Revision as of 14:52, 2 December 2018

Classification with Orfeo Toolbox

Type into the search box of the Windows taskbar: mapla.bat. Click on mapla.bat to open Monteverdi Application Launcher.
In the search engine of the Processing Toolbox, type ComputeImagesStatistics and double click ComputeImagesStatistics.
Specify a multispectral image as Input Image: the Sentinel-2 image Subset_S2A_MSIL2A_20170619T_MUL_BOA.tif
Specify directory and name for the XML Output image. Specify the extension .xml for this file.
Click on Execute.

Add the training areas as vector polygon file lab05_training_input.shp into QGIS.
Open Orfeo Toolbox --> TrainImageClassifier (libsvm) to use the Support Vector Machine SVM algorithm (see figure B).
Set Subset_S2A_MSIL2A_20170619T_MUL_BOA.tif as Input image list.
Set lab05_training_input.shp as Input vector list.
Set Subset_S2A_MSIL2A_20170619T_MUL_BOA.tif.xml as Input XML image statistics file.
Set Name of discrimination field to C_ID (C_ID refers to the column that contains the LUC code).
Save the Output confusion matrix as ConfusionMatrixSVM.csv.
Save the Output model as SVM.model.
Calculation of accuracies :
Open ConfusionMatrixSVM.csv in LibreOffice or MS Excel and calculate overall, producer and consumer accuracies.

Open Orfeo Toolbox --> Image Classification (see figure C).
Set Subset_S2A_MSIL2A_20170619T_MUL_BOA.tif as Input image.
Set SVM.model as Model file.
Set Subset_S2A_MSIL2A_20170619T_MUL_BOA.xml as Statistical file.
Save the Output image as su_svm.tif.
Evaluate classification results.
1. Add the classification result su_svm.tif to QGIS.
2. Right click su_svm.tif in the TOC and select Properties --> Style --> Style --> Load Style.
3. Load lab05_MinDist.qml.

@@ Line 1: / Line 1: @@
 = Classification with Orfeo Toolbox =
 == Image statistics ==
-# Add the Sentinel-2 imagery ''Subset_S2A_MSIL2A_20170619T_MUL_BOA.tif '' into a QGIS project.
+* Type into the search box of the Windows taskbar: {{typed|text=mapla.bat}}. Click on mapla.bat to open  Monteverdi Application Launcher.
-# Calculate mean and standard error for each band of the Sentinel-2 imagery using the OTB Graphical User Interface.
+* In the search engine of the Processing Toolbox, type {{typed|text=ComputeImagesStatistics}} and double click '''ComputeImagesStatistics'''.
-* In the Search box on the Windows Start menu type {{typed|text=OSGeo4W Shell}}. You should be able to open the shell by clicking on it.
+* Specify a multispectral image as Input Image: the Sentinel-2 image ''Subset_S2A_MSIL2A_20170619T_MUL_BOA.tif ''
-* Type into the shell: {{typed|text=otbgui_ComputeImagesStatistics}}.
+* Specify directory and name for the XML Output image. Specify the extension '''.xml''' for this file.
-Select a multiband input file and an output XML file as seen in the screenshot below.
+* Click on {{button|text=Execute}}.
 [[File:Qgis_ComputeImagesStatistics.png|500px]]