Time-lapse stereo-cameras and photogrammetry for continuous 3D monitoring of an alpine glacier

Photogrammetry and Structure-from-Motion have become widely assessed tools for geomorphological 3D reconstruction, and especially for monitoring remote and hardly accessible alpine environments. UAV-based photogrammetry enables large mountain areas to be modelled with high accuracy and limited costs. However, they still require a human intervention on-site. The use of fixed time-lapse cameras for retrieving qualitative and quantitative information on glacier flows have recently increased, as they can provide images with high temporal frequency (e.g., daily) for long-time spans, and they require minimum maintenance. However, in many cases, only one camera is employed, preventing the use of photogrammetry to compute georeferenced 3D models. This work presents a low-cost stereoscopic system composed of two time-lapse cameras for continuously and quantitatively monitoring the north-west tongue of the Belvedere Glacier (Italian Alps), by using a photogrammetric approach. Each monitoring station includes a DSLR camera, an Arduino microcontroller for camera triggering, and a Raspberry Pi Zero with a SIM card to send images to a remote server through GSM network. The instrumentation is enclosed in waterproof cases and mounted on tripods, anchored on big and stable rocks along the glacier moraines. The acquisition of a defined number of images and the timing can be arbitrary scheduled, e.g., 2 images per day acquired by each camera, around noon. A set of ground control points is materialized on stable rocks along the moraines and measured with topographic-grade GNSS receivers at the first epoch to orient stereo-pairs of images. From daily stereo-pairs, 3D models are computed with the commercial Structure from Motion software package Agisoft Metashape, and they can be used to detect morphological changes in the glacier tongue, as well as to compute daily glacier velocities. The work is currently focused on improving the orientation of stereo-pairs: the use of computer vision algorithms is under study to automatize the process and increase the robustness of consecutive orientation of stereo-images, e.g., by including images coming from different epochs in the same bundle block adjustment and dividing them afterwards for dense 3D reconstruction. Change detection can be then computed from 3D point clouds by using M3C2 algorithms. Although the stereoscopic system is already installed on the Belvedere Glacier and it is properly taking daily images of the glacier tongue, the processing workflow of stereo-pairs needs to be tuned and automatized to enable high-accurate continuous 3D photogrammetric monitoring of an alpine glacier, computing short-term and infra-seasonal ice volume variations and velocities, as well as detecting icefalls.