Land cover classification using sentinel 1 GRD data

[ABraun]

one input image is not sufficient for a random forest classifier, because it needs a large variety of different input features (bands). We had some discussions on this here::

• Random forest Classificaption
• Number of training samples at Random forest classifier

Calculating image textures is a good way to increase the input features. Also using two images of different seasons often brings more variation.

Have you seen this approach: Landcover classification with Sentinel-1 GRD