Note: This document is for an older version of GRASS GIS that is outdated. You should upgrade, and read the current manual page.
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
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.
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. |
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. |
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.
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.
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) |
g.region rast=lsat7_2002_40 -p
r.info lsat7_2002_40
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
Convert DN (digital number = pixel values) to Radiance at top-of-atmosphere (TOA), using the formula
Lλ = ((LMAXλ - LMINλ)/(QCALMAX-QCALMIN)) * (QCAL-QCALMIN) + LMINλ
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
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
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
i.atcorr -r -a -o lsat7_2002_40_rad ialt=elevation icnd=icnd_lsat4.txt oimg=lsat7_2002_40_atcorr
Note that the process is computationally intensive.
Note also, that i.atcorr reports solar elevation angle above horizon rather than solar zenith angle.
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 14:05:14 -0800 (Fri, 15 Feb 2013) $
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