Tutorial: Random Forest Classification Using Remotior Sensus

This is a tutorial about Remotior Sensus, a Python package that allows for the processing of remote sensing images and GIS data.

In the last few months Remotior Sensus was frequently update to fix and integrate new functions, in particular for the integration with the Semi-Automatic Classification Plugin for QGIS.

In this tutorial we are going to use Remotior Sensus to perform the Random Forest classification of a Copernicus Sentinel-2 image, which involves the following main steps:

1. Create a BandSet using an image
2. Load a training input
3. Perform the random forest classification

Following, the basic tutorial as a Gist that you can open also in Google Colab and execute directly in the browser.

Link to the guide https://colab.research.google.com/gist/semiautomaticgit/5b3c6dca89b3764a69cf083cf3d0674f/random_forest_classification.ipynb