseous absorption
| 1 | tropical
| 2 | midlatitude summer
| 3 | midlatitude winter
| 4 | subarctic summer
| 5 | subarctic winter
| 6 | us standard 62
| 7 | Define your own atmospheric model as a set of the following 5 parameters per each measurement:
altitude [km]
pressure [mb]
temperature [k]
h2o density [g/m3]
o3 density [g/m3]
For example: there is one radiosonde measurement for each altitude of 0-25km at a step of 1km, one
measurment for each altitude of 25-50km at a step of 5km, and two single measurements for altitudes 70km
and 100km. This makes 34 measurments. In that case, there are 34*5 values to input.
| 8 | Define your own atmospheric model providing values of the water vapor and ozone content:
uw [g/cm2]
uo3 [cm-atm]
The profile is taken from us62.
C. Aerosols model
| Code | Meaning | Details
| 0 | no aerosols |
| 1 | continental model |
| 2 | maritime model |
| 3 | urban model |
| 4 | shettle model for background desert aerosol |
| 5 | biomass burning |
| 6 | stratospheric model |
| 7 | define your own model | Enter the volumic percentage of each component:
c(1) = volumic % of dust-like
c(2) = volumic % of water-soluble
c(3) = volumic % of oceanic
c(4) = volumic % of soot
All values between 0 and 1.
| 8 | define your own model | Size distribution function: Multimodal Log Normal (up to 4 modes).
| 9 | define your own model | Size distribution function: Modified gamma.
| 10 | define your own model | Size distribution function: Junge Power-Law.
| 11 | define your own model | Sun-photometer measurements, 50 values max, entered as:
r and d V / d (logr)
where r is the radius [micron], V is the volume, d V / d (logr) [cm3/cm2/micron].
Followed by:
nr and ni for each wavelength
where nr and ni are respectively the real and imaginary part of the refractive index.
D. Aerosol concentration model (visibility)
If you have an estimate of the meteorological parameter visibility v, enter directly the value of v [km]
(the aerosol optical depth (AOD) will be computed from a standard aerosol profile).
If you have an estimate of aerosol optical depth, enter 0 for the visibility and in a following line
enter the aerosol optical depth at 550nm (iaer means 'i' for input and 'aer' for aerosol), for example:
0 - visibility
0.112 - aerosol optical depth 550 nm
NOTE: if iaer is 0, enter -1 for visibility.
E. Target altitude (xps), sensor platform (xpp)
Target altitude (xps, in negative [km]): xps >= 0 means the target is at the sea level.
otherwise xps expresses the altitude of the target (e.g., mean elevation) in [km], given as negative
value
Sensor platform (xpp, in negative [km] or -1000):
xpp = -1000 means that the sensor is on board a satellite.
xpp = 0 means that the sensor is at the ground level.
-100 < xpp < 0 defines the altitude of the sensor expressed in [km]; this altitude is given relative to
the target altitude as negative value.
For aircraft simulations only (xpp is neither equal to 0 nor equal to -1000): puw,po3 (water vapor
content,ozone content between the aircraft and the surface)
taerp (the aerosol optical thickness at 550nm between the aircraft and the surface)
If these data are not available, enter negative values for all of them. puw,po3 will then be
interpolated from the us62 standard profile according to the values at the ground level. taerp will be
computed according to a 2km exponential profile for aerosol.
F. Sensor band
There are two possibilities: either define your own spectral conditions (codes -2, -1, 0, or 1) or choose
a code indicating the band of one of the pre-defined satellites.
Define your own spectral conditions:
| Code | Meaning
| -2 | Enter wlinf, wlsup.
The filter function will be equal to 1 over the whole band (as iwave=0) but step by step output will be
printed.
| -1 | Enter wl (monochr. cond, gaseous absorption is included).
| 0 | Enter wlinf, wlsup.
The filter function will be equal to 1over the whole band.
| 1 | Enter wlinf, wlsup and user's filter function s(lambda) by step of 0.0025 micrometer.
