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.
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:
#--------- start of control file -----
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
#--------- end of control file -------
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: 2011-09-27 18:00:47 +0200 (Tue, 27 Sep 2011) $
Full index
© 2003-2011 GRASS Development Team