i.atcorr manual: added example to process Sentinel bands (contributed by Zofie Cimburová) and general manual clean-up

git-svn-id: https://svn.osgeo.org/grass/grass/trunk@72390 15284696-431f-4ddb-bdfa-cd5b030d7da7

imagery/i.atcorr/i.atcorr.html

@@ -7,37 +7,34 @@ available at the
 <a href="http://modis-sr.ltdri.org/">Land Surface
 Reflectance Science Computing Facility website</a>.
 
-<p><em>Important note: Current region settings are ignored!</em> The region is adjusted
-to cover the input raster map before the atmospheric correction is
-performed. The previous settings are restored afterwards.
+<p><em>Important: Current region settings are ignored!</em> The 
+region is adjusted to cover the input raster map before the atmospheric 
+correction is performed. The previous settings are restored afterwards.
 
-This flag tells <em>i.atcorr</em> to try and speedup calculations.
-However, this option will increase memory requirements.
-
-<p>If flag <b>-r</b> is used, the input raster data are treated as
-<em>reflectance</em>. Otherwise, the input raster data are treated
-as <em>radiance</em> values and are converted to reflectance at
+<p>If the <b>-r</b> flag is used, the input raster map is treated as
+<em>reflectance</em>. Otherwise, the input raster map is treated
+as <em>radiance</em> values and it is converted to reflectance at
 the <em>i.atcorr</em> runtime. The output data are always reflectance.
 
-<p>Note that the satellite overpass time has to be specified in Greenwich
+<p>The satellite overpass time has to be specified in Greenwich
 Mean Time (GMT).
 
-<p>An example 6S parameters:
+<p>An example of the 6S parameters could be:
 
 <div class="code"><pre>
 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                            - atmospheric model=tropical
 1                            - aerosols model=continental
 15                           - visibility [km] (aerosol model concentration)
--0.600                       - mean target elevation above sea level [km] (here 600m asl)
+-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
 </pre></div>
 
 If the position is not available in longitude-latitude (WGS84), the
 <em><a href="m.proj.html">m.proj</a></em> conversion module can be
-used to reproject from a different projection.
+used to reproject from a different reference system.
 
 <h2>6S CODE PARAMETER CHOICES</h2>
 
@@ -377,7 +374,7 @@ ozone content:
 <br>c(3) = volumic % of oceanic
 <br>c(4) = volumic % of soot
 <br>
-<br>All values between 0 and 1.</td>
+<br>All values should be between 0 and 1.</td>
 </tr>
 
 <tr>
@@ -400,9 +397,7 @@ ozone content:
 
 <tr>
 <td>11</td>
-
 <td>define your own model</td>
-
 <td>Sun-photometer measurements, 50 values max, entered as:
 <br>
 <br>r and d V / d (logr)
@@ -421,14 +416,14 @@ refractive index.</td>
 <h3>D. Aerosol concentration model (visibility)</h3>
 
 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).
+v, enter directly the value of v [km] (the aerosol optical depth (AOD) 
+will be computed from a standard aerosol profile).
 <p>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:<br>
 <div class="code"><pre>
 0                            - visibility
-0.112                        - aerosol optical depth 550 nm
+0.112                        - aerosol optical depth at 550 nm
 </pre></div>
 
 <p>NOTE: if iaer is 0, enter -1 for visibility.
@@ -439,9 +434,9 @@ Target altitude (xps, in negative [km]):
 <blockquote>xps &gt;= 0 means the target is at the sea level.
 <br>otherwise xps expresses the altitude of the target (e.g., mean elevation)
 in [km], given as negative value
-</blockquote>
+</blockquote><br>
 
-<p>Sensor platform (xpp, in negative [km] or -1000):
+Sensor platform (xpp, in negative [km] or -1000):
 <blockquote>
 <br>xpp = -1000 means that the sensor is on board a satellite.
 <br>xpp = 0 means that the sensor is at the ground level.
@@ -456,7 +451,7 @@ puw,po3 (water vapor content,ozone content between the aircraft and the surface)
 surface)
 <p>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
+to the values at the ground level; taerp will be computed according to a 2 km
 exponential profile for aerosol.
 </blockquote>
 
@@ -490,13 +485,13 @@ but step by step output will be printed.</td>
 <tr>
 <td>0</td>
 <td>Enter wlinf, wlsup.
-<br>The filter function will be equal to 1over the whole band.</td>
+<br>The filter function will be equal to 1 over the whole band.</td>
 </tr>
 
