Unsupervised classification (Tutorial)

Latest revision as of 14:37, 24 November 2020

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.

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

@@ Line 1: / Line 1: @@
-{{construction}}
+==Unsupervised K-Means classification==
-:''This article is part of the [[QGIS tutorial 2013/14]].<br/>In this article, you will learn how to classify a landscape raster via k-means clustering''
+* In the search engine of the Processing Toolbox, type {{typed|text=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 {{button|text=uint 8}} from the pull-down list.
+* Set the {{button|text=Number of classes}} to {{typed|text=20}}
+* Check the {{button|text=Training set size}} to {{typed|text=10000}}
+* Output pixel type: {{typed|text=uint8}}
+* Click on {{button|text=Run}}.
+[[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.
+* {{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}}