Monitoring Extractive Activity-Induced Surface Subsidence in Highland and Alpine Opencast Coal Mining Areas with Multi-Source Data

Abstract

Mining developments in alpine coal mining areas result in slow or rapid ground subsidence, which can lead to melting and collapse of permafrost. This paper integrated unmanned aerial vehicle (UAV) images and satellite-based SAR interferometry images to monitor intensive surface mining subsidence during reclamation. Digital Surface Model (DSM) acquired from UAV images was first used to evaluate the changes of the reclamation scheme on the microtopography carried out by slope and the Digital Elevation Model (DEM) of difference (DoD). The monitoring results showed that the slope had been reduced from over 30 degrees to under 15 degrees after the terrain had been reshaped. The DoD map revealed the distribution of main extraction areas and landfill areas. To further monitor the surface subsidence after local terrain adjustment, the Permanent Scatterer Interferometry (PS-InSAR) method was used to reveal the surface subsidence characteristics of the mine site before and after reclamation. The maximum cumulative subsidence ranged from −772.3 to 1183 mm based on 21 Sentinel-1A images in three years. Within a year of terrain reshaping, uplift and subsidence still occurred at hills and pit side slopes, following the nearly equal subsidence rate. The experimental results showed that the slope reshaping and vegetation recovery had a limited impact on the reduction of the ground subsidence in a short period. Therefore, on this basis, a combination of UAV and PS-InSAR methods can be used to continue monitoring time series subsidence in alpine mines.

1. Introduction

Coal resources provide essential support for regional economic development, but they have also led to ecological and geological disaster problems [1,2]. Mining activities can disrupt the original stress balance of the overlying rock layers, leading to geological hazards such as the destruction of aquifers, landslides, and damage to ground structures, which inevitably lead to ground deformation [3,4]. In opencast mining areas, the excavation process creates huge pits with steep slopes and uneven subsidence, which eventually lead to serious geological hazards [5]. Therefore, it is essential to monitor ecological environment change in mining and reclamation and predict the occurrence of geological disasters.

To create valuable landscapes, restore ecosystems, and minimize the negative environmental impacts of mining, mine reclamation is necessary to carry out during the mining process and after the abandonment of the mine [6,7,8]. The traditional targets of mine reclamation are (1) backfilling and soil reconstruction to create suitable landforms using machines and geological materials and (2) establishing vegetation on created landforms to help in slope stabilization, erosion control, and improvement of soil condition [9]. Some coal reclamation areas in China are located in high plateau alpine regions, such as on the Qinghai–Tibet Plateau. With a degradation trend of perennial permafrost thinning and some perennial permafrost becoming seasonal permafrost, the unique and fragile alpine ecosystem in the Qinghai–Tibet Plateau has a remarkable response to any natural and artificial disturbances [10]. Therefore, monitoring the effect of mine reclamation on high plateau alpine regions has especially ecological importance. Different mining methods in other areas can lead to varying consequences of mining, such as falling water levels, surface subsidence, surface cracks, destruction of vegetation, soil erosion, and other problems [11]. The study area of this paper, the Muli mine, is in an alpine region where the consequences of mining are mainly increased surface fragmentation and deformation. Therefore, this paper will use multi-source datasets to monitor the changes of slope and surface subsidence and explore the relationship between them in the study area.

The continuous innovation and development of spatial information technologies such as the Global Navigation Satellite System (GNSS) and interferometric synthetic aperture radar (InSAR) technologies have created opportunities to address mine reclamation monitoring activities in alpine regions. These on-site GNSS techniques can monitor ground deformation with high accuracy; however, this method can only monitor localized deformation and is often labor intensive [3]. For alpine regions, continuous GNSS field observations are even more challenging. As an active remote sensing technique, spaceborne InSAR has become one of the most useful geodetic techniques for ground deformation monitoring [12,13]. Therefore, using InSAR technology for slope deformation monitoring in opencast coal mines is an essential application in previous studies. Caro explored the relationship between surface deformation and subsurface water levels to provide rough correlation estimates and map the mine water dynamics [14]. Samsonov presented a novel methodology for the integration of ascending and descending InSAR data sets for the computation of two-dimensional time series of ground deformation [4]. Ng assessed land subsidence in the Gippsland Basin and found that several rapidly deforming areas have been identified at the mining sites and the surrounding regions [15]. Gong analyzed the deformation and soil erosion of coal mine dump in China [16]. Fan used the Temporarily Coherent Point (TCP) Insar method and TerraSAR-X images to monitor land subsidence in the mining region of western China [17]. Zhang detected mining-induced ground deformation and associated hazards [18]. Xia integrated D-InSAR and GIS to identify illegal underground mining [19].