 <tr>
 <td>1</td>
-<td>Enter wlinf, wlsup and user's filter function s(lambda) by step of 0.0025
-micrometer.</td>
+<td>Enter wlinf, wlsup and user's filter function s (lambda) by step of 
+0.0025 micrometer.</td>
 </tr>
 </table>
 
@@ -617,7 +612,7 @@ micrometer.</td>
 <tr><td>88</td><td><b>RapidEye</b> Blue band (440nm - 512nm)</td></tr>
 <tr><td>89</td><td>RapidEye Green band (515nm - 592nm)</td></tr>
 <tr><td>90</td><td>RapidEye Red band (628nm - 687nm)</td></tr>
-<tr><td>91</td><td>RapidEye RedEdge band (685nm - 735nm)</td></tr>
+<tr><td>91</td><td>RapidEye Red edge band (685nm - 735nm)</td></tr>
 <tr><td>92</td><td>RapidEye NIR band (750nm - 860nm)</td></tr>
 
 <tr><td>93</td><td><b>VGT1 (SPOT4)</b> band 0 (420nm - 497nm)</td></tr>
@@ -636,7 +631,7 @@ micrometer.</td>
 <tr><td>104</td><td>WorldView 2 Green band (503nm - 587nm)</td></tr>
 <tr><td>105</td><td>WorldView 2 Yellow band (583nm - 632nm)</td></tr>
 <tr><td>106</td><td>WorldView 2 Red band (623nm - 695nm)</td></tr>
-<tr><td>107</td><td>WorldView 2 Red Edge band (698nm - 750nm)</td></tr>
+<tr><td>107</td><td>WorldView 2 Red edge band (698nm - 750nm)</td></tr>
 <tr><td>108</td><td>WorldView 2 NIR1 band (760nm - 905nm)</td></tr>
 <tr><td>109</td><td>WorldView 2 NIR2 band (853nm - 1047nm)</td></tr>
 
@@ -646,21 +641,21 @@ micrometer.</td>
 <tr><td>113</td><td>QuickBird Red band (560nm - 747nm)</td></tr>
 <tr><td>114</td><td>QuickBird NIR1 band (650nm - 935nm)</td></tr>
 
-<tr><td>115</td><td><b>Landsat 8 </b> Coastal Aerosol Band (433nm - 455nm)</td></tr>
-<tr><td>116</td><td>Landsat 8 Blue Band  (448nm - 515nm)</td></tr>
-<tr><td>117</td><td>Landsat 8 Green Band (525nm - 595nm)</td></tr>
-<tr><td>118</td><td>Landsat 8 Red Band (633nm - 677nm)</td></tr>
-<tr><td>119</td><td>Landsat 8 Panchromatic Band (498nm - 682nm)</td></tr>
-<tr><td>120</td><td>Landsat 8 NIR Band (845nm - 885nm)</td></tr>
-<tr><td>121</td><td>Landsat 8 Cirrus Band (1355nm - 1390nm)</td></tr>
-<tr><td>122</td><td>Landsat 8 SWIR1 Band (1540nm - 1672nm)</td></tr>
-<tr><td>123</td><td>Landsat 8 SWIR2 Band (2073nm - 2322nm)</td></tr>
+<tr><td>115</td><td><b>Landsat 8 </b> Coastal aerosol band (433nm - 455nm)</td></tr>
+<tr><td>116</td><td>Landsat 8 Blue band  (448nm - 515nm)</td></tr>
+<tr><td>117</td><td>Landsat 8 Green band (525nm - 595nm)</td></tr>
+<tr><td>118</td><td>Landsat 8 Red band (633nm - 677nm)</td></tr>
+<tr><td>119</td><td>Landsat 8 Panchromatic band (498nm - 682nm)</td></tr>
+<tr><td>120</td><td>Landsat 8 NIR band (845nm - 885nm)</td></tr>
+<tr><td>121</td><td>Landsat 8 Cirrus band (1355nm - 1390nm)</td></tr>
+<tr><td>122</td><td>Landsat 8 SWIR1 band (1540nm - 1672nm)</td></tr>
+<tr><td>123</td><td>Landsat 8 SWIR2 band (2073nm - 2322nm)</td></tr>
 
