## 1 Introduction  
The development of a large-scale multi-scale  
## 1 Introduction  
Geological deformation induced by open-pit mining has become a critical factor threatening safe production in mining regions. Large-scale mining activities often trigger geological disasters such as surface subsidence and slope instability, which not only threaten the stability of mining infrastructure but also pose significant threats to human safety [1, 2, 3]. Therefore, large-scale, high-precision, rapid-response surface deformation monitoring in mining areas is undoubtedly crucial in order to identify safety issues in mining areas [4]. Traditional in situ monitoring methods, such as the Global Navigation Satellite System (GNSS), leveling, and distributed fiber-optic sensing, suffer from limitations including single-point constraints, low efficiency, and elevated costs, rendering them inadequate for large-scale, continuous monitoring in mining areas [5]. The time-series InSAR (TS-InSAR) techniques, represented by methods such as PS-InSAR [6, 7], small baseline subset InSAR (SBAS-InSAR) [8], and distributed scatterer InSAR (DS-InSAR) [9], demonstrate significant algorithmic distinctions. In recent years, they have become powerful tools for open-pit mine deformation monitoring, with capabilities including wide area coverage, high precision, and regular temporal sampling. These techniques have been widely adopted in practical applications, marking a significant advancement in the field of mine deformation monitoring. Among various applications, using medium-to-low-resolution Sentinel-1A satellite images in combination with TS-InSAR technology has become one of the most prevalent approaches to monitoring deformation in mining areas. For instance, [PERSON] et al. [10] investigated the Wannian Mine in the Fengfeng mining area using various TS-InSAR techniques, concluding that DS-InSAR provides higher accuracy compared to other techniques. Similarly, [PERSON] et al. [11] utilized both PS-InSAR and DS-InSAR to process Sentinel-1A images covering the PeiBei mining area from 2017 to 2018 and found that DS-InSAR not only proved feasible for mine deformation monitoring but also outperformed PS-InSAR in terms of capability. However, open-pit mining areas are frequently subjected to large-gradient deformations due to intensive extraction activities [12]. These deformation fields often exhibit strong nonlinearity and spatial discontinuity. They are also influenced by high-frequency anthropogenic activities, such as mining truck operations and mechanical vibrations, dynamic changes in surface conditions, including exposure to bare ground, and the movement of waste piles. During active operations, localized, small-scale deformation bodies may also develop within specific mining sections. The C-band Sentinel-1A satellite, despite its advantages, has a limited spatial resolution and a relatively long revisit interval, which restricts its ability to capture large-gradient deformations that exceed the theoretical detection threshold (i.e., deformation between consecutive acquisitions must remain below one-quarter of the radar wavelength). Furthermore, the sparse distribution of coherent scatterers often leads to phase unwrapping errors in localized regions, undermining the satellite's accuracy and reliability in deformation monitoring in geologically complex mining environments. Integrating high-resolution SAR data (e.g., TerraSAR-X, ALOS PALSAR) into InSAR technology has dramatically improved deformation monitoring in mining areas. Notable progress has been achieved in terms of both spatial resolution and accuracy in deformation detection. For example, [PERSON] et al. [13] combined D-InSAR with SqueeSAR to process high-resolution TerraSAR-X data, effectively evaluating the influence of mining-induced deformation intensity and mining boundaries on the surrounding urban infrastructure. In a subsequent study, [PERSON] et al.