## 2 Data and Methods
### Camera Data and Methods  
Time-lapse and video camera employment has shown to be of great use to monitor volcanic processes, as it provides visual support that helps to interpret data associated with plumes [40], erosion processes at Volcan de Colima, Mexico [41], gas pistoning at Kilauea, Hawaii [42], lava flow surface velocities [43], and surface deformation at Mount St. Helens, USA [44]. Cameras can provide data on a volcano edifice from different viewing angles, allowing one to study specific details such as the migration of eruption vents. In total, we installed seven digital time-lapse cameras (Reconyx Ultrafire XR6) located around the eruption site to record images with a resolution of 3776 \(\times\) 2124 pixels on a regular interval. Here, we used three of the cameras that have a good view onto the craters (Figure 1), for which we set the time-lapse interval to 1 image every 15 min, day and night. The three cameras had two lenses each to capture images in RGB during the day, and at night, they shifted to residual light view mode. Camera 1 was installed at \(\sim\)1500 m distance from the erupting vents at 28.607\({}^{\circ}\)N, 17.849\({}^{\circ}\)W at 1605 m above sea level and recorded from 2 October 2021, until the end of the eruption. The field of view (FOV) covered the SE part of the active craters, facing toward the NW direction. Camera 2 was installed at \(\sim\)500 m from the erupting vents at 28.618\({}^{\circ}\)N, 17.860\({}^{\circ}\)W at 1087 m height, and operated from 11 November 2021, onward. The FOV covered the NE craters and was facing SW. Camera 3 was installed on 28.612\({}^{\circ}\)N, 17.863\({}^{\circ}\)W at 1055 m height on 4 December 2021. It lookedtoward the SE flank facing NW and was located at a distance of \(\sim\)140 m from the closest vent. For the time-lapse camera data processing, we used the image metadata (exit file), providing time and date (in UTC) and camera characteristics. We resampled the data by time to select only one picture every 15 min for each camera. The images were scaled from pixel to meter. For this, we measured the distance in meters using the DEM between two prominent marker points visible in each view of the cameras. Then, the images were processed in the Fiji ImageJ open source software package with the multi-kymograph tool. Kymographs are space vs. time plots that serve to analyze dynamic volcanic processes [14; 25; 40; 45]. This allowed us to extract the pixel values (RGB or intensity) along a predefined profile and assemble the profiles from all images together (Figure 3). The graph's x-axis corresponds to the number of pixels along the profile, and the y-axis corresponds to the time of each pixel row. To overcome differences between day (RGB) and nighttime (grayscale) images, we concentrated on the nighttime images only, acquired from 20h00 to 08h00 (UTC). To improve the contrast for better visual analysis we plotted the kymographs in a jet color theme, showing the bright nighttime lava fountains by warmer colors (red, orange, and yellow). For the kymographs analysis, we manually picked a trend line following the highest intensity values representing the lava fountains' activity. With this, it was possible to identify periods of stability and instability in the vent activity. Similarly, it was possible to identify intermittent activity between nearby lava vents in the NW cone and more drastic changes such as shifts in activity from the NW to SE vents. This helped identify the vent activity's general trend during the eruption. Changes in the position of lava fountains were  
Figure 3: Camera views and profiles. (**a**) Camera 1 view from 1500 m distance to the NW, (**b**) camera 2 view from 500 m distance to the SW, and (**c**) camera 3 view from 140 m distance to the NW. The red line represents the profile generated for the different camera views to extract the pixel values for further processing. All of the profiles were extracted from SE to NW. (**d**) Kymograph generation demonstration for camera 2 dataset.