Pre-defined satellite bands:
| Code | Meaning
| 2 | meteosat vis band (0.350-1.110)
| 3 | goes east band vis (0.490-0.900)
| 4 | goes west band vis (0.490-0.900)
| 5 | avhrr (noaa6) band 1 (0.550-0.750)
| 6 | avhrr (noaa6) band 2 (0.690-1.120)
| 7 | avhrr (noaa7) band 1 (0.500-0.800)
| 8 | avhrr (noaa7) band 2 (0.640-1.170)
| 9 | avhrr (noaa8) band 1 (0.540-1.010)
| 10 | avhrr (noaa8) band 2 (0.680-1.120)
| 11 | avhrr (noaa9) band 1 (0.530-0.810)
| 12 | avhrr (noaa9) band 1 (0.680-1.170)
| 13 | avhrr (noaa10) band 1 (0.530-0.780)
| 14 | avhrr (noaa10) band 2 (0.600-1.190)
| 15 | avhrr (noaa11) band 1 (0.540-0.820)
| 16 | avhrr (noaa11) band 2 (0.600-1.120)
| 17 | hrv1 (spot1) band 1 (0.470-0.650)
| 18 | hrv1 (spot1) band 2 (0.600-0.720)
| 19 | hrv1 (spot1) band 3 (0.730-0.930)
| 20 | hrv1 (spot1) band pan (0.470-0.790)
| 21 | hrv2 (spot1) band 1 (0.470-0.650)
| 22 | hrv2 (spot1) band 2 (0.590-0.730)
| 23 | hrv2 (spot1) band 3 (0.740-0.940)
| 24 | hrv2 (spot1) band pan (0.470-0.790)
| 25 | tm (landsat5) band 1 (0.430-0.560)
| 26 | tm (landsat5) band 2 (0.500-0.650)
| 27 | tm (landsat5) band 3 (0.580-0.740)
| 28 | tm (landsat5) band 4 (0.730-0.950)
| 29 | tm (landsat5) band 5 (1.5025-1.890)
| 30 | tm (landsat5) band 7 (1.950-2.410)
| 31 | mss (landsat5) band 1 (0.475-0.640)
| 32 | mss (landsat5) band 2 (0.580-0.750)
| 33 | mss (landsat5) band 3 (0.655-0.855)
| 34 | mss (landsat5) band 4 (0.785-1.100)
| 35 | MAS (ER2) band 1 (0.5025-0.5875)
| 36 | MAS (ER2) band 2 (0.6075-0.7000)
| 37 | MAS (ER2) band 3 (0.8300-0.9125)
| 38 | MAS (ER2) band 4 (0.9000-0.9975)
| 39 | MAS (ER2) band 5 (1.8200-1.9575)
| 40 | MAS (ER2) band 6 (2.0950-2.1925)
| 41 | MAS (ER2) band 7 (3.5800-3.8700)
| 42 | MODIS band 1 (0.6100-0.6850)
| 43 | MODIS band 2 (0.8200-0.9025)
| 44 | MODIS band 3 (0.4500-0.4825)
| 45 | MODIS band 4 (0.5400-0.5700)
| 46 | MODIS band 5 (1.2150-1.2700)
| 47 | MODIS band 6 (1.6000-1.6650)
| 48 | MODIS band 7 (2.0575-2.1825)
| 49 | avhrr (noaa12) band 1 (0.500-1.000)
| 50 | avhrr (noaa12) band 2 (0.650-1.120)
| 51 | avhrr (noaa14) band 1 (0.500-1.110)
| 52 | avhrr (noaa14) band 2 (0.680-1.100)
| 53 | POLDER band 1 (0.4125-0.4775)
| 54 | POLDER band 2 (non polar) (0.4100-0.5225)
| 55 | POLDER band 3 (non polar) (0.5325-0.5950)
| 56 | POLDER band 4 P1 (0.6300-0.7025)
| 57 | POLDER band 5 (non polar) (0.7450-0.7800)
| 58 | POLDER band 6 (non polar) (0.7000-0.8300)
| 59 | POLDER band 7 P1 (0.8100-0.9200)
| 60 | POLDER band 8 (non polar) (0.8650-0.9400)
| 61 | etm+ (landsat7) band 1 (0.435-0.520)
| 62 | etm+ (landsat7) band 2 (0.506-0.621)
| 63 | etm+ (landsat7) band 3 (0.622-0.702)
| 64 | etm+ (landsat7) band 4 (0.751-0.911)
| 65 | etm+ (landsat7) band 5 (1.512-1.792)
| 66 | etm+ (landsat7) band 7 (2.020-2.380)
| 67 | etm+ (landsat7) band 8 (0.504-0.909)
| 68 | liss (IRC 1C) band 2 (0.502-0.620)
| 69 | liss (IRC 1C) band 3 (0.612-0.700)
| 70 | liss (IRC 1C) band 4 (0.752-0.880)
