Convert CRLF to LF

git-svn-id: https://svn.osgeo.org/grass/grass/trunk@33854 15284696-431f-4ddb-bdfa-cd5b030d7da7

imagery/i.modis.qc/i.modis.qc.html

@@ -1,97 +1,97 @@
-<H2>DESCRIPTION</H2>
-
-<EM>i.modis.qc</EM> Extracts Requested Quality Assessment flags from Modis 09 A and Q products 
-(Surface_reflectance_250/500m_quality_control_flags).
-This does not yet include QA_state_500m layer (see Notes and TODO).
-
-<pre>
-<EM>MODLAND QA Bits 250m/500m bits[0-1]</EM>
-</pre>
-<ul>
- <li>[00]= class 0: Corrected product produced at ideal quality -- all bands</li>
- <li>[01]= class 1: Corrected product produced at less than ideal quality -- some or all bands</li>
- <li>[10]= class 2: Corrected product NOT produced due to cloud effect -- all bands</li>
- <li>[11]= class 3: Corrected product NOT produced due to other reasons -- some or all bands maybe be fill value (Note that a value of [11] overrides a value of [01])</li>
-</ul>
-
-<pre>
-<EM>Cloud State 250m Unsigned Int bits[2-3] </EM>
-</pre>
-<ul>
- <li>[00]= class 0: Clear -- No clouds</li>
- <li>[01]= class 1: Cloudy</li>
- <li>[10]= class 2: Mixed</li>
- <li>[11]= class 3: Not Set ; Assumed Clear</li>
-</ul>
-
-<pre>
-<EM>Band-wise Data Quality 250m Unsigned Int bits[4-7][8-11]</EM>
-<EM>Band-wise Data Quality 500m long Int bits[2-5][6-9][10-13][14-17][18-21][22-25][26-29]</EM>
-</pre>
-<ul>
- <li>[0000]= class 0: highest quality</li>
- <li>[0111]= class 1: noisy detector</li>
- <li>[1000]= class 2: dead detector; data interpolated in L1B</li>
- <li>[1001]= class 3: solar zenith ge 86 degrees</li>
- <li>[1010]= class 4: solar zenith ge 85 and lt 86 degrees</li>
- <li>[1011]= class 5: missing input</li>
- <li>[1100]= class 6: internal constant used in place of climatological data for at least one atmospheric constant</li>
- <li>[1101]= class 7: correction out of bounds, pixel constrained to extreme allowable value</li>
- <li>[1110]= class 8: L1B data faulty</li>
- <li>[1111]= class 9: not processed due to deep ocean or cloud</li>
- <li>Class 10-15: Combination of bits unused</li>
-</ul>
-
-<pre>
-<EM>Atmospheric correction 250m/500m bit[12]/[30]</EM>
-</pre>
-<ul>
- <li>[0]= class 0: Not Corrected product</li>
- <li>[1]= class 1: Corrected product</li>
-</ul>
-
-<pre>
-<EM>Adjacency correction 250m/500m bit[13][31]</EM>
-</pre>
-<ul>
- <li>[0]= class 0: Not Corrected product</li>
- <li>[1]= class 1: Corrected product</li>
-</ul>
-
-<pre>
-<EM>Different orbit from 500m product, 250m Unsigned Int bit[14]</EM>
-</pre>
-<ul>
- <li>[0]= class 0: same orbit as 500m</li>
- <li>[1]= class 1: different orbit from 500m</li>
-</ul>
-
-
-<H2>NOTES</H2>
-It seems that cloud related info is not filled properly since version 3.
-State-QA 500m images should be used (see Vermote et al., 2008).
-
-<H2>TODO</H2>
-STATE-QA500m flag Processing should be included for detailed cloud status. 
-More testing is required.
-
-<H2>SEE ALSO</H2>
-
-Vermote E.F., Kotchenova S.Y., Ray J.P.
-MODIS Surface Reflectance User's Guide.
-Version 1.2. June 2008.
-MODIS Land Surface Reflectance Science Computing Facility.
