The work analyses various remote sensing techniques utilized to monitor alpine glacier environments, which are crucial for agriculture, tourism and CO2 capture. Due to current climate change, these glacier environments are undergoing subtle changes and require constant monitoring. Using aircraft acquisition methods, DIGISKY s.r.l captured high-resolution RGB imagery (25 cm) of the Monte Bianco range. However, processing these large images posed challenges in terms of computational requirements. This study develops a workflow to minimize computational demands, with the entire analysis conducted using QGIS, an open-source software. The results highlight effective methodologies for efficient processing and monitoring of alpine glacier environments.This study focused on applying machine learning (ML) techniques to a rock debris glacier in the Monte Bianco range, specifically the Miage Glacier, one of the widest rock debris glaciers in Europe.