## 4 Result  
### InSAR Identification Results  
This study employed the SBAS-InSAR technique to conduct a temporal interferometric analysis of Sentinel-1 radar imagery collected over central Tianshui City from 2022 to 2023. The annual average ground deformation rates were extracted, with the ascending track deformation rates ranging from \(-93.68\) mm/a to \(88.12\) mm/a and the descending track deformation rates ranging from \(-48.66\) mm/a to \(41.19\) mm/a. Due to insufficient data density for high-precision temporal InSAR analysis, as only 35 ascending track images were acquired over the two-year period, the study primarily analyzed 21 ascending track images from 2023 to ensure the stability and reliability of the deformation-monitoring results. To enhance the accuracy of the identification outcomes, ascending and descending track deformation results were cross-validated [34; 35; 36]. Additionally, areas with uncertain interpretation results underwent auxiliary verification using the Google Earth platform, thus improving the overall accuracy and credibility of the interpretations.  
The InSAR monitoring results indicate that significant deformation zones are concentrated in the northern mountainous areas of Maiji District, where a major landslide event occurred on 25 July 2013, marking it as a region prone to geological hazards in Tianshui City [20; 25]. Existing geological studies reveal that major fault lines traverse near this region, with evident spatial coupling between fault activities and landslide occurrences. Consequently, this area, characterized by complex geological structures and significant landslide hazards, was identified as a priority zone for landslide risk assessments.  
For deformation identification, temporal differential interferometric analysis was applied to obtain InSAR deformation rates from both the ascending and descending tracks. These deformation results were comprehensively analyzed alongside sub-meter resolution JL1 optical remote-sensing imagery and DEM data, examining the morphological characteristics and spatial distributions of deformation zones. The ascending track analysis identified 115 landslide-related interpretation points, while the descending track analysis identified 67 points, with 13 overlapping points identified by both tracks, totaling 169 potential landslides and landslide hazard regions. These interpretation points primarily encompass potential landslide hazard points, historical landslide sites, slope deformation areas, and slopes influenced by engineering activities. The results demonstrate uneven spatial distributions, predominantly located along riverbanks and near road embankments, potentially threatening critical infrastructure such as waterways, roads, buildings, and reservoirs, thereby providing essential data for subsequent field verification and disaster prevention efforts.  
Given the absence of in situ monitoring stations in the study area for validation purposes, reliability assessments of InSAR identification were conducted via comparative analyses of ascending and descending track deformation results [1]. The findings confirm high conformity between identified engineering activity points in the third enlarged area of the ascending track imagery and actual project boundaries, validating interpretation accuracy. Furthermore, the second enlarged area in the descending track imagery, located in the overlap zone between two SAR image frames (frames: 473 and 479), demonstrated good consistency in deformation intensity and boundary delineations through cross-validation. These analyses collectively indicate that the InSAR ground deformation monitoring in this study achieved high accuracy, providing robust technical support for subsequent comprehensive landslide hazard identification research (Figures 6 and 7).