| 71 | liss (IRC 1C) band 5 (1.452-1.760)
| 72 | aster band 1 (0.480-0.645)
| 73 | aster band 2 (0.588-0.733)
| 74 | aster band 3N (0.723-0.913)
| 75 | aster band 4 (1.530-1.750)
| 76 | aster band 5 (2.103-2.285)
| 77 | aster band 6 (2.105-2.298)
| 78 | aster band 7 (2.200-2.393)
| 79 | aster band 8 (2.248-2.475)
| 80 | aster band 9 (2.295-2.538)
| 81 | avnir band 1 (0.390-0.550)
| 82 | avnir band 2 (0.485-0.695)
| 83 | avnir band 3 (0.545-0.745)
| 84 | avnir band 4 (0.700-0.925)
| 85 | ikonos Green band (0.350-1.035)
| 86 | ikonos Red band (0.350-1.035)
| 87 | ikonos NIR band (0.350-1.035)
| 88 | RapidEye Blue band (0.438-0.513)
| 89 | RapidEye Green band (0.463-0.594)
| 90 | RapidEye Red band (0.624-0.690)
| 91 | RapidEye RedEdge band (0.500-0.737)
| 92 | RapidEye NIR band (0.520-0.862)
| 93 | VGT1 (SPOT4) band 0 (0.400-0.500)
| 94 | VGT1 (SPOT4) band 2 (0.580-0.782)
| 95 | VGT1 (SPOT4) band 3 (0.700-1.030)
| 96 | VGT1 (SPOT4) MIR band (1.450-1.800)
| 97 | VGT2 (SPOT5) band 0 (0.400-0.550)
| 98 | VGT2 (SPOT5) band 2 (0.580-0.780)
| 99 | VGT2 (SPOT5) band 3 (0.700-1.000)
| 100 | VGT2 (SPOT5) MIR band (1.450-1.800)
EXAMPLES
Atmospheric correction of a LANDSAT-7 channel
The example is based on the North Carolina sample dataset (GMT -5 hours). First we set the computational
region to the satellite map, e.g. channel 4:
g.region rast=lsat7_2002_40 -p
It is important to verify the available metadata for the sun position which has to be defined for the
atmospheric correction. An option is to check the satellite overpass time with sun position as reported
in metadata. For the North Carolina sample dataset, they have also been stored for each channel and can
be retrieved like this:
r.info lsat7_2002_40
In this case, we have: SUN_AZIMUTH = 120.8810347, SUN_ELEVATION = 64.7730999.
If the sun position metadata are unavailable, we can also calculate them from the overpass time as
follows (r.sunmask uses SOLPOS):
r.sunmask -s elev=elevation out=dummy year=2002 month=5 day=24 hour=10 min=42 sec=7 timezone=-5
# .. reports: sun azimuth: 121.342461, sun angle above horz.(refraction corrected): 65.396652
If the overpass time is unknown, use the Satellite Overpass Predictor.
Convert DN (digital number = pixel values) to Radiance at top-of-atmosphere (TOA), using the formula
Lλ = ((LMAXλ - LMINλ)/(QCALMAX-QCALMIN)) * (QCAL-QCALMIN) + LMINλ
Where:
Lλ = Spectral Radiance at the sensor's aperture in Watt/(meter squared * ster *
µm), the apparent radiance as seen by the satellite sensor;
QCAL = the quantized calibrated pixel value in DN;
LMINλ = the spectral radiance that is scaled to QCALMIN in watts/(meter squared *
ster * µm);
LMAXλ = the spectral radiance that is scaled to QCALMAX in watts/(meter squared *
ster * µm);
QCALMIN = the minimum quantized calibrated pixel value (corresponding to LMINλ) in
DN;
QCALMAX = the maximum quantized calibrated pixel value (corresponding to LMAXλ) in
DN=255.
