## 4 Subsidence Results and Comparison  
Employing DInSAR technology, this study utilized two ascending track datasets from the LT-1 and Sentinel-1 satellites to conduct mining-induced subsidence monitoring in the study area. The analysis yielded significant subsidence areas along the radar line of sight (LOS), as illustrated in Figures 3 and 4 for LT-1 and Sentinel-1 data, respectively. The LT-1 dataset provided 40 million measurement points (MPs), triple the 13 million MPs obtained from the Sentinel-1 dataset. This disparity stems from LT-1's higher-resolution post-multi-looking and the C-band Sentinel-1 signals' relatively weaker penetration, which is more susceptible to vegetation obstruction, leading to diminished coherence and concealment of low-coherence areas. We monitored the subsidence of the study area using DInSAR technology and LT-1 ascending data. The results are shown in Figure 3a-d. A total of nine subsidies areas were identified (see Figure 3a). These nine subsidies areas have medium vegetation coverage, and an average subsidence zone greater than 400 m long and 300 m wide. During the monitoring period, they all have obvious subsidence, with the maximum subsidence of \(-\)19.6 mm within 32 days. Three typical subsidence zones located in the lower middle part of the study area are seen in Figure 3a. The subsidence zone shown in Figure 3b is approximately 600 m long and 300 m wide, with maximum subsidence values of \(-\)16.2 mm. The two subsidence zones shown in Figure 3c are approximately 300 m long and 300 m wide and 800 m long and 300 m wide, respectively, with the maximum subsidence value of \(-\)19.6 mm. The subsidence zone shown in Figure 3d is of a relatively smaller dimension (200 m long and 200 m wide) but shows an equally high subsidence value of \(-\)16.8 mm. The subsidence results of DInSAR technology and Sentinel-1 ascending data are shown in Figure 4. Sentinel-1 data identified seven subsidence areas and LT-1 data identified nine subsidence areas. The subsidence areas identified by LT-1 include all areas identified by Sentinel-1. The difference in the identification results is due to the different penetrations of the wavelengths. In the densely vegetated area, LT-1 has stronger penetration to the vegetation, so it acquired dense data points. Figure 3: (a) LT-1 satellite data subsidence monitoring results in the study area; (**b–d**) enlarged views of typical subsidence areas; (**c1,d1**) are typical subsidence areas identified by both LT-1 and Sentinel-1 satellite data. Additionally, as highlighted in Figure 5a-f, LT-1 data identified two additional hazard areas that were not detected by Sentinel-1. These areas are marked with black dashed circles in Figure 5a-c. The analysis shows that the Sentinel-1 data have a higher incidence of unwrapping errors, with a ratio of 75.4%, resulting in a less significant and more diffuse subsidence signal in the hazardous areas. In contrast, the LT-1 data exhibit a lower ratio of unwrapping errors at 25.4%, producing a more concentrated and reliable subsidence signal in these areas. Furthermore, as depicted in Figure 5, the Sentinel-1 data present an unwrapping error ratio of 48.5%, while the LT-1 data show a significantly lower error ratio of 16.5%. This comparison underscores the LT-1 data's superior ability to suppress unwrapping errors, leading to more accurate subsidence detection. To enhance the accuracy of subsidence monitoring analysis, this study selected two typical subsidence areas, c1 and d1 as depicted in Figure 3, as the primary focus. These areas, identified by both LT-1 and Sentinel-1 data, are further examined in Figure 5. Figure 5j-l offers a quantitative analysis of the subsidence in the first area, specifically assessing subsidence along the AA' cross-section. However, due to numerous voids in the data from the second subsidence area, no cross-section analysis was conducted, as highlighted in Figure 5g-i.