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i.atcorr(1)		    GRASS GIS User's Manual		   i.atcorr(1)

       i.atcorr	 - Performs atmospheric	correction using the 6S	algorithm.
       6S - Second Simulation of Satellite Signal in the Solar Spectrum.

       imagery,	 atmospheric correction, radiometric conversion, radiance, re-
       flectance, satellite

       i.atcorr	--help
       i.atcorr	[-irab]	input=name  [range=min,max]   [elevation=name]	 [vis-
       ibility=name]	  parameters=name    output=name     [rescale=min,max]
       [--overwrite]  [--help]	[--verbose]  [--quiet]	[--ui]

	   Output raster map as	integer

	   Input raster	map converted to reflectance (default is radiance)

	   Input from ETM+ image taken after July 1, 2000

	   Input from ETM+ image taken before July 1, 2000

	   Allow output	files to overwrite existing files

	   Print usage summary

	   Verbose module output

	   Quiet module	output

	   Force launching GUI dialog

       input=nameA [required]
	   Name	of input raster	map

	   Input range
	   Default: 0,255

	   Name	of input elevation raster map (in m)

	   Name	of input visibility raster map (in km)

       parameters=nameA	[required]
	   Name	of input text file with	6S parameters

       output=nameA [required]
	   Name	for output raster map

	   Rescale output raster map
	   Default: 0,255

       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:  Current region settings are ignored!	The region is adjusted
       to cover	the input raster map before the	atmospheric correction is per-
       formed. The previous settings are restored afterwards.

       If the -r flag is used, the input raster	map is treated as reflectance.
       Otherwise, the input raster map is treated as radiance values and it is
       converted  to  reflectance at the i.atcorr runtime. The output data are
       always reflectance.

       The satellite overpass time has to be specified in Greenwich Mean  Time

       An example of the 6S parameters could be:
       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 model=tropical
       1			    - aerosols model=continental
       15			    - visibility [km] (aerosol model concentration)
       -0.600			    - mean target elevation above sea level [km] (here 600 m 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 ref-
       erence system.

   A. Geometrical conditions
       Code							    Description							 Details

       1							    meteosat observation					 enter	 month,day,decimal   hour   (universal	 time-hh.ddd)
																 A A A A A A A A A A A A A A A A A A A A A  n.	of  column,n.
																 of line. (full	scale 5000*2500)A

       2							    goes east observation					 enter	 month,day,decimal   hour   (universal	 time-hh.ddd)
																 A A A A A A A A A A A A A A A A A A A A A  n.	of  column,n.
																 of line. (full	scale 17000*12000)c

       3							    goes west observation					 enter	 month,day,decimal   hour   (universal	 time-hh.ddd)
																 A A A A A A A A A A A A A A A A A A A A A  n.	of  column,n.
																 of line. (full	scale 17000*12000)

       4							    avhrr (PM noaa)						 enter	 month,day,decimal   hour   (universal	 time-hh.ddd)
																 A A A A A A A A A A A A A A A A A A A A A    n.   of	 col-
																 A A A A A A A A A A A A A A A A A A A A A   give  long.(xlo-
																 nan)	    and	      overpass	     hour	(hna)	   at
																 A A A A A A A A A A A A A A A A A A A A A    the   ascendant
																 node at equator

       5							    avhrr (AM noaa)						 enter	 month,day,decimal   hour   (universal	 time-hh.ddd)
																 A A A A A A A A A A A A A A A A A A A A A    n.   of	 col-
																 A A A A A A A A A A A A A A A A A A A A A   give  long.(xlo-
																 nan)	    and	      overpass	     hour	(hna)	   at
																 A A A A A A A A A A A A A A A A A A A A A    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. *

