ENVI Machine Learning Unsupervised Classification Tutorial

The BIRCH Classification tool runs the memory-efficient BIRCH algorithm to construct a tree data structure with the cluster centroids being read off the leaf.

This tool performs unsupervised classification on a single raster. You provide an input raster and parameter settings to generate a classified raster. For more advanced options, you can use the Train Birch Tool to create a training model using one or more rasters, then perform classification using the model in the Machine Learning Classification Tool, or build a workflow in the ENVI Modeler.

For background on the algorithm used, see BIRCH Classification.

  1. From the Toolbox, select Machine Learning > Unsupervised > BIRCH Classification. The BIRCH Classification dialog appears.
  2. Click the Browse button next to the Input Raster field. In the Data Selection dialog that appears, select the input raster, perform optional spatial and spectral subsetting and/or masking, then click OK.
  3. Enter the maximum number of clustering feature subclusters in each node in the Branching Factor field. The default is 50.
  4. Enter the Number of Classes to identify. The default is 3.
  5. In the Threshold field, enter the radius of the subcluster obtained by merging a new sample and the closest subcluster should be less than the threshold. The default is 0.5.
  6. In the Output Raster field, enter a location and filename for the classification raster.
  7. In the Output Model field, enter a location and filename for the model.
  8. Enable the Display result check box to display the output in the view when processing is complete.

  9. To reuse these task settings in future ENVI sessions, save them to a file. Click the down arrow and select Save Parameter Values, then specify the location and filename to save to. Note that some parameter types, such as rasters, vectors, and ROIs, will not be saved with the file. To apply the saved task settings, click the down arrow and select Restore Parameter Values, then select the file where you previously stored your settings.

  10. You can run the process in the background on your computer or in the background on an ENVI Server (if available). Click the down arrow next to the OK button and select one of the following:

    • Run Task in the Background: Runs the process on your computer. This method does not use an ENVI Server. The job progress will show in the ENVI Job Console's Background Jobs tab.
    • Run Task on envi_server_name. Runs the process on the selected ENVI Server. The job progress will show in the ENVI Job Console's envi_server_name tab.

    In ENVI Help, see ENVI Job Console for details on monitoring ENVI Server jobs and viewing results, and see ENVI Servers for details on setting up an ENVI Server.

  11. To see a model-based version of this tool that shows how the tool is constructed from individual tasks, click Open in Modeler.

  12. Click OK.

See Also

ENVI Machine Learning Algorithms Background, Train Birch Tool, TrainBirch Task, Mini Batch K-Means Classification Tool