This tutorial is about the Random Forest classification using the Semi-Automatic Classification Plugin (SCP) for QGIS. It is assumed that one has the basic knowledge of SCP and Basic Tutorials.
Random Forest is a particular machine learning technique, based on the iterative and random creation of decision trees (i.e. a set of rules and conditions that define a class).
WARNING: ESA SNAP is required. The ESA SNAP GPT executable must be defined in External programs settings.
The purpose of the classification is to identify the following land cover classes:
- Water;
- Built-up;
- Vegetation;
- Soil.
The following are the steps of the tutorial:
- Input Data
- Create the ROIs
- Random Forest Classification
Following the video of this tutorial.