View source for Object-based supervised classification

=Object-based image analysis (OBIA) with QGIS and OTB processing plugin=
==Segmentation==
* In the search engine of Processing Toolbox, type {{typed|text=segmentation}} and double click '''Segmentation'''.
* Select the input image: '''a multispectral Sentinel-2 image''' (data type uint16).
* Set {{button|text=Segmentation algorithm}} to '''meanshift'''
* The {{button|text=Range radius}} value can be set to {{typed|text=600}}. The optimal value depends on datatype dynamic range of the input image and requires experimental trials for the specific classifcation objectives.
* Set {{button|text=Minimum Region size}} (in pixels) to {{typed|text=16}}.
* {{button|text=Processing mode}} '''Vector'''
* Set the {{button|text=Mask image}} to blank (top of drop-down list).
* Check {{button|text=8-neighborhood connectivity}} on.
* The {{button|text=Minimum object size}} (in pixels) can be set to {{typed|text=16}} depending on  minimum mapping size.
* Name the {{button|text=Output vector file}} e.g. '''segments_meanshift.shp'''. Extension should be '''.shp''' in this module).
* Click {{button|text=Run}}.

[[File:qgis_otb_segmentation.png|400px]]

* Evaluate the segmentation results: Load the output vector file '''segments_meanshift.shp''' into QGIS on top of the image ''Subset_S2A_MSIL2A_20170619T_Mul.tif''
Mark the vector layer in the Qgis Layers window. Right click {{mitem|text=Properties --> Symbology  --> Simple Fill}}, {{mitem|text=Fill Style}}: ''No Brush'' and {{mitem|text=Stroke color}}:''white''.

==Feature extraction==
In the search engine of Processing Toolbox, type {{typed|text=zonalstats}} and open '''ZonalStatistics''' under Image Manipulation of OTB.
* Select the Input image: '''a multispectral Sentinel-2 image'''.
* Background value to ignore: {{typed|text=65535}}
* For the {{button|text=Input vector data}} select a vector file with segments (output from Segmentation)
* File name for the output vector data: '''segments_stats.gpkg'''.
* Click {{button|text=Run}}.
[[File:otb_zonalstats.png|400px]]

==Training phase==
* In the search engine of Processing Toolbox, type {{typed|text=Train}} and double click '''TrainVectorClassifier'''.
* In the {{button|text=Input Vector Data List}} '''do not''' select a file from the list which is already loaded in the QGIS Viewer. There is currently a bug in QGIS 3.16 which leads to failure during file import. Instead please select a vector file clicking [[File:Qgis_add_file.png]] and browse directly to the file containing training area polygons in format GPKG or SHP e.g. {{button|text=lucc_training_obia.gpkg}}.
* ''Output model filename'' is {{button|text=svm_obia.model}}
* In the field ''Field names for training features'' copy and paste 
<pre> "mean_2 stdev_0 mean_9 mean_7 mean_0" </pre>
* This is one of many variable sets as a result of a feature selection procedure.
* The name of ''Field containing the class id for supervision" is {{button|text=C_ID}}.
* Classifier to use for training: {{button|text=libsvm}}
* SVM Kernel Type: {{button|text=linear}}
* SVM Model Type: {{button|text=csvc}}
* Click Parameters optimization{{button|text=ON}}.
* Click {{button|text=Run}}.
[[File:qgis_otb_trainvector.png|400px]]
{{info|message=Info|text=For more detailed information on the SVM algorithm visit the [http://www.csie.ntu.edu.tw/~cjlin/libsvm/ LibSVM website]}}

==Classification phase==
* In the search engine of Processing Toolbox, type {{typed|text=VectorClass}} and double click '''VectorClassifier'''.
* In the {{button|text=Input Vector Data}} '''do not''' select a file from the list which is already loaded in the QGIS Viewer. There is currently a bug in QGIS 3.16 which leads to failure during file import. Instead please select a vector file clicking [[File:Qgis_add_file.png]] and browse directly to the file containing segments and features for the whole image (result of Feature extaction)training area polygons in format GPKG {{typed|text=segments_meanshift_zonal.gpkg}}.
* Name of the input model file is {{typed|text=svm_obia.model}}.
* Output field containing the class is {{typed|text=C_ID}}
* Copy and paste into the field ''Field names to be calculated'' have to be the '''same features''' for prediction as were defined before in the TrainVectorClassifier module:
<pre> "mean_2 stdev_0 mean_9 mean_7 mean_0" </pre>
* Output vector Data file is {{typed|text=lucc_classified_obia.gpkg}}.
{{button|text=Run}}.

[[File:qgis_otb_vectorclassifier.png|400px]]

Load the output vector file manually into QGIS and apply the same QGIS style used for the training data. {{mitem|text=Layer --> Layer properties --> Symbology > Style --> Load style...}}.

[[Category:QGIS Tutorial]]