2.34. Image classification

Performs automatic classification of an image (e.g. satellite image) based on a vector layer with training polygons. Random Forest algorithm is used.

You’ll need to input two files:

  • Image in GDAL-compatible format (preferably GeoTIFF). It can contain any number of bands, all of which will be used for classification.

  • Polygon vector layer with training objects. Any OGR-compatible vector format (preferably GeoPackage) is supported. Each polygon should have a field with object class number in its attributes.

Set up the parameters:

  • Name of the attribute that describes the class number for each object in the training polygons layer. The attribute must be an integer.

  • The number of trees in the decision forest. Leave blank to use the default value (100).

  • Maximum tree depth. Leave blank to not limit the tree depth.

Output:

  • Classified raster.

  • Classification report. It records the overall quality of the classification, the number of misclassified pixels in each class (and indicates the classes to which they were put instead).

Launch instrument: https://toolbox.nextgis.com/operation/image_classification

Try it out using our sample:

Download input dataset to test the instrument. Step-by-step instructions included.

Get the output to additionally check the results.