Classifying a raster

Image classification is one of the most complex aspects of remote sensing. While QGIS is able to color pixels based on values for visualization, it stops short of doing much classification. It does provide a Raster Calculator tool where you can perform arbitrary math formulas on an image; however, it does not attempt to implement any common algorithms. The Orfeo Toolbox is dedicated purely to remote sensing and includes an automated classification algorithm called K-Means Clustering, which groups pixels into an arbitrary number of similar classes to create a new image. We can do a nice demonstration of image classification using this algorithm.

Getting ready

For this recipe, we will use a false color image, which you can download here:

https://github.com/GeospatialPython/Learn/raw/master/FalseColor.zip

Unzip this TIF file and place it in your /qgis_data/rasters directory.

How to do it...

All we need to do is run the algorithm on our input image. The important parameters...