       16							    WorldView 2							 enter month,day,hh.ddd,long.,lat. *

       17							    QuickBird							 enter month,day,hh.ddd,long.,lat. *

       18							    LandSat 8							 enter month,day,hh.ddd,long.,lat. *

       19							    Geoeye 1							 enter month,day,hh.ddd,long.,lat. *

       20							    Spot6							 enter month,day,hh.ddd,long.,lat. *

       21							    Spot7							 enter month,day,hh.ddd,long.,lat. *

       22							    Pleiades1A							 enter month,day,hh.ddd,long.,lat. *

       23							    Pleiades1B							 enter month,day,hh.ddd,long.,lat. *

       24							    Worldview3							 enter month,day,hh.ddd,long.,lat. *

       25							    Sentinel-2A							 enter month,day,hh.ddd,long.,lat. *

       26							    Sentinel-2B							 enter month,day,hh.ddd,long.,lat. *

       27							    PlanetScope	0c 0d						 enter month,day,hh.ddd,long.,lat. *

       28							    PlanetScope	0e						 enter month,day,hh.ddd,long.,lat. *

       29							    PlanetScope	0f 10						 enter month,day,hh.ddd,long.,lat. *

       30							    Worldview4							 enter month,day,hh.ddd,long.,lat. *

       NOTE: for HRV, TM, ETM+,	LISS and ASTER experiments, longitude and lat-
       itude 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 mea-
								    surements for altitudes 70km and 100km. This makes	34  mea-
								    surments. 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							 A

       1							    continental	model						 A

       2							    maritime model						 A

       3							    urban model							 A

       4							    shettle model for background desert	aerosol			 A

       5							    biomass burning						 A

       6							    stratospheric model						 A

       7							    define your	own model					 Enter the volumic percentage of each component: c(1) =	volu-
																 mic % of dust-like c(2) = volumic % of	water-soluble c(3)  =
																 volumic  %  of	 oceanic  c(4) = volumic % of soot All values
																 should	be between 0 and 1.

       8							    define your	own model					 Size distribution function: Multimodal	Log Normal (up	to  4

       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 visi-
       bility 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 at 550 nm

       NOTE: if	iaer is	0, enter -1 for	visibility.

       NOTE: if	a visibility map is provided, these parameters are ignored.

   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	eleva-
       tion) 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

       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 ac-
       cording to the values at	the ground level; taerp	will be	 computed  ac-
       cording to a 2 km 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 1
								    over 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							    Band name (peak response)

       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 blue	(435nm - 517nm)

       62							    etm+ (landsat7) band 2 green (508nm	- 617nm)

       63							    etm+ (landsat7) band 3 red (625nm -	702nm)

       64							    etm+ (landsat7) band 4 NIR (753nm -	910nm)

       65							    etm+ (landsat7) band 5 SWIR	(1520nm	- 1785nm)

       66							    etm+ (landsat7) band 7 SWIR	(2028nm	- 2375nm)

       67							    etm+ (landsat7) band 8 PAN (505nm -	917nm)

       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 (408nm	- 517nm)

       82							    avnir band 2 (503nm	- 612nm)

       83							    avnir band 3 (583nm	- 717nm)

       84							    avnir band 4 (735nm	- 922nm)

