GLACIER VOLUME CHANGE MONITORING FROM UAV OBSERVATIONS: ISSUES AND POTENTIALS OF STATE-OF-THE-ART TECHNIQUES
- 1Leica Geosystems AG, Heerbrugg, Switzerland
- 2Department of Environmental Science and Policy, Università degli Studi di Milano, Milan, Italy
- 3Geodesy and Geomatics Division, DICEA, “La Sapienza” University of Rome, Rome, Italy
- 4Department of Architecture, Built Environment and Construction Engineering, Politecnico di Milano, Italy
Keywords: Glacier Monitoring, Volume Change, UAVs Photogrammetry, Accuracy Assessment, Point Cloud Co-registration
Abstract. Alpine glaciers play a key role in our society through the production of freshwater for domestic, industrial and agricultural use. As they are severely affected by climate change, it is of crucial importance to understand their behaviour and monitor their morphological evolution, with the primary aims to estimate ice volume and mass changes. However, the accurate retrieval of glacier morphology changes over time is not an easy task. In this context, the use of Unmanned Aerial Vehicles (UAVs) is of interest to the glaciological community because of their flexibility, fine spatial detail and ease of processing with state-of-the-art software packages, which makes them an ideal candidate to investigate glacier changes. The goal of this work is to assess the accuracy that can be obtained with UAVs observations when comparing volume changes computed from multi-temporal acquisitions on an Alpine glacier, on the basis of a photogrammetric pipeline implemented in Leica Infinity software. The study area is Forni Glacier in Raethian Alps, Italy. Two photogrammetric blocks were acquired in 2014 and 2016 using different UAVs: a fixed-wing drone in 2014 and an in-house multicopter in 2016. Ground Control Points (GCPs) were established only during the 2016 survey which was used to establish the reference datum. Different techniques to co-register the 2014 dataset to the 2016 dataset were applied and compared: 1) using points extracted from the 2016 Dense Point Cloud (DPC) as GCPs for the 2014 DPC generation; 2) shifting and rotating the raw 2014 DPC, using manually digitised common points from the 2014 and 2016 DPCs in Leica Infinity; 3) first manually shifting, then automatically roto-translating with the Iterative Closest Point (ICP) algorithm the raw 2014 DPC in CloudCompare. The investigation shows a good agreement of the three co-registration methods in terms of height and ice volume changes and the potential of UAV data processing with Leica Infinity for glacier monitoring even when the acquisition conditions are problematic (lack of ground control points, sub-optimal image quality).