## 1 Introduction  
Mountainous areas can be complex and dangerous, characterized by high mountains and deep valleys, complex and changeable stratigraphic lithologies, complex geological structures, high vegetation coverage, and harsh and changeable climates. These areas bring considerable difficulty to the identification of geological disasters. As is typical of complex and dangerous mountainous areas, the Qinling-Daba Mountains have steep terrain, high vegetation coverage, complex lithology, and mountains and hills [1,2]. The distinctive terrain and local hydrological cycle make the rainfall in this area short-lived, strong and frequent [3]. In recent years, human engineering activities such as building railways, highways, and houses have gradually increased in frequency in the area. These activitieshave reduced vegetation and reduced slope stability. As a result, the rate of geological disasters, especially landslides, is increasing in the region. Therefore, the selection of appropriate and effective landslide-detection methods will be of great significance for the detection of geohazards in the Qinling-Daba Mountains and other similar areas. Due to the wide range of research areas, harsh environments, and complex terrains, it is difficult to monitor mountainous regions using traditional artificial and ground-based disasteridentification methods. Since [PERSON] first proposed the use of synthetic aperture radar interferometry technology (InSAR) to monitor small surface deformations in 1974 [4], the advantages of this technology has been demonstrated. These advantages include being independent of time and climate and having the ability to detect deformation with a high level of precision. Today, this technology is widely used in the early detection of landslides, debris flows, collapses, and other geological disasters over a large range [5; 6; 7]. InSAR technology used for geohazard monitoring can achieve millimeter-level accuracy, and good progress has been made [8; 9; 10]. In terms of data sources, there are several SAR satellites of different bands currently in orbit, including Sentinel\(-\)1A and Radarsat\(-\)2 in C\(-\)band, COSMO\(-\)SkyMed, TerraSAR\(-\)X in X\(-\)band, ALOS/PALSAR\(-\)2, SAOCOM, and L\(-\)SAR in L\(-\)band, etc. Each radar wavelength has its own penetration performance and accuracy in deformation monitoring; for example, long-wave radar has good penetration performance to ground objects at the cost of slightly lower deformation accuracy, while short-wave radar has higher deformation accuracy at the cost of weaker penetration performance. Each satellite has different characteristics. Free C\(-\)band Sentinel\(-\)1A/B data and L\(-\)band ALOS\(-\)2 data are two kinds of data with excellent performance and have become the leaders in radar data. Therefore, it is particularly important to consider the geological history and landslide characteristics of different regions in selecting the monitoring data most suitable to the region. To date, a large number of scholars have used SBAS\(-\)InSAR, PS\(-\)InSAR, and D\(-\)InSAR technology to detect potential geohazards in complex and dangerous mountainous areas and have obtained good monitoring results [11; 12; 13; 14], indicating that InSAR technology has substantial advantages in monitoring potential geohazards. Most of the work carried out in the Qinling-Daba Mountains is focused on geological mechanisms and characteristics [15; 16; 17; 18; 19]. Some scholars have also detected and studied typical geological hazards in the Qinling-Daba Mountains based on InSAR technology and analyzed the principles of their movement and the factors that induce movement. Study areas have included the Bailong River Basin [20; 21], the Jiangdingya landslide [22], and typical landslides in Lueyang County [23], with studies reaching a shared, clear understanding of the typical landslides in the region.