In addition to the above using conventional Sentinel-1 data, Envisat data, etc., some applications incorporate other data such as Unmanned Aerial Vehicle (UAV) data, GNSS, Light detection and ranging (Lidar), etc. for joint mine subsidence analysis. Gong used a UAV to assist in phase unwrapping and removal of the topographic component [16]. Khan used LiDAR, InSAR, and the Global Position System (GPS) to monitor ground subsidence [20].

After the mines were abandoned and the pumping stopped, the groundwater flowed back to hydrostatic equilibrium, and the land began to rise [14]. Four years later, with the closure of the last mine, the first indications of uplift were observed [14]. Samsonov determined that deformation rate changes are mainly caused by water level variations in the mines [4].

However, in the past, differential InSAR (D-InSAR)-based deformation monitoring of mine sites has mainly focused on underground mining [21], while ignoring the instability and severe stockpile erosion problems generated by opencast mining [22,23].

Although many studies used InSAR methods for subsidence analysis, the monitoring and protection of slopes in opencast coal mines in high-altitude zones are still in a blind spot, and most of the drainage field landforms are stacked at natural resting angles. Artificial gradients in alpine zones are affected by permafrost factors, and deformation varies at different slope angles, slope heights, freeze–thaw cycle zone thicknesses, and different thaw cycles. We selected the opencast coal mine in Muli, Qinghai Province as the study area. The UAV images were used to generate DSMs to acquire micro-geomorphic changes. Additionally, this paper used Sentinel 1A data to track the settlement process during reclamation, especially the settlement changes in landfill pits and slag hills.

This paper is structured as follows. In Section 2, the locational conditions and climate of the study area are presented, as well as the main data sets used. The methodology for microtopography detecting and surface subsidence monitoring is described in Section 3. The results of microtopography changes and ground subsidence in the study area are shown in Section 4. In Section 5, the causes of subsidence and relationships between slope reshaping and subsidence are discussed.

2. Study Area and Data

2.1. Study Area

The Muli mining area is located in the central Qilian Mountains at a high altitude of 3800 to 4200 m, dominated by the plateau ice edge landform type. It is a typical highland alpine anoxic zone with a typical plateau continental climate. The natural conditions in the mining area are very harsh, and the soil type is mainly alpine meadow soil and swampy meadow soil. The soil layer is 10 to 50 cm thick, covered by permafrost for many years, and swamps, wetlands, and alpine meadows are developed (Figure 1). The rivers in the area include the Shangdoshe River, the Xiadoshe River, the Jiangcangqu River, and its tributaries, all of which belong to the Datong River system. The rivers are recharged by snowmelt, springs, and atmospheric precipitation, and there are seasonal drains on both sides of the pits. The hydrogeological conditions are simple, and the surface water dynamics vary significantly with seasonality. The ecological environment in the area is fragile, easily damaged, and difficult to restore.

Mining at the Muli mine began in 2006 and caused severe ecological problems in the following decade due to private mining. The mining caused landscape damage, vegetation damage, land destruction, permafrost damage, land sanding, and slope instability (landslides, crumbling), shown in Figure 2a. In 2016, the local government began ecological management and restoration through the remediation of the slag hill and planting of grass in the mining area. In 2020, the Muli mine stopped mining and began ecological governance, showed in Figure 2b. It is planned that by December 2023, a highland alpine mining ecological park will be completed, and a long-term mechanism for the park’s operation and maintenance will be formed.

2.2. Data

The Sentinel-1A satellite is a C-band (5.6 cm) synthetic aperture radar launched by the Copernicus programme of the European Space Agency (ESA) on 3 April 2014, with a spatial resolution of 5 m × 20 m, a revisit period of 12 days, and a new TOPS (Terrain Observation by Progressive Scans) scanning mode, with an amplitude of 250 km.