-<A HREF="http://modis-sr.ltdri.org">Homepage</A><br>
-
-
-<em>
-<A HREF="i.vi.html">i.vi</A><br>
-</em>
-
-
-<H2>AUTHORS</H2>
-Yann Chemin, International Rice Research Institute, The Philippines.<BR>
-
-
-<p>
-<i>Last changed: $Date: 2008/07/28 15:33:42 $</i>
+<H2>DESCRIPTION</H2>
+
+<EM>i.modis.qc</EM> Extracts Requested Quality Assessment flags from Modis 09 A and Q products 
+(Surface_reflectance_250/500m_quality_control_flags).
+This does not yet include QA_state_500m layer (see Notes and TODO).
+
+<pre>
+<EM>MODLAND QA Bits 250m/500m bits[0-1]</EM>
+</pre>
+<ul>
+ <li>[00]= class 0: Corrected product produced at ideal quality -- all bands</li>
+ <li>[01]= class 1: Corrected product produced at less than ideal quality -- some or all bands</li>
+ <li>[10]= class 2: Corrected product NOT produced due to cloud effect -- all bands</li>
+ <li>[11]= class 3: Corrected product NOT produced due to other reasons -- some or all bands maybe be fill value (Note that a value of [11] overrides a value of [01])</li>
+</ul>
+
+<pre>
+<EM>Cloud State 250m Unsigned Int bits[2-3] </EM>
+</pre>
+<ul>
+ <li>[00]= class 0: Clear -- No clouds</li>
+ <li>[01]= class 1: Cloudy</li>
+ <li>[10]= class 2: Mixed</li>
+ <li>[11]= class 3: Not Set ; Assumed Clear</li>
+</ul>
+
+<pre>
+<EM>Band-wise Data Quality 250m Unsigned Int bits[4-7][8-11]</EM>
+<EM>Band-wise Data Quality 500m long Int bits[2-5][6-9][10-13][14-17][18-21][22-25][26-29]</EM>
+</pre>
+<ul>
+ <li>[0000]= class 0: highest quality</li>
+ <li>[0111]= class 1: noisy detector</li>
+ <li>[1000]= class 2: dead detector; data interpolated in L1B</li>
+ <li>[1001]= class 3: solar zenith ge 86 degrees</li>
+ <li>[1010]= class 4: solar zenith ge 85 and lt 86 degrees</li>
+ <li>[1011]= class 5: missing input</li>
+ <li>[1100]= class 6: internal constant used in place of climatological data for at least one atmospheric constant</li>
+ <li>[1101]= class 7: correction out of bounds, pixel constrained to extreme allowable value</li>
+ <li>[1110]= class 8: L1B data faulty</li>
+ <li>[1111]= class 9: not processed due to deep ocean or cloud</li>
+ <li>Class 10-15: Combination of bits unused</li>
+</ul>
+
+<pre>
+<EM>Atmospheric correction 250m/500m bit[12]/[30]</EM>
+</pre>
+<ul>
+ <li>[0]= class 0: Not Corrected product</li>
+ <li>[1]= class 1: Corrected product</li>
+</ul>
+
+<pre>
+<EM>Adjacency correction 250m/500m bit[13][31]</EM>
+</pre>
+<ul>
+ <li>[0]= class 0: Not Corrected product</li>
+ <li>[1]= class 1: Corrected product</li>
+</ul>
+
+<pre>
+<EM>Different orbit from 500m product, 250m Unsigned Int bit[14]</EM>
+</pre>
+<ul>
+ <li>[0]= class 0: same orbit as 500m</li>
+ <li>[1]= class 1: different orbit from 500m</li>
+</ul>
+
+
+<H2>NOTES</H2>
+It seems that cloud related info is not filled properly since version 3.
+State-QA 500m images should be used (see Vermote et al., 2008).
+
+<H2>TODO</H2>
+STATE-QA500m flag Processing should be included for detailed cloud status. 
+More testing is required.
+
+<H2>SEE ALSO</H2>
+
+Vermote E.F., Kotchenova S.Y., Ray J.P.
+MODIS Surface Reflectance User's Guide.
+Version 1.2. June 2008.
+MODIS Land Surface Reflectance Science Computing Facility.