LMINλ and LMAXλ are the radiances related to the minimal and maximal DN value, and are
reported in the metadata file for each image, or in the table 1. High gain or low gain is also reported
in the metadata file of each Landsat image. The minimal DN value (QCALMIN) is 1 for Landsat ETM+ images
(see Landsat handbook), and the maximal DN value (QCALMAX) is 255. QCAL is the DN value for every
separate pixel in the Landsat image.
We extract the coefficients and apply them in order to obtain the radiance map:
CHAN=4
r.info lsat7_2002_${CHAN}0 -h | tr '\n' ' ' | sed 's+ ++g' | tr ':' '\n' | grep
"LMIN_BAND${CHAN}\|LMAX_BAND${CHAN}"
LMAX_BAND4=241.100,p016r035_7x20020524.met
LMIN_BAND4=-5.100,p016r035_7x20020524.met
QCALMAX_BAND4=255.0,p016r035_7x20020524.met
QCALMIN_BAND4=1.0,p016r035_7x20020524.met
Conversion to radiance (this calculation is done for band 4, for the other bands, the numbers in italics
need to be replaced with their related values):
r.mapcalc "lsat7_2002_40_rad=((241.1 - (-5.1)) / (255.0 - 1.0)) * (lsat7_2002_40 - 1.0) + (-5.1)"
# find mean elevation (target above sea level, used as initialization value in control file)
r.univar elevation
Create a control file 'icnd.txt' for channel 4 (NIR), based on metadata. For the overpass time, we need
to define decimal hours:
10:42:07 NC local time = 10.70 decimal hours (decimal minutes: 42 * 100 / 60) which is 15.70 GMT:
8 - geometrical conditions=Landsat ETM+
5 24 15.70 -78.691 35.749 - month day hh.ddd longitude latitude ("hh.ddd" is in GMT decimal hours)
2 - atmospheric mode=midlatitude summer
1 - aerosols model=continental
50 - visibility [km] (aerosol model concentration)
-0.110 - mean target elevation above sea level [km]
-1000 - sensor on board a satellite
64 - 4th band of ETM+ Landsat 7
Finally, run the atmospheric correction (-r for reflectance input map; -a for date >July 2000; -o to use
cache acceleration):
i.atcorr -r -a -o lsat7_2002_40_rad ialt=elevation icnd=icnd_lsat4.txt oimg=lsat7_2002_40_atcorr
Note that the altitude value from 'icnd_lsat4.txt' file is read at the beginning to compute the initial
transform. It is necessary to give a value which could be the mean value of the elevation model. For the
atmospheric correction then the raster elevation values are used from the map.
Note that the process is computationally intensive.
Note also, that i.atcorr reports solar elevation angle above horizon rather than solar zenith angle.
REMAINING DOCUMENTATION ISSUES
1. The influence and importance of the visibility value or map should be explained, also how to obtain an
estimate for either visibility or aerosol optical depth at 550nm.
SEE ALSO
GRASS Wiki page about Atmospheric correction
r.info, r.mapcalc, r.univar
REFERENCES
Vermote, E.F., Tanre, D., Deuze, J.L., Herman, M., and Morcrette, J.J., 1997, Second
simulation of the satellite signal in the solar spectrum, 6S: An overview., IEEE Trans.
Geosc. and Remote Sens. 35(3):675-686.
6S Manual: PDF1, PDF2, and PDF3
RapidEye sensors have been provided by RapidEye AG, Germany
AUTHORS
Original version of the program for GRASS 5:
Christo Zietsman, 13422863(at)sun.ac.za
Code clean-up and port to GRASS 6.3, 15.12.2006:
Yann Chemin, ychemin(at)gmail.com
Documentation clean-up + IRS LISS sensor addition 5/2009:
Markus Neteler, FEM, Italy
ASTER sensor addition 7/2009:
Michael Perdue, Canada
AVNIR, IKONOS sensors addition 7/2010:
Daniel Victoria, Anne Ghisla
RapidEye sensors addition 11/2010:
Peter Löwe, Anne Ghisla
VGT1 and VGT2 sensors addition from 6SV-1.1 sources, addition 07/2011:
Alfredo Alessandrini, Anne Ghisla
Last changed: $Date: 2013-02-15 14:04:18 -0800 (Fri, 15 Feb 2013) $
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GRASS 6.4.3 i.atcorr(1grass)