Unsupervised classification (Tutorial)

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(Unsupervised K-Means classification)
 
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==Unsupervised K-Means classification==
 
==Unsupervised K-Means classification==
 
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* In the search engine of the Processing Toolbox, type {{typed|text=kmeans}} and double click '''KMeansClassification''' of OTB.
* Type into the search box of the Windows taskbar: {{typed|text=mapla.bat}}. Click on mapla.bat to open the Monteverdi Application Launcher.
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* In the search engine of the Processing Toolbox, type {{typed|text=kmeans}} and double click '''KMeansClassification'''.
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* Specify a multispectral image as Input Image.
 
* Specify a multispectral image as Input Image.
 
* Specify directory and name for the Output image. Select the output data type {{button|text=uint 8}} from the pull-down list.
 
* Specify directory and name for the Output image. Select the output data type {{button|text=uint 8}} from the pull-down list.
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* Check the {{button|text=Training set size}} to {{typed|text=10000}}
 
* Check the {{button|text=Training set size}} to {{typed|text=10000}}
 
* Output pixel type: {{typed|text=uint8}}
 
* Output pixel type: {{typed|text=uint8}}
* Click on {{button|text=Execute}}.
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* Click on {{button|text=Run}}.
 
[[File:qgis_otb_kmeans.png|400px]]
 
[[File:qgis_otb_kmeans.png|400px]]
  
 
* Load the resulting image into QGIS. It is single band file with 20 grey levels labeled from 0 to 19.
 
* Load the resulting image into QGIS. It is single band file with 20 grey levels labeled from 0 to 19.
 
* {{mitem|text=Layer Properties --> Symbology --> Render type}}. Switch to {{button|text=Singleband pseudocolor}} and select a '''Color ramp''' (e.g. Spectral). Select the '''Mode''' {{button|text=Equal interval}} and set the number of classes to {{typed|text=20}}
 
* {{mitem|text=Layer Properties --> Symbology --> Render type}}. Switch to {{button|text=Singleband pseudocolor}} and select a '''Color ramp''' (e.g. Spectral). Select the '''Mode''' {{button|text=Equal interval}} and set the number of classes to {{typed|text=20}}
 
[[Category:QGIS Tutorial]]
 

Latest revision as of 14:37, 24 November 2020

[edit] Unsupervised K-Means classification

  • In the search engine of the Processing Toolbox, type kmeans and double click KMeansClassification of OTB.
  • Specify a multispectral image as Input Image.
  • Specify directory and name for the Output image. Select the output data type uint 8 from the pull-down list.
  • Set the Number of classes to 20
  • Check the Training set size to 10000
  • Output pixel type: uint8
  • Click on Run.

Qgis otb kmeans.png

  • Load the resulting image into QGIS. It is single band file with 20 grey levels labeled from 0 to 19.
  • Layer Properties --> Symbology --> Render type. Switch to Singleband pseudocolor and select a Color ramp (e.g. Spectral). Select the Mode Equal interval and set the number of classes to 20
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