 <tr><td>115</td><td><b>GeoEye 1</b> Panchromatic band (448nm - 812nm)</td></tr>
-<tr><td>116</td><td>GeoEye 1 Blue Band (443nm - 525nm)</td></tr>
-<tr><td>117</td><td>GeoEye 1 Green Band (503nm - 587nm)</td></tr>
-<tr><td>118</td><td>GeoEye 1 Red Band (653nm - 697nm)</td></tr>
-<tr><td>120</td><td>GeoEye 1 NIR Band (770nm - 932nm)</td></tr>
+<tr><td>116</td><td>GeoEye 1 Blue band (443nm - 525nm)</td></tr>
+<tr><td>117</td><td>GeoEye 1 Green band (503nm - 587nm)</td></tr>
+<tr><td>118</td><td>GeoEye 1 Red band (653nm - 697nm)</td></tr>
+<tr><td>120</td><td>GeoEye 1 NIR band (770nm - 932nm)</td></tr>
 
 <tr><td>129</td><td><b>Spot6</b> Blue band (440nm - 532nm)</td></tr>
 <tr><td>130</td><td>Spot6 Green band (515nm - 600nm)</td></tr>
@@ -738,32 +733,189 @@ micrometer.</td>
 
 <h2>EXAMPLES</h2>
 
-<h3>Atmospheric correction of a LANDSAT-7 channel</h3>
+<h3>Atmospheric correction of a Sentinel-2 band</h3>
+<p>This example illustrates how to perform atmospheric correction of a 
+Sentinel-2 scene in the North Carolina location.
+
+<p>Let's assume that the Sentinel-2 L1C scene 
+<em>S2A_OPER_PRD_MSIL1C_PDMC_20161029T092602_R054_V20161028T155402_20161028T155402</em>
+was downloaded and imported with region cropping 
+(see <a href="r.import.html">r.import</a>) 
+into the <em>PERMANENT</em> mapset of the North Carolina location. The 
+computational region was set to the extent of the <em>elevation</em> 
+map in the North Carolina dataset. Now, we have 13 individual bands
+(<em>B01-B12</em>) that we want to apply the atmospheric correction to. 
+The following steps are applied to each band separately.
+
+<p><b>Create the parameters file for i.atcorr</b>
+<p>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:
+<ul> 
+    <li> geometrical conditions, 
+    <li> moth, day, decimal hours in GMT, decimal longitude and latitude of measurement,
+    <li> atmospheric model,
+	<li> aerosol model,
+    <li> visibility or aerosol optical depth,
+	<li> mean target elevation above sea level,
+    <li> sensor height and,
+    <li> sensor band.
+</ul>
+
+<ol>
+<li><em>Geometrical conditions</em>
+<p>For Sentinel-2A, the geometrical conditions take the value <tt>25</tt> and for 
+Sentinel-2B, the geometrical conditions value is <tt>26</tt> (See table A). 
+Our scene comes from the Sentinel-2A mission (the file name begins with 
+S2A_...).
+<br><br>
+<li><em>Day, time, longitude and latitude of measurement</em>
+<p>Day and time of the measurement are hidden in the filename (i.e., the
+second datum in the file name with format <tt>YYYYMMDDTHHMMSS</tt>), 
+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.
+
+<p>Longitude and latitude refer to the centre of the computational region
+(which can be smaller than the scene), and must be in WGS84 decimal 
+coordinates. To obtain the coordinates of the centre, we can run: 
+
+<div class="code"><pre>
+g.region -bg
+</pre></div>
+
+<p>The longitude and latitude of the centre are stored in <em>ll_clon</em>
+and <em>ll_clat</em>. In our case, <tt>ll_clon=-78.691</tt> and 
+<tt>ll_clat=35.749</tt>.
+
+<br><br>
+<li><em>Atmospheric model</em>
+<p>We can choose between various atmospheric models as defined at the 
+beginning of this manual. For North Carolina, we can choose <tt>2 - 
+midlatitude summer</tt>.
+
+<br><br>
+<li><em>Aerosol model</em>
+<p>We can also choose between various aerosol models as defined at the 
+beginning of this manual. For North Carolina, we can choose <tt>1 - 
+continental model</tt>.
+
+<br><br>
+<li><em>Visibility or Aerosol Optical Depth</em>
+<p>For Sentinel-2 scenes, the visibility is not measured, and therefore 
+we have to estimate the aerosol optical depth instead, e.g. from 
+<a href="https://aeronet.gsfc.nasa.gov">AERONET</a>. 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 <em>EPA-Res_Triangle_Pk</em> station 
+measured AOD = 0.07 (approximately).
+
+<br><br>
+<li><em>Mean target elevation above sea level</em>
+<p>Mean target elevation above sea level refers to the mean elevation 
+of the computational region. You can estimate it from the digital 
+elevation model, e.g. by running:
+
+<div class="code"><pre>
+r.univar -g elevation
+</pre></div>
+
+<p>The mean elevation is stored in <em>mean</em>. In our case, 
+<tt>mean=110</tt>. In the 6S file it will be displayed in [-km], 
+i.e., <tt>-0.110</tt>.
+
+<br><br>
+<li><em>Sensor height</em>
+<p>Since the sensor is on board a satellite, the sensor height will be 
+set to <tt>-1000</tt>.
+
+<br><br>
+<li><em>Sensor band</em>
+<p>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 
+Sentinel-2B, from 179 to 191.
+</ol>
+
+<p>Finally, here is what the 6S file would look like for Band 02 of our 
+scene. In order to use it in the <em>i.atcorr</em> module, we can save 
+it in a text file, for example <tt>params_B02.txt</tt>.
+<div class="code"><pre>
+25
+10 28 15.901 -78.691 35.749
+2
+1
+0
+0.07
+-0.110
+-1000
+167
+</pre></div>
+
+<p><b>Compute atmospheric correction</b>
+<p>In the next step we run <em>i.atcorr</em> for the selected band 
+<em>B02</em> of our Sentinel 2 scene. We have to specify the following 
+parameters:
+<ul> 
+    <li><b>input</b> = raster band to be processed, 
+    <li><b>parameters</b> = path to 6S file created in the previous step (we could also enter the values directly),
+    <li><b>output</b> = name for the output corrected raster band,
+	<li><b>range</b> = from 1 to the <tt>QUANTIFICATION_VALUE</tt> stored in the metadata file. It is <tt>10000</tt> for both Sentinel-2A and Sentinel-2B.
+	<li><b>rescale</b> = the output range of values for the corrected bands. This is up to the user to choose, for example: 0-255, 0-1, 1-10000.
+</ul>
+<p>If the data is available, the following parameters can be specified 
+as well:
+<ul> 
+    <li><b>elevation</b> = raster of digital elevation model,
+    <li><b>visibility</b> = raster of visibility model.
+</ul>
+    
+<p>Finally, this is how the command would look like to apply atmospheric 
+correction to band <em>B02</em>:
+
+<div class="code"><pre>
+i.atcorr input=B02 parameters=params_B02.txt output=B02.atcorr range=1,10000 rescale=0,255 elevation=elevation
+</pre></div>
+
+<p>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.
+
+<div align="center" style="margin: 10px">
+<a href="i_atcorr_B02_atcorr.png">
+<img src="i_atcorr_B02_atcorr.png" width="600" height="486" alt="i.atcorr example" border="0">
+</a><br>
+<i>Figure: Sentinel-2A Band 02 with applied atmospheric correction (histogram equalization grayscale color scheme)</i>
+</div>
+
+<h3>Atmospheric correction of a Landsat-7 band</h3>
+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:
 
