## 2 Study Area and Data
### Data  
As short-wave and long-wave SAR data sources, Sentinel\(-\)1A and ALOS/PALSAR\(-\)2 have stable satellite flight and excellent performance in obtaining deformation time-series data. They represent the most commonly used radar-satellite data. Therefore, these two mainstream data types were chosen for comparison and analysis of their adaptability to use in landslide monitoring.  
In 2014, the ESA launched the environmental observation satellite Sentinel\(-\)1A and implemented a policy of free and open use. This satellite is equipped with a C\(-\)band (5.6 cm) sensor and uses a new terrain-observation method with progression scans (TOPS) imaging technology [36]. Its short revisit period (12 days), wide coverage, rich collection of archived and open-access data, and sensitivity to surface deformation have made it an important data source for monitoring of deformations such as landslides and earthquakes. However, it still has some disadvantages, such as its low resolution and weak penetration [37; 38]. ALOS\(-\)2 is a land-observing satellite equipped with SAR sensors that was launched by Japan's JAXA in 2014. It has three types of imaging: strip, spotlight, and wide-mode. The radar sensor PALSAR (Phased Array type L\(-\)band Synthetic Aperture Radar) has a wavelength in the L\(-\)band that has better penetrating ability than other short-band sensors [36], and its performance is significantly better than that of ALOS\(-\)1. The radar images have high spatial resolution, and richer information can be obtained in mountainous areas [39; 40], making this sensor suitable for resource investigation, geohazard monitoring and mapping, etc.  
In this paper, the coverage areas of Sentinel\(-\)1A and ALOS/PALSAR\(-\)2 are clipped (Figure 1) to compare the potential of the two data sources to be adapted for use in landslide detection. The main parameters of the two satellite sensors and the details of the images used in this experiment are shown in Tables 1 and 2. For distributed backscattering points, the longer the baseline, the lower the coherence. Therefore, it is particularly important to set the appropriate baseline threshold. The Sentinel\(-\)1A data have poor penetration and a short revisit period, while the ALOS/PALSAR\(-\)2 data are the opposite. To combine these data characteristics and ensure that sufficient interference pairs can be obtained, we set the temporal and spatial baselines of the Sentinel\(-\)1A to 48 days and \(\pm\)150 and the temporal and spatial baselines of ALOS/PALSAR\(-\)2 are set to 140 days and \(\pm\)150. Finally, 55 and 33 interference pairs were generated, respectively (Figure 2).  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Satellite**} & **Wave Band** & **Incidence** & \multirow{2}{*}{**Mode**} & \multirow{2}{*}{**Resolution**} & \multirow{2}{*}{**Period**} \\  & **(Wavelength/cm)** & & & & \\ \hline \multirow{2}{*}{Sentinel\(-\)1A} & \multirow{2}{*}{C(5.6)} & 37.76 & Interferometric & \multirow{2}{*}{2.32 \(\times\) 13.97} & 12 \\  & & & & Wide(IW) & \\ \multirow{2}{*}{ALOS/PALSAR\(-\)2} & \multirow{2}{*}{L(25)} & 36.18 & Spotlight & \multirow{2}{*}{1.43 \(\times\) 2.12} & 14 \\ \hline \hline \end{tabular}
\end{table}
Table 1: The parameters of Sentinel\(-\)1A and ALOS/PALSAR\(-\)2 sensors.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Satellite**} & **Orbit** & **Number of** & \(\Delta\)**T**1  & **B\({}_{\perp}\)**2  \\  & **Directon** & **Images** & **(days)** & **(meters)** & **Master** & **Start-Stop Time** \\ \hline \multirow{2}{*}{Sentinel\(-\)1A} & \multirow{2}{*}{Ascending} & 19 & 12–48 & 0.9–146 & 20220126 & 20210925\(-\) \\  & & & & & 20220604 \\ \multirow{2}{*}{ALOS/PALSAR\(-\)2} & \multirow{2}{*}{Ascending} & 10 & 14–140 & 4.2–146.1 & 20220129 & 20210928\(-\) \\  & & & & & 20220607 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Basic description of the SAR data used herein.