       85							    Ikonos Green band (408nm - 642nm)

       86							    Ikonos Red band (448nm - 715nm)

       87							    Ikonos NIR band (575nm - 787nm)

       88							    RapidEye Blue band (440nm -	512nm)

       89							    RapidEye Green band	(515nm - 592nm)

       90							    RapidEye Red band (628nm - 687nm)

       91							    RapidEye Red edge band (685nm - 735nm)

       92							    RapidEye NIR band (750nm - 860nm)

       93							    VGT1 (SPOT4) band 0	(420nm - 497nm)

       94							    VGT1 (SPOT4) band 2	(603nm - 747nm)

       95							    VGT1 (SPOT4) band 3	(740nm - 942nm)

       96							    VGT1 (SPOT4) MIR band (1540nm - 1777nm)

       97							    VGT2 (SPOT5) band 0	(423nm - 492nm)

       98							    VGT2 (SPOT5) band 2	(600nm - 737nm)

       99							    VGT2 (SPOT5) band 3	(745nm - 945nm)

       100							    VGT2 (SPOT5) MIR band (1523nm - 1757nm)

       101							    WorldView2 Panchromatic band (448nm	- 812nm)

       102							    WorldView2 Coastal Blue band (395nm	- 457nm)

       103							    WorldView2 Blue band (440nm	- 517nm)

       104							    WorldView2 Green band (503nm - 587nm)

       105							    WorldView2 Yellow band (583nm - 632nm)

       106							    WorldView2 Red band	(623nm - 695nm)

       107							    WorldView2 Red edge	band (698nm - 750nm)

       108							    WorldView2 NIR1 band (760nm	- 905nm)

       109							    WorldView2 NIR2 band (853nm	- 1047nm)

       110							    QuickBird Panchromatic band	(385nm - 1060nm)

       111							    QuickBird Blue band	(420nm - 585nm)

       112							    QuickBird Green band (448nm	- 682nm)

       113							    QuickBird Red band (560nm -	747nm)

       114							    QuickBird NIR1 band	(650nm - 935nm)

       115							    Landsat 8 Coastal aerosol band (433nm - 455nm)

       116							    Landsat 8 Blue band	(448nm - 515nm)

       117							    Landsat 8 Green band (525nm	- 595nm)

       118							    Landsat 8 Red band (633nm -	677nm)

       119							    Landsat 8 Panchromatic band	(498nm - 682nm)

       120							    Landsat 8 NIR band (845nm -	885nm)

       121							    Landsat 8 Cirrus band (1355nm - 1390nm)

       122							    Landsat 8 SWIR1 band (1540nm - 1672nm)

       123							    Landsat 8 SWIR2 band (2073nm - 2322nm)

       124							    GeoEye 1 Panchromatic band (448nm -	812nm)

       125							    GeoEye 1 Blue band (443nm -	525nm)

       126							    GeoEye 1 Green band	(503nm - 587nm)

       127							    GeoEye 1 Red band (653nm - 697nm)

       128							    GeoEye 1 NIR band (770nm - 932nm)

       129							    Spot6 Blue band (440nm - 532nm)

       130							    Spot6 Green	band (515nm - 600nm)

       131							    Spot6 Red band (610nm - 710nm)

       132							    Spot6 NIR band (738nm - 897nm)

       133							    Spot6 Pan band (438nm - 760nm)

       134							    Spot7 Blue band (445nm - 532nm)

       135							    Spot7 Green	band (525nm - 607nm)

       136							    Spot7 Red band (610nm - 727nm)

       137							    Spot7 NIR band (745nm - 902nm)

       138							    Spot7 Pan band (443nm - 760nm)

       139							    Pleiades1A Blue band (433nm	- 560nm)

       140							    Pleiades1A Green band (500nm - 617nm)

       141							    Pleiades1A Red band	(590nm - 722nm)

       142							    Pleiades1A NIR band	(740nm - 945nm)

       143							    Pleiades1A Pan band	(460nm - 845nm)

       144							    Pleiades1B Blue band 438nm - 560nm)

       145							    Pleiades1B Green band (498nm - 615nm)

       146							    Pleiades1B Red band	(608nm - 727nm)

       147							    Pleiades1B NIR band	(750nm - 945nm)

       148							    Pleiades1B Pan band	(460nm - 845nm)

       149							    Worldview3 Pan band	(445nm - 812nm)

       150							    Worldview3 Coastal blue band (395nm	- 455nm)

       151							    Worldview3 Blue band (443nm	- 517nm)