-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:
 <div class="code"><pre>
 g.region raster=lsat7_2002_40 -p
 </pre></div>
 
-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
+<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
 <a href="ftp://ftp.glcf.umd.edu/glcf/Landsat/WRS2/p016/r035/p016r035_7x20020524.ETM-EarthSat-Orthorectified/p016r035_7x20020524.met">metadata</a>
 file (<a href="http://www.grassbook.org/wp-content/uploads/ncexternal/landsat/2002/p016r035_7x20020524.met">file copy</a>; North Carolina
-sample dataset). In case of the North Carolina sample dataset, values
-have been stored for each channel and can be retrieved like this:
+sample dataset). In the case of the North Carolina sample dataset, these
+values have been stored for each channel and can be retrieved with:
 
 <div class="code"><pre>
 r.info lsat7_2002_40
 </pre></div>
 
 In this case, we have: SUN_AZIMUTH = 120.8810347, SUN_ELEVATION = 64.7730999.
-<p>
-If the sun position metadata are unavailable, we can also calculate
+<p>If the sun position metadata are unavailable, we can also calculate
 them from the overpass time as follows
 (<em><a href="r.sunmask.html">r.sunmask</a></em>
 uses <a href="http://www.nrel.gov/midc/solpos/solpos.html">SOLPOS</a>):
+
 <div class="code"><pre>
 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
@@ -772,20 +924,22 @@ r.sunmask -s elev=elevation out=dummy year=2002 month=5 day=24 hour=10 min=42 se
 If the overpass time is unknown, use the
 <a href="http://cloudsgate2.larc.nasa.gov/cgi-bin/predict/predict.cgi">NASA LaRC Satellite Overpass Predictor</a>.
 
