## 2 Materials and Methods
### Data and Data Preparation
#### 2.2.2 Radar Data
\begin{table}
\begin{tabular}{c c c} \hline
**Date** & **Sensor, Product** & **Pre-/Post-Event** \\ \hline
20 June 2018 & Sentinel-2 B MSI, Level-1C & Pre \\
17 July 2018 & Sentinel-2 B MSI, Level-1C & Post \\
1 August 2019 & Sentinel-2 B MSI, Level-1C & Post \\ \hline \end{tabular}
\end{table} 
Table 1: Sentinel-2 datasets used in this research. MSI stands for Multispectral Instrument. Likewise, the height ambiguity (_ha_) was used as an indicator of the accuracy of the topographic height, which generates the 2-\(\pi\) InSAR phase change (Equation (1)), whereby the higher the B\({}_{\text{perp}}\), the more accurate the altitude measurement [57, 60]:  
\[ha=\ \frac{\lambda\,R\sin\theta}{2B_{\text{perp}}} \tag{1}\]  
where _ha_ is the height ambiguity, \(\lambda\) is the radar wavelength, \(R\) is the range from satellite to ground, and \(\theta\) is the look angle. From the above equation, it is clear that _ha_ is proportionally related to the B\({}_{\text{perp}}\), and a higher B\({}_{\text{perp}}\) theoretically should result in a more accurate altitude measurement. However, for a longer baseline, it is more difficult to solve the 2\(\pi\) phase ambiguity by phase unwrapping than for a shorter baseline [61]. Figure 3: Sentinel-1 and Sentinel-2 datasets used for geomorphological features mapping. The upper row shows the intensity layer for Sentinel-1 vertical-vertical (VV) polarization for the following image acquisition dates: (**a**) 5 July 2018; (**b**) 17 July 2018; (**c**) 5 August 2019. The lower row shows the true color composites of the Sentinel-2 images with the following acquisition dates: (**d**) 20 June 2018; (**e**) 17 July 2018; (**f**) 1 August 2019. The temporal interval between two SAR images was another factor to consider for the image selection. It influences the coherence, which determines how accurately the phase can be measured. A low coherence indicates a higher phase noise, which can cause larger elevation errors and phase unwrapping errors. A maximum relative coherency is recommended to be considered for the selection of SAR data pairs for DEM generation. Moreover, the interferometric phase depends on the orbit geometry, scene topography, line-of-sight surface displacements, and atmospheric path delays [62]. We used the Alaska Satellite Facility Baseline Tool to identify and select image pairs. From the available orbit tracks (i.e., number 16, number 118, and number 155), and flight directions (descending and ascending), we selected three post-event Sentinel-1 (A and B) image pairs (Table 2) for DEM generation and volume estimation. We used the InSAR stack overview function implemented in the SNAP (Sentinel Application Platform) toolbox to estimate the expected coherency (called \"modeled coherency\"), and the height ambiguity between two TOPSAR pair images. All SAR processing was completed using the open-source SNAP toolbox provided by ESA. Moreover, we used existing global earth topography and sea surface elevation data at 30 arc-second resolution (GETASSE30), which was freely available and accessible in the SNAP toolbox in the DEM generation process.