Autonomous UAVs for Monitoring Glacier Dynamics and Hazards: A Case Study from Jostedalsbreen, Norway

Monitoring glaciers is essential for understanding their response to climate change, managing freshwater resources, and mitigating geohazards such as icefalls and glacial lake outburst floods (GLOFs). Traditional glacier monitoring techniques often face challenges connected to limited spatial and temporal resolution and logistical constraints in hazardous terrain. These challenges are especially pronounced for steep and fast-moving glaciers with large surface changes and high velocities. In such settings high temporal and spatial resolution data are essential for capturing rapid surface changes and understanding glacier dynamics.

We introduce the potential of autonomous unmanned aerial vehicles (UAVs) operating from stationary drone docks as a novel, flexible, and cost-effective solution for glacier monitoring. We tested a DJI Dock 2 at Flatbreen and Bøyabreen, two outlet glaciers of the Jostedalsbreen ice cap in Western Norway. We captured high-resolution aerial imagery for photogrammetric mapping, conducted at customizable intervals (hourly, daily, weekly). These datasets enabled the generation of multitemporal point clouds, digital terrain models and orthophotos. To derive surface velocities and detect changes over time we used the 3D point cloud analysis algorithm M3C2 and 2D feature-tracking methods.

Preliminary findings revealed that autonomous UAVs can monitor surface changes and velocity patterns effectively with a high temporal and spatial resolution. Surface velocities for both glaciers ranged from 0.4 to 1.5 m per day, with higher rates observed in steeper sections of the glacier. The data offers unique insights on short-term processes, including acceleration phases, crevassing, the collapse of subglacial cavities and several significant icefall events. The results demonstrate a level of detection of 2-4 cm, which allows for the identification of subtle changes at cm-scale. Integrating autonomous UAVs into existing glacier monitoring frameworks represents a significant advancement in data collection by improving spatial and temporal resolution and time efficient workflows through automation in data collection and post processing.

This study highlights the feasibility and effectiveness of autonomous UAVs for near-continuous glacier and geohazard monitoring, particularly valuable in inaccessible or dangerous environments. We demonstrate the potential of autonomous UAVs to track both long-term glacier dynamics and short-term changes. This capability enhances process understanding and provides a robust foundation for developing UAV based early warning systems for glacial hazards. While challenges remain, particularly in difficult weather conditions, low visibility, and regulatory compliance, this innovative approach demonstrates substantial potential for monitoring, supporting effective risk management in regions vulnerable to glacial hazards.