       152							    Worldview3 Green band (508nm - 587nm)

       153							    Worldview3 Yellow band (580nm - 630nm)

       154							    Worldview3 Red band	(625nm - 697nm)

       155							    Worldview3 Red edge	band (698nm - 752nm)

       156							    Worldview3 NIR1 band (760nm	- 902nm)

       157							    Worldview3 NIR2 band (855nm	- 1042nm)

       158							    Worldview3 SWIR1 band (1178nm - 1242nm)

       159							    Worldview3 SWIR2 band (1545nm - 1600nm)

       160							    Worldview3 SWIR3 band (1633nm - 1687nm)

       161							    Worldview3 SWIR4 band (1698nm - 1762nm)

       162							    Worldview3 SWIR5 band (2133nm - 2195nm)

       163							    Worldview3 SWIR6 band (2170nm - 2235nm)

       164							    Worldview3 SWIR7 band (2225nm - 2295nm)

       165							    Worldview3 SWIR8 band (2283nm - 2377nm)

       166							    Sentinel2A Coastal blue band B1 (430nm - 455nm)

       167							    Sentinel2A Blue band B2 (440nm - 530nm)

       168							    Sentinel2A Green band B3 (540nm - 580nm)

       169							    Sentinel2A Red band	B4 (648nm - 682nm)

       170							    Sentinel2A Red edge	band B5	(695nm - 712nm)

       171							    Sentinel2A Red edge	band B6	(733nm - 747nm)

       172							    Sentinel2A Red edge	band B7	(770nm - 795nm)

       173							    Sentinel2A NIR band	B8 (775nm - 905nm)

       174							    Sentinel2A Red edge	band B8A (850nm	- 880nm)

       175							    Sentinel2A Water vapour band B9 (933nm - 957nm)

       176							    Sentinel2A SWIR Cirrus band	B10 (1355nm - 1392nm)

       177							    Sentinel2A SWIR band B11 (1558nm - 1667nm)

       178							    Sentinel2A SWIR band B12 (2088nm - 2315nm)

       179							    Sentinel2B Coastal blue band B1 (430nm - 455nm)

       180							    Sentinel2B Blue band B2 (440nm - 530nm)

       181							    Sentinel2B Green band B3 (538nm - 580nm)

       182							    Sentinel2B Red band	B4 (648nm - 682nm)

       183							    Sentinel2B Red edge	band B5	(695nm - 712nm)

       184							    Sentinel2B Red edge	band B6	(730nm - 747nm)

       185							    Sentinel2B Red edge	band B7	(768nm - 792nm)

       186							    Sentinel2B NIR band	B8 (778nm - 905nm)

       187							    Sentinel2B Red edge	band B8A (850nm	- 877nm)

       188							    Sentinel2B Water vapour band B9 (930nm - 955nm)

       189							    Sentinel2B SWIR Cirrus band	B10 (1358nm - 1397nm)

       190							    Sentinel2B SWIR band B11 (1555nm - 1667nm)

       191							    Sentinel2B SWIR band B12 (2075nm - 2300nm)

       192							    PlanetScope	0c 0d Blue band	B1 (440nm - 570nm)

       193							    PlanetScope	0c 0d Green band B2 (450nm - 690nm)

       194							    PlanetScope	0c 0d Red band B3 (460nm - 700nm)

       195							    PlanetScope	0c 0d NIR band B4 (770nm - 880nm)

       196							    PlanetScope	0e Blue	band B1	(430nm - 700nm)

       197							    PlanetScope	0e Green band B2 (450nm	- 700nm)

       198							    PlanetScope	0e Red band B3 (460nm -	700nm)

       199							    PlanetScope	0e NIR band B4 (760nm -	880nm)

       200							    PlanetScope	0f 10 Blue band	B1 (450nm - 680nm)

       201							    PlanetScope	0f 10 Green band B2 (450nm - 680nm)

       202							    PlanetScope	0f 10 Red band B3 (450nm - 680nm)

       203							    PlanetScope	0f 10 NIR band B4 (760nm - 870nm)

       204							    Worldview4 Pan band	(424nm - 842nm)

       205							    Worldview4 Blue band (416nm	- 567nm)

       206							    Worldview4 Green band (488nm - 626nm)

       207							    Worldview4 Red band	(639nm - 711nm)

       208							    Worldview4 NIR1 band (732nm	- 962nm)

   Atmospheric correction of a Sentinel-2 band
       This  example  illustrates  how	to perform atmospheric correction of a
       Sentinel-2 scene	in the North Carolina location.