+<A HREF="http://modis-sr.ltdri.org">Homepage</A><br>
+
+
+<em>
+<A HREF="i.vi.html">i.vi</A><br>
+</em>
+
+
+<H2>AUTHORS</H2>
+Yann Chemin, International Rice Research Institute, The Philippines.<BR>
+
+
+<p>
+<i>Last changed: $Date: 2008/07/28 15:33:42 $</i>

imagery/i.vi/i.vi.html

@@ -1,168 +1,168 @@
-<H2>DESCRIPTION</H2>
-
-<EM>i.vi</EM> calculates vegetation indices based on biophysical
-parameters.
-
-<ul>
-  <li>ARVI: atmospherically resistant vegetation indices</li>
-  <li>DVI: Difference Vegetation Index</li>
-  <li>EVI: Enhanced Vegetation Index</li>
-  <li>GARI: Green atmospherically resistant vegetation index</li>
-  <li>GEMI: Global Environmental Monitoring Index</li>
-  <li>GVI: Green Vegetation Index</li>
-  <li>IPVI: Infrared Percentage Vegetation Index</li>
-  <li>MSAVI2: second Modified Soil Adjusted Vegetation Index</li>
-  <li>MSAVI: Modified Soil Adjusted Vegetation Index</li>
-  <li>NDVI: Normalized Difference Vegetation Index</li>
-  <li>PVI: Perpendicular Vegetation Index</li>
-  <li>RVI: ratio vegetation index</li>
-  <li>SAVI: Soil Adjusted Vegetation Index</li>
-  <li>SR: Simple Vegetation ratio</li>
-  <li>WDVI: Weighted Difference Vegetation Index</li>
-</ul>
-
-<pre>
-ARVI: Atmospheric Resistant Vegetation Index 
-ARVI is resistant to atmospheric effects (in comparison to 
-the NDVI) and is accomplished by a self correcting process 
-for the atmospheric effect in the red channel, using the 
-difference in the radiance between the blue and the red 
-channels.(Kaufman and Tanre 1996).
-ARVI = (nirchan - (2.0*redchan - bluechan)) / 
-( nirchan + (2.0*redchan - bluechan))
-arvi( redchan, nirchan, bluechan )
-</pre>
-
-<pre>
-DVI: Difference Vegetation Index
-DVI = ( nirchan - redchan )
-dvi( redchan, nirchan )
-</pre>
-
-<pre>
-EVI: Enhanced Vegetation Index
-Huete A.R., Liu H.Q., Batchily K., vanLeeuwen W. (1997). 
-A comparison of vegetation indices global set of TM images for 
-EOS-MODIS. Remote Sensing of Environment, 59:440-451.
-EVI = 2.5 * ( nirchan - redchan ) / 
-( nirchan + 6.0 * redchan - 7.5 * bluechan + 1.0 )
-evi( bluechan, redchan, nirchan )
-</pre>
-
-<pre>
-GARI: green atmospherically resistant vegetation index
-GARI = ( nirchan - (greenchan-(bluechan - redchan))) / 
-( nirchan- (greenchan-(bluechan - redchan)))
-gari( redchan, nirchan, bluechan, greenchan )
-</pre>
-
-<pre>
-GEMI: Global Environmental Monitoring Index
-GEMI = (( (2*((nirchan * nirchan)-(redchan * redchan))+
-1.5*nirchan+0.5*redchan) / (nirchan + redchan + 0.5)) * 
-(1 - 0.25 * (2*((nirchan * nirchan)-(redchan * redchan))
-+1.5*nirchan+0.5*redchan) /(nirchan + redchan + 0.5)))-
-( (redchan - 0.125) / (1 - redchan))
-gemi( redchan, nirchan )
-</pre>
-
-<pre>
-GVI: Green Vegetation Index
-GVI = ( -0.2848 * bluechan - 0.2435 * greenchan - 
-0.5436 * redchan + 0.7243 * nirchan + 0.0840 * chan5chan-
-0.1800 * chan7chan)
-gvi( bluechan, greenchan, redchan, nirchan, chan5chan, chan7chan)
-</pre>
-
-<pre>
-IPVI: Infrared Percentage Vegetation Index 
-IPVI = nirchan/(nirchan+redchan)
-ipvi( redchan, nirchan )
-</pre>
-
-<pre>
-MSAVI2: second Modified Soil Adjusted Vegetation Index
-MSAVI2 = (1/2)*(2(NIR+1)-sqrt((2*NIR+1)^2-8(NIR-red)))
-msavi2( redchan, nirchan )
-</pre>
-
-<pre>
-MSAVI: Modified Soil Adjusted Vegetation Index
-MSAVI = s(NIR-s*red-a) / (a*NIR+red-a*s+X*(1+s*s))	
-where a is the soil line intercept, s is the
-soil line slope, and X 	is an adjustment factor
-which is set to minimize soil noise (0.08 in 
-original papers).			
