Assessing glacier thickness changes with multi-temporal UAV-derived DEMs: The evolution of Forni Glacier over the period 2014–2022

Abstract

Glaciers in the European Alps are undergoing significant retreat and thickness decrease due to climate change, contributing to sea-level rise and impacting the mountain environment and its biodiversity, tourism and local economy. Unmanned Aerial Vehicle (UAV) photogrammetry offers cost-effective methods for high-resolution glacier monitoring. However, multi-temporal UAV-based data usually must be improved in terms of consistency due to possible variable survey conditions, requiring precise co-registration. This study presents a novel application of the Iterative Closest Point algorithm of the NASA Ames Stereo Pipeline to co-register Digital Elevation Models (DEMs) from UAV images of Forni Glacier (Italy) collected under different conditions from 2014 to 2022. We co-registered the DEMs generated from Structure-from-Motion/Multi-View Stereo matching within a pairwise structure. This process demonstrated clear improvements in data consistency, with mean and median values tending to zero, RMSEs below 0.50 m, and NMADs below 0.32 m. The comparison of co-registered DEM highlighted glacier thickness losses at the terminus reaching 50 m, with side areas showing smaller reductions of around 25 m between 2014 and 2022.

Keywords

• UAV photogrammetry
• Multi-temporal UAV data
• DEM generation
• DEM co-registration
• Climate change
• Glacier monitoring