       Let's	 assume	     that      the	Sentinel-2	L1C	 scene
       was downloaded and imported with	region cropping	 (see  r.import)  into
       the  PERMANENT mapset of	the North Carolina location. The computational
       region was set to the extent of the elevation map in the	North Carolina
       dataset.	Now, we	have 13	individual bands (B01-B12) that	we want	to ap-
       ply the atmospheric correction to.  The following steps are applied  to
       each band separately.

       Create the parameters file for i.atcorr

       In  the	first step we create a file containing the 6S parameters for a
       particular scene	and band. To create a 6S file, we need to  obtain  the
       following information:

	   o   geometrical conditions,

	   o   moth, day, decimal hours	in GMT,	decimal	longitude and latitude
	       of measurement,

	   o   atmospheric model,

	   o   aerosol model,

	   o   visibility or aerosol optical depth,

	   o   mean target elevation above sea level,

	   o   sensor height and,

	   o   sensor band.

       1      Geometrical conditions

       For Sentinel-2A,	the geometrical	conditions take	the value 25  and  for
       Sentinel-2B, the	geometrical conditions value is	26 (See	table A).  Our
       scene comes from	the Sentinel-2A	mission	(the  file  name  begins  with

       2      Day, time, longitude and latitude	of measurement

       Day  and	 time of the measurement are hidden in the filename (i.e., the
       second datum in the file	name with  format  YYYYMMDDTHHMMSS),  and  are
       also  noted  in	the metadata file, which is included in	the downloaded
       scene (file with	.xml extension). Our sample scene was taken on October
       28th  (20161028)	 at  15:54:02  (155402).  Note that the	time has to be
       specified in decimal hours in Greenwich Mean Time (GMT).	 Luckily,  the
       time in the scene name is in GMT	and we can convert it to decimal hours
       as follows: 15 +	54/60 +	2/3600 = 15.901.

       Longitude and latitude refer to the centre of the computational	region
       (which can be smaller than the scene), and must be in WGS84 decimal co-
       ordinates. To obtain the	coordinates of the centre, we can run:
       g.region	-bg

       The longitude and latitude of the centre	 are  stored  in  ll_clon  and
       ll_clat.	In our case, ll_clon=-78.691 and ll_clat=35.749.

       3      Atmospheric model

       We  can choose between various atmospheric models as defined at the be-
       ginning of this manual. For North Carolina, we can choose 2 -  midlati-
       tude summer.

       4      Aerosol model

       We can also choose between various aerosol models as defined at the be-
       ginning of this manual. For North Carolina, we can choose 1 - continen-
       tal model.

       5      Visibility or Aerosol Optical Depth

       For Sentinel-2 scenes, the visibility is	not measured, and therefore we
       have to estimate	the aerosol optical depth instead, e.g.	from  AERONET.
       With  a bit of luck, you	can find a station nearby your location, which
       measured	the Aerosol Optical Depth at 500 nm at the same	 time  as  the
       scene  was taken. In our	case, on 28th October 2016, the	EPA-Res_Trian-
       gle_Pk station measured AOD = 0.07 (approximately).

       6      Mean target elevation above sea level

       Mean target elevation above sea level refers to the mean	 elevation  of
       the  computational  region. You can estimate it from the	digital	eleva-
       tion model, e.g.	by running:
       r.univar	-g elevation

       The mean	elevation is stored in mean. In	our case, mean=110. In the  6S
       file it will be displayed in [-km], i.e., -0.110.

       7      Sensor height

       Since the sensor	is on board a satellite, the sensor height will	be set
       to -1000.