-msavi( redchan, nirchan )
-</pre>
-
-<pre>
-NDVI: Normalized Difference Vegetation Index 
-Data Type Band Numbers ([IR, Red]) 
-TM Bands= [4,3] 
-MSS Bands = [7, 5] 
-AVHRR Bands = [2, 1] 
-SPOT XS Bands = [3, 2] 
-AVIRIS Bands = [51, 29] 
-
-
-(AVHRR) NDVI = (channel 2 - channel 1) / (channel 2 + channel 1)
-</pre>
-
-<pre>
-PVI: Perpendicular Vegetation Index
-PVI = sin(a)NIR-cos(a)red 
-for a isovegetation lines (lines of equal vegetation)
-would all be parallel to the soil line therefore a=1
-pvi( redchan, nirchan )
-</pre>
-
-<pre>
-SAVI: Soil Adjusted Vegetation Index
-SAVI = ((1.0+0.5)*(nirchan - redchan)) / (nirchan + redchan +0.5)
-savi( redchan, nirchan )
-</pre>
-
-<pre>
-SR: Simple Vegetation ratio
-SR = (nirchan/redchan)
-sr( redchan, nirchan )
-</pre>
-
-<pre>
-WDVI: Weighted Difference Vegetation Index
-WDVI = nirchan - a * redchan
-if(soil_weight_line == None):
-a = 1.0 #slope of soil line
-wdvi( redchan, nirchan, soil_line_weight )
-</pre>
-
-<H2>NOTES</H2>
-
-<pre>
-Originally from kepler.gps.caltech.edu
-A FAQ on Vegetation in Remote Sensing 
-Written by Terrill W. Ray
-	   Div. of Geological and Planetary Sciences
-	   California Institute of Technology
-email: terrill@mars1.gps.caltech.edu
-Snail Mail:  Terrill Ray
-	     Division of Geological and Planetary Sciences
-	     Caltech
-	     Mail Code 170-25
-	     Pasadena, CA  91125
-</pre>
-
-<H2>SEE ALSO</H2>
-
-<em>
-  <a href="i.albedo.html">i.albedo</a>
-</em>
-
-
-<H2>AUTHORS</H2>
-Baburao Kamble, Asian Institute of Technology, Thailand<br>
-Yann Chemin, Asian Institute of Technology, Thailand<br>
-
-<p>
-<i>Last changed: $Date: 2006/10/09 21:30:42 $</i>
+<H2>DESCRIPTION</H2>
+
+<EM>i.vi</EM> calculates vegetation indices based on biophysical
+parameters.
+
+<ul>
+  <li>ARVI: atmospherically resistant vegetation indices</li>
+  <li>DVI: Difference Vegetation Index</li>
+  <li>EVI: Enhanced Vegetation Index</li>
+  <li>GARI: Green atmospherically resistant vegetation index</li>
+  <li>GEMI: Global Environmental Monitoring Index</li>
+  <li>GVI: Green Vegetation Index</li>
+  <li>IPVI: Infrared Percentage Vegetation Index</li>
+  <li>MSAVI2: second Modified Soil Adjusted Vegetation Index</li>
+  <li>MSAVI: Modified Soil Adjusted Vegetation Index</li>
+  <li>NDVI: Normalized Difference Vegetation Index</li>
+  <li>PVI: Perpendicular Vegetation Index</li>
+  <li>RVI: ratio vegetation index</li>
+  <li>SAVI: Soil Adjusted Vegetation Index</li>
+  <li>SR: Simple Vegetation ratio</li>
+  <li>WDVI: Weighted Difference Vegetation Index</li>
+</ul>
+
+<pre>
+ARVI: Atmospheric Resistant Vegetation Index 
+ARVI is resistant to atmospheric effects (in comparison to 
+the NDVI) and is accomplished by a self correcting process 
+for the atmospheric effect in the red channel, using the 
+difference in the radiance between the blue and the red 
+channels.(Kaufman and Tanre 1996).