-<h4>Conversion of digital number (DN) to radiance at top-of-atmosphere (TOA)</h4>
+<h4>Convert digital numbers (DN) to radiance at top-of-atmosphere (TOA)</h4>
 
 For Landsat and ASTER, the conversion can be conveniently done with
-<a href="i.landsat.toar.html">i.landsat.toar</a> or <a href="i.aster.toar.html">i.aster.toar</a>,
-respectively.
+<em><a href="i.landsat.toar.html">i.landsat.toar</a></em> or 
+<em><a href="i.aster.toar.html">i.aster.toar</a></em>, respectively.
+
+<p>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:
 
-<p>
-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
 <div class="code"><pre>
 # formula depends on satellite sensor, see respective metadata
 L&lambda; = ((LMAX&lambda; - LMIN&lambda;)/(QCALMAX-QCALMIN)) * (QCAL-QCALMIN) + LMIN&lambda;
 </pre></div>
-where:
+
+where,
 <ul>
 <li> L&lambda; = Spectral Radiance at the sensor's aperture in Watt/(meter squared * ster * &micro;m), the
       apparent radiance as seen by the satellite sensor;</li>
@@ -796,15 +950,16 @@ where:
 <li> QCALMAX = the maximum quantized calibrated pixel value (corresponding to LMAX&lambda;) in DN=255.</li>
 </ul>
 
-LMIN&lambda; and LMAX&lambda; 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
-satellite image. For Landsat, the minimal DN value (QCALMIN) is 1 for Landsat ETM+
-images (see
-<a href="http://landsathandbook.gsfc.nasa.gov/pdfs/Landsat7_Handbook.pdf">Landsat handbook</a>, see chapter 11),
+LMIN&lambda; and LMAX&lambda; are the radiances related to the minimal 
+and maximal 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 <a href="http://landsathandbook.gsfc.nasa.gov/pdfs/Landsat7_Handbook.pdf">Landsat handbook</a>, chapter 11),
 and the maximal DN value (QCALMAX) is 255. QCAL is the DN value for every
 separate pixel in the Landsat image.
-<p>We extract the coefficients and apply them in order to obtain the radiance map:
+<p>We extract the coefficients and apply them in order to obtain the 
+radiance map:
+
 <div class="code"><pre>
 CHAN=4
 r.info lsat7_2002_${CHAN}0 -h | tr '\n' ' ' | sed 's+ ++g' | tr ':' '\n' | grep "LMIN_BAND${CHAN}\|LMAX_BAND${CHAN}"
@@ -814,36 +969,33 @@ QCALMAX_BAND4=255.0,p016r035_7x20020524.met
 QCALMIN_BAND4=1.0,p016r035_7x20020524.met
 </pre></div>
 
-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):
+Conversion to radiance (this calculation is done for band 4, for the 
+other bands, the numbers will need to be replaced with their related
+values):
 
 <div class="code"><pre>
 r.mapcalc "lsat7_2002_40_rad = ((241.1 - (-5.1)) / (255.0 - 1.0)) * (lsat7_2002_40 - 1.0) + (-5.1)"
 </pre></div>
 
-Again, the <em>r.mapcalc</em> calculation is only needed when working with satellite data
-other than Landsat or ASTER.
+Again, the <em>r.mapcalc</em> calculation is only needed when working 
+with satellite data other than Landsat or ASTER.
 
-<h4>Creation of parameter file for i.atcorr</h4>
+<h4>Create the parameters file for i.atcorr</h4>
 
-The underlying 6S model is parametrized through a control file, indicated with the
-<em>parameter</em> option. This is a text file defining geometrical and atmospherical
-conditions of the satellite overpass. Below some details:
+The underlying 6S model is parametrized through a control file, 
+indicated with the <b>parameters</b> option. This is a text file 
+defining geometrical and atmospherical conditions of the satellite 
+overpass.
 
-<p>
-<div class="code"><pre>
-# find mean elevation (target above sea level, used as initialization value in control file)
-r.univar elevation
-</pre></div>
-
-Create a control file 'icnd.txt' for channel 4 (NIR), based on metadata. For the overpass time,
-we need to define decimal hours:<br>
-10:42:07 NC local time = 10.70 decimal hours (decimal minutes: 42 * 100 / 60) which is 15.70 GMT:
+Here we create a control file <tt>icnd_lsat4.txt</tt> for band 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.
 