       8      Sensor band

       The overview of satellite bands can be found in table  F	 (see  above).
       For  Sentinel-2A,  the  band numbers span from 166 to 178, and for Sen-
       tinel-2B, from 179 to 191.

       Finally,	here is	what the 6S file would look like for Band  02  of  our
       scene.  In  order to use	it in the i.atcorr module, we can save it in a
       text file, for example params_B02.txt.
       10 28 15.901 -78.691 35.749

       Compute atmospheric correction

       In the next step	we run i.atcorr	for the	selected band B02 of our  Sen-
       tinel 2 scene. We have to specify the following parameters:

	   o   input = raster band to be processed,

	   o   parameters  =  path to 6S file created in the previous step (we
	       could also enter	the values directly),

	   o   output =	name for the output corrected raster band,

	   o   range = from 1 to the QUANTIFICATION_VALUE stored in the	 meta-
	       data file. It is	10000 for both Sentinel-2A and Sentinel-2B.

	   o   rescale	=  the output range of values for the corrected	bands.
	       This is up to the user to  choose,  for	example:  0-255,  0-1,

       If  the data is available, the following	parameters can be specified as

	   o   elevation = raster of digital elevation model,

	   o   visibility = raster of visibility model.

       Finally,	this is	how the	command	would look like	to  apply  atmospheric
       correction to band B02:
       i.atcorr	input=B02 parameters=params_B02.txt output=B02.atcorr range=1,10000 rescale=0,255 elevation=elevation

       To  apply  atmospheric correction to the	remaining bands, only the last
       line in the 6S parameters file (i.e., the  sensor  band)	 needs	to  be
       changed.	 The other parameters will remain the same.
       Figure:	Sentinel-2A  Band 02 with applied atmospheric correction (his-
       togram equalization grayscale color scheme)

   Atmospheric correction of a Landsat-7 band
       This example is also based on the North Carolina	sample dataset (GMT -5
       hours).	 First	we  set	the computational region to the	satellite map,
       e.g. band 4:
       g.region	raster=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  the
       metadata	 file  (file copy; North Carolina sample dataset). In the case
       of the North Carolina sample dataset, these values have been stored for
       each channel and	can be retrieved with: lsat7_2002_40
       In  this	 case,	we  have:  SUN_AZIMUTH	= 120.8810347, SUN_ELEVATION =

       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 NASA LaRC Satellite Overpass

   Convert digital numbers (DN)	to radiance at top-of-atmosphere (TOA)
       For Landsat and ASTER, the conversion can  be  conveniently  done  with
       i.landsat.toar or i.aster.toar, respectively.

       In case of different satellites,	the conversion of DN (digital number =
       pixel values) to	radiance at top-of-atmosphere (TOA) can	also  be  done
       manually, using e.g. the	formula:
       # formula depends on satellite sensor, see respective metadata

	   o   LI>>  = Spectral	Radiance at the	sensor's aperture in Watt/(me-
	       ter squared * ster * A<micro>m),	the apparent radiance as  seen
	       by the satellite	sensor;

	   o   QCAL = the quantized calibrated pixel value in DN;

	   o   LMINI>>	=  the	spectral radiance that is scaled to QCALMIN in
	       watts/(meter squared * ster * A<micro>m);

	   o   LMAXI>> = the spectral radiance that is scaled  to  QCALMAX  in
	       watts/(meter squared * ster * A<micro>m);

	   o   QCALMIN	= the minimum quantized	calibrated pixel value (corre-
	       sponding	to LMINI>>) in DN;

	   o   QCALMAX = the maximum quantized calibrated pixel	value  (corre-
	       sponding	to LMAXI>>) in DN=255.
       LMINI>>	and LMAXI>> are	the radiances related to the minimal and maxi-
       mal DN value, and they are reported in the metadata file	of each	image.
       High  gain  or  low  gain is also reported in the metadata file of each
       satellite image.	For Landsat ETM+, the minimal DN value (QCALMIN) is  1
       (see  Landsat handbook, chapter 11), and	the maximal DN value (QCALMAX)
       is 255. QCAL is the DN value for	every separate pixel  in  the  Landsat

