## 2 Materials and Methods
### Geomorphological Features Mapping  
In the mapping of geomorphological features, we focused on the Hitardalur landslide, the landslide-dammed lake, and the riverbed with flowing water. Additionally, we differentiated between the landslide source and deposition area and identified changes in the watercourse based on the pre-and post-event images. We used an OBIA approach and created a knowledge-based classification ruleset in eCognition (Trimble) software, integrating Sentinel-1 and Sentinel-2 datasets. We used spectral indices derived from the Sentinel-2 data, including a brightness layer (average of the three visible spectral bands blue (B2), green (B3), red (B4)) and the normalized difference vegetation index (NDVI). For the detection of riverbeds, we calculated an edge extraction layer based on the Sentinel-2 NIR (B8) spectral band using the Lee sigma [65] algorithm. We also used the intensity information from the pre- and post-event Sentinel-1 VV, and VH polarization intensity images to create subtraction layers for 2018 and 2019. The Sentinel-1 intensity subtraction layers and the edge extraction layers derived from band B8 were used for the object-based classification for 2018 and 2019 and are shown in Figure 4. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Sentinel-1 Image Pairs** & **Orbit Track** & \begin{tabular}{c} **Flight** \\ **Direction** \\ \end{tabular} & \begin{tabular}{c} **Time Baseline** \\ **(Days)** \\ \end{tabular} & \begin{tabular}{c} **B\({}_{\text{perp}}\) (m)** \\ \end{tabular} & \
\begin{tabular}{c} **Modeled** \\ **Coherency** \\ \end{tabular} &
\begin{tabular}{c} **Height** \\ **Ambiguity (m)** \\ \end{tabular} \\ \hline
11 July 2018 and 17 July 2018 & 16 & Ascending & 6 & 134 & 0.88 & 115 \\
5 August 2018 and 11 August 2018 & 118 & Ascending & 6 & 142 & 0.87 & 110 \\
4 July 2019 and 10 July 2019 & 155 & Descending & 6 & 159 & 0.86 & 98 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Sentinel-1 data and their characteristics used to generate the digital elevation models (DEMs). The B\({}_{\text{perp}}\) stands for the spatial perpendicular baseline, which was used as the main criterion for the selection of Sentinel-1 A and B image pairs. The modeled coherency and height ambiguity measurements were derived using the interferometric synthetic aperture radar (SAR) (InSAR) stack overview function implemented in the Sentinel Application Platform (SNAP) toolbox. The Hitardalur landslide and landslide-dammed lake are distinguishable in the Sentinel-1 subtraction layer of the year 2018 (Figure 4a), but they are less obvious on the Sentinel-1 subtraction layer from 2019 (Figure 4b). Due to the SAR amplitude changes, the Hitardalur landslide appears very bright, and the landslide-dammed lake very dark on the Sentinel-1 subtraction layer of 2018 (Figure 4a). The white path visible on the Sentinel-1 VV polarization subtraction layer of 2018 (Figure 4a) is the Hitara riverbed (i.e., towards the south-west of the landslide). In the Sentinel-1 subtraction layer of the year 2019, the Hitara river change is hardly visible (Figure 4b). The Sentinel-2 edge extraction layer of the year 2018 clearly shows the new watercourse between the dammed lake and Stekka river (i.e., the river towards the south-east of the landslide) (Figure 4c). This connection, however, is not readily distinguishable on the edge extraction layer of the year 2019. In both images (Figure 4c,d), the outlines of the lake are partly visible, but, it is difficult to differentiate them from the edges of other features. The white circular area in Figure 4d is a cloud mask. The OBIA classification of the landslide was based on the pre- and post-event VV polarization subtraction layer, the brightness layer was used for the classification of the landslide-dammed lake, and the riverbed with water was classified using the edge extraction layer and refined based on spectral and spatial parameters. The first step in the object-based mapping was the creation of image objects using the multiresolution segmentation algorithm.