+ARVI = (nirchan - (2.0*redchan - bluechan)) / 
+( nirchan + (2.0*redchan - bluechan))
+arvi( redchan, nirchan, bluechan )
+</pre>
+
+<pre>
+DVI: Difference Vegetation Index
+DVI = ( nirchan - redchan )
+dvi( redchan, nirchan )
+</pre>
+
+<pre>
+EVI: Enhanced Vegetation Index
+Huete A.R., Liu H.Q., Batchily K., vanLeeuwen W. (1997). 
+A comparison of vegetation indices global set of TM images for 
+EOS-MODIS. Remote Sensing of Environment, 59:440-451.
+EVI = 2.5 * ( nirchan - redchan ) / 
+( nirchan + 6.0 * redchan - 7.5 * bluechan + 1.0 )
+evi( bluechan, redchan, nirchan )
+</pre>
+
+<pre>
+GARI: green atmospherically resistant vegetation index
+GARI = ( nirchan - (greenchan-(bluechan - redchan))) / 
+( nirchan- (greenchan-(bluechan - redchan)))
+gari( redchan, nirchan, bluechan, greenchan )
+</pre>
+
+<pre>
+GEMI: Global Environmental Monitoring Index
+GEMI = (( (2*((nirchan * nirchan)-(redchan * redchan))+
+1.5*nirchan+0.5*redchan) / (nirchan + redchan + 0.5)) * 
+(1 - 0.25 * (2*((nirchan * nirchan)-(redchan * redchan))
++1.5*nirchan+0.5*redchan) /(nirchan + redchan + 0.5)))-
+( (redchan - 0.125) / (1 - redchan))
+gemi( redchan, nirchan )
+</pre>
+
+<pre>
+GVI: Green Vegetation Index
+GVI = ( -0.2848 * bluechan - 0.2435 * greenchan - 
+0.5436 * redchan + 0.7243 * nirchan + 0.0840 * chan5chan-
+0.1800 * chan7chan)
+gvi( bluechan, greenchan, redchan, nirchan, chan5chan, chan7chan)
+</pre>
+
+<pre>
+IPVI: Infrared Percentage Vegetation Index 
+IPVI = nirchan/(nirchan+redchan)
+ipvi( redchan, nirchan )
+</pre>
+
+<pre>
+MSAVI2: second Modified Soil Adjusted Vegetation Index
+MSAVI2 = (1/2)*(2(NIR+1)-sqrt((2*NIR+1)^2-8(NIR-red)))
+msavi2( redchan, nirchan )
+</pre>
+
+<pre>
+MSAVI: Modified Soil Adjusted Vegetation Index
+MSAVI = s(NIR-s*red-a) / (a*NIR+red-a*s+X*(1+s*s))	
+where a is the soil line intercept, s is the
+soil line slope, and X 	is an adjustment factor
+which is set to minimize soil noise (0.08 in 
+original papers).			