 <div class="code"><pre>
 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
+2                            - atmospheric model=midlatitude summer
 1                            - aerosols model=continental
 50                           - visibility [km] (aerosol model concentration)
 -0.110                       - mean target elevation above sea level [km]
@@ -851,27 +1003,30 @@ we need to define decimal hours:<br>
 64                           - 4th band of ETM+ Landsat 7
 </pre></div>
 
-Finally, run the atmospheric correction (-r for reflectance input map; -a for date &gt;July 2000):
+Finally, run the atmospheric correction (-r for reflectance input map; 
+-a for date &gt; July 2000):
+
 <div class="code"><pre>
-i.atcorr -r -a lsat7_2002_40_rad elev=elevation parameters=icnd_lsat4.txt output=lsat7_2002_40_atcorr
+i.atcorr -r -a lsat7_2002_40_rad elevation=elevation parameters=icnd_lsat4.txt output=lsat7_2002_40_atcorr
 </pre></div>
 
-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.
-<p>Note that the process is computationally intensive.<br>
-Note also, that <em>i.atcorr</em> reports solar elevation angle above horizon rather than solar zenith angle.
+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 
+(<tt>r.univar elevation</tt>). For the atmospheric correction per se, the 
+elevation values from the raster map are used.
+<p>Note that the process is computationally intensive. Note also, that 
+<em>i.atcorr</em> reports solar elevation angle above horizon rather 
+than solar zenith angle.
 
 <h2>REMAINING DOCUMENTATION ISSUES</h2>
-1. The influence and importance of the visibility value or map should be
+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.
 
 <h2>SEE ALSO</h2>
 
-GRASS Wiki page about
-  <a href="http://grasswiki.osgeo.org/wiki/Atmospheric_correction">Atmospheric correction</a>
+GRASS Wiki page about <a href="http://grasswiki.osgeo.org/wiki/Atmospheric_correction">Atmospheric correction</a>
 <p>
 <em>
 <a href="i.aster.toar.html">i.aster.toar</a>,
@@ -884,7 +1039,7 @@ GRASS Wiki page about
 <h2>REFERENCES</h2>
 
 <ul>
-<li> Vermote, E.F., Tanre, D., Deuze, J.L., Herman, M., and Morcrette, J.J., 1997,
+<li>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.
 <!-- too new:
@@ -893,14 +1048,15 @@ overview., IEEE Trans. Geosc. and Remote Sens. 35(3):675-686.
    at the <a href="http://6s.ltdri.org">6S homepage</a> of the Land Surface Reflectance
    Science Computing Facility
 -->
-<li> 6S Manual: <a href="http://www.rsgis.ait.ac.th/~honda/textbooks/advrs/6smanv2.0_P1.pdf">PDF1</a>,
-     <a href="http://www.rsgis.ait.ac.th/~honda/textbooks/advrs/6smanv2.0_P2.pdf">PDF2</a>,
-     and <a href="http://www.rsgis.ait.ac.th/~honda/textbooks/advrs/6smanv2.0_P3.pdf">PDF3</a>
+<li>6S Manual: <a href="http://www.rsgis.ait.ac.th/~honda/textbooks/advrs/6smanv2.0_P1.pdf">PDF1</a>,
+    <a href="http://www.rsgis.ait.ac.th/~honda/textbooks/advrs/6smanv2.0_P2.pdf">PDF2</a>,
+    and <a href="http://www.rsgis.ait.ac.th/~honda/textbooks/advrs/6smanv2.0_P3.pdf">PDF3</a>
 <li>RapidEye sensors have been provided by <a href="http://www.rapideye.com/">RapidEye AG, Germany</a>
-<li> Julia A. Barsi, Brian L. Markham and Jeffrey A. Pedelty  "The operational land imager: spectral response and spectral uniformity", Proc. SPIE 8153, 81530G (2011); doi:10.1117/12.895438
+<li>Barsi, J.A., Markham, B.L. and Pedelty, J.A., 2011, The operational 
+land imager: spectral response and spectral uniformity., Proc. SPIE 8153,
+81530G; doi:10.1117/12.895438
 </ul>
 
-
 <h2>AUTHORS</h2>
 
 <p><em>Original version of the program for GRASS 5:</em>