## 4 The Collapse of 24 November 2018
### Estimation of the Volumes Mobilised  
Terrestrial LiDAR (Light Detection and Ranging) and photogrammetry are two methods widely used in the study of rockfalls in high mountain areas [88; 89; 90] and elsewhere [91; 92; 93; 94; 95]. The volume of the collapse was reconstructed by comparing a point cloud acquired after the event (16 September 2019) by terrestrial LiDAR (Optech ILRIS-3D-ER; 2754 points per m\({}^{2}\)) from Gros Bechar (900 m NW of the scar; Figure 1) and a point cloud before the event obtained by photogrammetry using 33 IGN (French National Institute for Geographic and Forestry Information) RGB orthophotors of 2012 (1599 points per m\({}^{2}\)). This methodology has been widely used over the last 10 years to reconstruct post-event collapses [5; 96; 25].  
For this study, the methodology deployed by [PERSON] et al. [42] was remobilised in order to (1) generate a photogrammetry point cloud using aerial images from 2012, (2) clean the point cloud acquired by terrestrial LiDAR in 2019, (3) align the two pointclouds using the geometry of the cloud acquired by LiDAR, then (4) compare the two clouds, and (5) mesh the collapsed volume (Figure 4). Meshing, mapping, and computing rockfall volumes between 2012 and 2019 were carried out with 3 DReshaper software (2016 MR1 version). The workflow described by [PERSON] et al. [97] and applied by [PERSON] et al. [25] was used to generate point clouds of the rockwall using orthophotos of 2012. All the points were used for each meshing, and these were generated by a chordal deviation process with a maximum length of triangle edge of 3.5 m so as to fill the existing holes in the point clouds: the post-event cloud contains topographical masks, as it was acquired from a single position [88]. The collapse volume is 42,900 \(\pm\) 2200 m\({}^{3}\). Uncertainty is mainly depending on the different quality of the 3D mesh.  
In order to quantify the volume of the main deposit and compare it with the volume detached, a 3D model of the landslide deposit was created using photogrammetry with 437 photos taken by a DJI Phantom 4 drone on 5 December 2018. The model was geo-referenced using 11 ground control points, whose coordinates were determined through differential Global Navigation Satellite Systems. It was then compared to a 2008 LiDAR digital terrain model (from INRAE), assuming that the Taconnaz stream bed had not changed significantly between 2008 and 2018. The co-registration step involved aligning the photogrammetric model with the LiDAR model in stable areas, and the volume was then calculated only on the deposit. As the stable areas were not extensive enough, a level of detection (LoD) could not be calculated directly, so we used a LoD of 20 cm. The deposit volume was finally close to 30,000 m\({}^{3}\) (Figure 5). The melting of the snow and ice included in the deposit released a rockfall deposit whose volume was smaller than after the event due to the melting of the ice. Unfortunately, we were unable to acquire a new digital terrain model at that time, which would have allowed us to accurately quantify the amount of ice in the deposit. However, we estimated the height of the remaining deposit front to be around 1.5 m. As the front of the deposit initially measured 6.5 m, the percentage of ice could be close to 75%. This means that the rock volume of the deposit would be only around 7500 m\({}^{3}\).  
Estimating that \(\sim\)8000 m\({}^{3}\) of rock were left at the foot of the scar, that 4000 to 5000 m\({}^{3}\) could have sequestered in crevasses (\(\sim\)1.4 km of crevasses intersected by the rockfall based on measurements on Spot6 2016 images), that the sheets of debris may possibly represent up to 10,000 or 15,000 m\({}^{3}\), and that the volume of the scar includes volumes that fell in 2019 (even if this is essentially a transfer of mass by slow sliding from the middle of the scar towards the downstream part of it; see Section 4.4), this result does not seem abnormal.