       We extract the coefficients and apply them in order to obtain the radi-
       ance map:
       CHAN=4 lsat7_2002_${CHAN}0 -h | tr '\n' ' ' | sed 's+ ++g' | tr ':' '\n'	| grep "LMIN_BAND${CHAN}\|LMAX_BAND${CHAN}"
       Conversion to radiance (this calculation	is done	for band  4,  for  the
       other  bands,  the  numbers will	need to	be replaced with their related
       r.mapcalc "lsat7_2002_40_rad = ((241.1 -	(-5.1))	/ (255.0 - 1.0)) * (lsat7_2002_40 - 1.0) + (-5.1)"
       Again, the r.mapcalc calculation	is only	needed when working with  sat-
       ellite data other than Landsat or ASTER.

   Create the parameters file for i.atcorr
       The  underlying	6S model is parametrized through a control file, indi-
       cated with the parameters option. This is a text	file defining  geomet-
       rical  and atmospherical	conditions of the satellite overpass.  Here we
       create a	control	file icnd_lsat4.txt for	band 4 (NIR), based  on	 meta-
       data.  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 model=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):
       i.atcorr	-r -a lsat7_2002_40_rad	elevation=elevation parameters=icnd_lsat4.txt output=lsat7_2002_40_atcorr
       Note that the altitude value from 'icnd_lsat4.txt' file is read at  the
       beginning  to compute the initial transform. Therefore, it is necessary
       to provide a value that might be	the mean value of the elevation	 model
       (r.univar elevation). For the atmospheric correction per	se, the	eleva-
       tion values from	the raster map are used.

       Note that the process is	computationally	 intensive.  Note  also,  that
       i.atcorr	 reports solar elevation angle above horizon rather than solar
       zenith angle.

       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.

       GRASS Wiki page about Atmospheric correction

	i.aster.toar,  i.colors.enhance,  i.landsat.toar,,  r.mapcalc,

	   o   Vermote,	 E.F.,	Tanre,	D.,  Deuze, J.L., Herman, M., and Mor-
	       crette, 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.

	   o   6S Manual: PDF1,	PDF2, and PDF3

	   o   RapidEye	sensors	have been provided by RapidEye AG, Germany

	   o   Barsi, J.A., Markham, B.L. and Pedelty, J.A., 2011, The	opera-
	       tional land imager: spectral response and spectral uniformity.,
	       Proc. SPIE 8153,	81530G;	doi:10.1117/12.895438

       Original	version	of the program for GRASS 5:
       Christo Zietsman, 13422863(at)

       Code clean-up and port to GRASS 6.3, 15.12.2006:
       Yann Chemin, ychemin(at)

       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 LA<paragraph>we, Anne Ghisla

       VGT1 and	VGT2 sensors addition from 6SV-1.1 sources, addition 07/2011:
       Alfredo Alessandrini, Anne Ghisla

       Added Landsat 8 from NASA sources, addition 05/2014:
       Nikolaos	Ves

       Geoeye1 addition	7/2015:
       Marco Vizzari

       Worldview3 addition 8/2016:
       Markus Neteler,, Germany

       Sentinel-2A addition 12/2016:
       Markus Neteler,, Germany

       Sentinel-2B addition 1/2018:
       Stefan Blumentrath, Zofie Cimburova, Norwegian Institute	for Nature Re-
       search, NINA, Oslo, Norway

       Worldview4 addition 12/2018:
       Markus Neteler,, Germany

       Available at: i.atcorr source code (history)

       Main  index | Imagery index | Topics index | Keywords index | Graphical
       index | Full index

       A(C) 2003-2020 GRASS Development	Team, GRASS GIS	7.8.4 Reference	Manual

GRASS 7.8.4							   i.atcorr(1)


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