+msavi( redchan, nirchan )
+</pre>
+
+<pre>
+NDVI: Normalized Difference Vegetation Index 
+Data Type Band Numbers ([IR, Red]) 
+TM Bands= [4,3] 
+MSS Bands = [7, 5] 
+AVHRR Bands = [2, 1] 
+SPOT XS Bands = [3, 2] 
+AVIRIS Bands = [51, 29] 
+
+
+(AVHRR) NDVI = (channel 2 - channel 1) / (channel 2 + channel 1)
+</pre>
+
+<pre>
+PVI: Perpendicular Vegetation Index
+PVI = sin(a)NIR-cos(a)red 
+for a isovegetation lines (lines of equal vegetation)
+would all be parallel to the soil line therefore a=1
+pvi( redchan, nirchan )
+</pre>
+
+<pre>
+SAVI: Soil Adjusted Vegetation Index
+SAVI = ((1.0+0.5)*(nirchan - redchan)) / (nirchan + redchan +0.5)
+savi( redchan, nirchan )
+</pre>
+
+<pre>
+SR: Simple Vegetation ratio
+SR = (nirchan/redchan)
+sr( redchan, nirchan )
+</pre>
+
+<pre>
+WDVI: Weighted Difference Vegetation Index
+WDVI = nirchan - a * redchan
+if(soil_weight_line == None):
+a = 1.0 #slope of soil line
+wdvi( redchan, nirchan, soil_line_weight )
+</pre>
+
+<H2>NOTES</H2>
+
+<pre>
+Originally from kepler.gps.caltech.edu
+A FAQ on Vegetation in Remote Sensing 
+Written by Terrill W. Ray
+	   Div. of Geological and Planetary Sciences
+	   California Institute of Technology
+email: terrill@mars1.gps.caltech.edu
+Snail Mail:  Terrill Ray
+	     Division of Geological and Planetary Sciences
+	     Caltech
+	     Mail Code 170-25
+	     Pasadena, CA  91125
+</pre>
+
+<H2>SEE ALSO</H2>
+
+<em>
+  <a href="i.albedo.html">i.albedo</a>
+</em>
+
+
+<H2>AUTHORS</H2>
+Baburao Kamble, Asian Institute of Technology, Thailand<br>
+Yann Chemin, Asian Institute of Technology, Thailand<br>
+
+<p>
+<i>Last changed: $Date: 2006/10/09 21:30:42 $</i>

raster/r.usler/Makefile

@@ -1,10 +1,10 @@
-MODULE_TOPDIR = ../..
-
-PGM = r.usler
-
-LIBES = $(GISLIB)
-DEPENDENCIES = $(GISDEP)
-
-include $(MODULE_TOPDIR)/include/Make/Module.make
-
-default: cmd
+MODULE_TOPDIR = ../..
+
+PGM = r.usler
+
+LIBES = $(GISLIB)
+DEPENDENCIES = $(GISDEP)
+
+include $(MODULE_TOPDIR)/include/Make/Module.make
+
+default: cmd

raster/r.usler/r.usler.html

@@ -1,24 +1,24 @@
-<h2>DESCRIPTION</h2>
-
-<em>r.usler</em> calculates USLE R factor for Rainfall erosivity. It
-enables several empirical equations: Roosle (1975), Morgan (1974),
-Foster(1981) and El-Swaify (1985).
-
-<h2>NOTES</h2>
-
-<h2>TODO</h2>
-
-<h2>SEE ALSO</h2>
-
-<em>
-  <a href="r.uslek.html">r.uslek</a>,
-  <a href="r.watershed.html">r.watershed</a
-</em>
-
-
-<h2>AUTHORS</h2>
-Natialia Medvedeva, SIC-ISDC, Ashgabat, Turkmenistan<br>
-Yann Chemin, SIC-ISDC, Ashgabat, Turkmenistan
-
-<p>
-<i>Last changed: $Date: 2008/10/12 08:30:42 $</i>
+<h2>DESCRIPTION</h2>
+
+<em>r.usler</em> calculates USLE R factor for Rainfall erosivity. It
+enables several empirical equations: Roosle (1975), Morgan (1974),
+Foster(1981) and El-Swaify (1985).
+
+<h2>NOTES</h2>
+
+<h2>TODO</h2>
+
+<h2>SEE ALSO</h2>
+
+<em>
+  <a href="r.uslek.html">r.uslek</a>,
+  <a href="r.watershed.html">r.watershed</a
+</em>
+
+
+<h2>AUTHORS</h2>
+Natialia Medvedeva, SIC-ISDC, Ashgabat, Turkmenistan<br>
+Yann Chemin, SIC-ISDC, Ashgabat, Turkmenistan
+
+<p>
+<i>Last changed: $Date: 2008/10/12 08:30:42 $</i>