Abstract
Abstract. Image-based monitoring has emerged as a prevalent technique for sensing mountain environments. Monoscopic time-lapse cameras, which rely on digital image correlation to quantify glacier motion, have limitations due to the need for a Digital Elevation Model for deriving 3D flow velocity fields. Multi-camera systems overcome this limitation, as they allow for a 3D reconstruction of the scene. This paper presents a replicable low-cost stereoscopic system designed for 4D glacier monitoring. The system consists of independent and autonomous units, built from off-the-shelves components, such as a DSLR camera, an Arduino microcontroller, and a Raspberry Pi Zero, reducing costs compared to pre-built time-lapse cameras. The units are energetically self-sufficient and resistant to harsh alpine conditions. The system was successfully tested for more than a year to monitor the northwest terminus of the Belvedere Glacier (Italian Alps). Daily stereo-pairs acquired were processed with Structure-from-Motion to derive 3D point clouds of the glacier terminus and estimate glacier retreat and ice volume loss. By combining the information about ice volume loss with ablation estimates and ice flow velocity information, e.g., derived from monoscopic-camera time series, a multi-camera system enables a comprehensive understanding of sub-seasonal glacier dynamics.
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