Hi @bgumwelt,

it is not possible to run supervised classification directly in Sentinel Hub.

You might however find this blog post series relevant, where we demonstrate, start-to-end, on how to do supervised classification using eo-learn and Sentinel Hub, with a Jupyter Notebook sample with all the steps:

Land Cover Classification with eo-learn: Part 1

Mastering Satellite Image Data in an Open-Source Python Environment

Reading time: 8 min read

You should be able to modify this for your use-case pretty easily.

An example of the script for SCL is here:
https://shforum.sinergise.com/t/l2a-scene-classification-for-sentinel-2/51

You can find CLM and CLP cloud masks directly along the Sentinel-2 bands, see:

Sentinel Hub

Sentinel Hub is multi-spectral, temporal satellite imagery service for real-time processing of big remote sensing data.

More info here:

Sentinel Hub

Sentinel Hub is multi-spectral, temporal satellite imagery service for real-time processing of big remote sensing data.

The masks are not the same as L2A scene classification, as those are done using Sen2Cor algorithm and CLM/CLP use s2cloudless algorithm.