Commit 5670af30 authored by Manuel Grizonnet's avatar Manuel Grizonnet

DOC: spelling in app-python-en

parent fa9fef47
...@@ -210,7 +210,7 @@ ExtractROI.STARTX=140 ...@@ -210,7 +210,7 @@ ExtractROI.STARTX=140
- SRE: (SRE for Surface REflectance) corrected for atmospheric effects, - SRE: (SRE for Surface REflectance) corrected for atmospheric effects,
including adjacency effects including adjacency effects
- FRE: (FRE for Flat REflectance) are also corrected for slope effect, - FRE: (FRE for Flat REflectance) are also corrected for slope effect,
which consists in suppressing the apparent reflectances which consists in suppressing the apparent reflectance
variations. The corrected images look like if the land was flat. variations. The corrected images look like if the land was flat.
- MTD: Metadata - MTD: Metadata
- QKL: quicklook file (low resolution image to show an RGB overview ) - QKL: quicklook file (low resolution image to show an RGB overview )
...@@ -265,7 +265,7 @@ ExtractROI.STARTX=140 ...@@ -265,7 +265,7 @@ ExtractROI.STARTX=140
*Note:* Make sure that OTB binary files ($otb-path/bin) is included *Note:* Make sure that OTB binary files ($otb-path/bin) is included
in your PATH environment variable. in your PATH environment variable.
4. Look at /MASKS subfolder : there is a CLM file that contains a cloud 4. Look at /MASKS sub-folder : there is a CLM file that contains a cloud
mask. Do you think that this information might be interesting to mask. Do you think that this information might be interesting to
make better water detections? How? make better water detections? How?
...@@ -317,7 +317,7 @@ ExtractROI.STARTX=140 ...@@ -317,7 +317,7 @@ ExtractROI.STARTX=140
| Parameter Key | Parameter Name | Parameter Type | | Parameter Key | Parameter Name | Parameter Type |
|---------------+------------------------+----------------| |---------------+------------------------+----------------|
| inr | Reference Input | input image | | inr | Reference Input | input image |
| inm | The image to reproject | input image | | inm | Image to re-project | input image |
| out | Output image | output image | | out | Output image | output image |
2. Open ~exercise1.py~ and complete the "FILL THE GAP 1". 2. Open ~exercise1.py~ and complete the "FILL THE GAP 1".
...@@ -598,7 +598,7 @@ ExtractROI.STARTX=140 ...@@ -598,7 +598,7 @@ ExtractROI.STARTX=140
#+BEGIN_EXAMPLE #+BEGIN_EXAMPLE
application2.SetParameterString("exp", "(im1b1-im2b1)/(im1b1+im2b1)<0?1:0") application2.SetParameterString("exp", "(im1b1-im2b1)/(im1b1+im2b1)<0?1:0")
#+END_EXAMPLE #+END_EXAMPLE
4. The lines with ~ApplicationX.Execute()~ will not launch inmediatly the ApplicationX. This line 4. The lines with ~ApplicationX.Execute()~ will not launch immediately the ApplicationX. This line
just describes that the ApplicationX will be launched in a pipeline sequence. just describes that the ApplicationX will be launched in a pipeline sequence.
When another ~ApplicationY.ExecuteAndWriteOutput()~ is further applied When another ~ApplicationY.ExecuteAndWriteOutput()~ is further applied
in the same pipeline, where the inputs of ApplicationY are dependent of the in the same pipeline, where the inputs of ApplicationY are dependent of the
...@@ -620,7 +620,7 @@ ExtractROI.STARTX=140 ...@@ -620,7 +620,7 @@ ExtractROI.STARTX=140
appX.SetParameterOutputImagePixelType("out", \ appX.SetParameterOutputImagePixelType("out", \
"water_mask.tif?&gdal:co:NBITS=1") "water_mask.tif?&gdal:co:NBITS=1")
#+END_EXAMPLE #+END_EXAMPLE
This solution will use just 1 bit per pixel. For a better understading, This solution will use just 1 bit per pixel. For a better understanding,
see module "Internals". see module "Internals".
*** Water detection chain with NoData management: exercise4.py *** Water detection chain with NoData management: exercise4.py
...@@ -664,7 +664,7 @@ ExtractROI.STARTX=140 ...@@ -664,7 +664,7 @@ ExtractROI.STARTX=140
20171203 >> GSW_20 (kappa = 0.5677) 20171203 >> GSW_20 (kappa = 0.5677)
4. The water surface contained in the 20161218 image (the dryest one) is seen at least 4. The water surface contained in the 20161218 image (the driest one) is seen at least
75% of the times (during the 32 years of Landsat observations). 75% of the times (during the 32 years of Landsat observations).
The second image have a water extent that has been seen only 10% of the times The second image have a water extent that has been seen only 10% of the times
and the third one only the 20% of the times. and the third one only the 20% of the times.
......
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