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Geoprocessing with Python by Chris Garrard

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Chapter 12. Map classification

This chapter covers

  • Using the spectral module for unsupervised map classification
  • Using the scikit-learn module for supervised map classification

One common use for raster data is map classification, which involves categorizing the pixels into groups. For example, say you wanted to create a vegetation landcover dataset. You might use satellite imagery, elevation, slope, geology, precipitation, or other input data in order to create your classifications. The techniques we’ve looked at so far will help you prepare your datasets, but you need something else in order to classify pixels. Many different classification techniques exist, and which one you use will probably depend on your use case and available resources. ...

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