In order to compare the slope deformation results at the Muli mine after reclamation, this study collected 22 views of Sentinel-1A uplift data, with data coverage dates from August 2018 to December 2020, and 18 views of Sentinel-1A downlift data, with data coverage dates from January 2021 to August 2021 (

Table 1. Datasets used in this study.

Sensors	Sentinel-1A	Sentinel-1A	UAV	UAV
Period	August 2018–December 2020	January 2021–August 2021	August 2020	December 2020
No. of image	22	18	192	150

).

Meanwhile, tilt photography was carried out to survey the Muli mine by a UAV during two flights in August 2020 and December 2020 after the landfill (Table 1). The UAV-collected photographs were used to obtain orthophotographs and DSMs using the standard Structure from Motion (SfM) workflow [24]. The high-precision DSM provided quantified values for changes in micro-landscapes and the characteristics of deformation at different slopes in a three-dimensional environment.

3. Methods

3.1. Quantification of Slope Change and DEM of Difference

To quantity the landform changes at the slag hill and pits (Figure 1), we have acquired hundreds of images of the Muli mine using UAV tilt photography in August 2020. After completing the reshaping of the terrain in December 2020, we also took images of Pit 4 using a UAV tilt approach. Using these images, DEMs with 5 and 7.5 cm ground resolutions were generated by the SfM method. Using these DEMs, the slope could be easily calculated in ArcGIS to identify changes of side slopes and assess the effect of artificially created topography.

Then, both DEMs, the original post-excavation slag hill and side slopes, and the one representing a reclamation situation, were used to produce a DEM of Difference (DoD). The DoD method was used to measure earthquake deformation [25], quantify flood deposits [26], and analyze changes in the morphology of a proglacial valley [27]. The DoD approach is to subtract an old DEM from the new DEM, taking into account the uncertainty of the DEMs, which included measurement errors, sampling bias, and uncertainties due to interpolation methods, among others [28]. This technique involves subtracting georeferenced DEMs from different periods to produce a morphologically (i.e., height) variable raster (Equation (1)):

DoD = DEM_t2 − DEM_t1

(1)

where t1 is the initial time, and t2 is the consecutive time of DEM acquisition. Positive and negative values in the DoDs indicate deposition and erosion, respectively [29].

In this study, there were no prominent houses or tall vegetation in the study area, so the DSM obtained from the UAV can be considered a DEM and used for the DoD method. The DSMs both had the fine ground resolutions of 5 and 7.5 cm, respectively, resulting in a massive volume of data. As such high accuracy is not required for analyses such as slope gradient, the resolution of the two DSMs was resampled to 0.3 m in this paper. Therefore, only the co-registration error of the DSMs was considered, and a probabilistic thresholding method was used, with a confidence interval of 95% in this paper when using the DoD method for micro-geomorphological analysis. We calculated the micro-geomorphic changes using the Geomorphic Change Detection 7 (GCD 7) toolbar embedded in ArcGIS 10.7 (http://gcd.riverscapes.xyz/Download/ (accessed on 12 February 2022). We only analyzed the DoD of the restored portion of Pit 4. The slag hill to the north of Pit 4 was unchanged, so the DoD did not treat that portion, only the intersected portion of the DSM for both periods. In addition, the DoD was masked by two large water-filled holes in the mine.

3.2. Permanent Scatterer Interferometry (PS-InSAR)

PS-InSAR was developed from the D-InSAR technique to analyze only highly coherent point targets with solid and stable scattering characteristics in the time series [30]. These point targets have a high coherence even in interferometric pairs with long spatial and temporal baselines and can therefore be analyzed for their phase in the time series.

By estimating the delayed phase of the atmosphere in the monitoring area, PS-InSAR could accurately estimate the linear deformation rate and elevation error of the coherent target. By recovering the nonlinear deformation phase at the monitoring site, an accurate deformation history of the target at the monitoring site could be obtained.

The interference phase in a differential interferogram can be expressed by the following Equation (2):

$${\phi }_{int\_i}=\frac{4\pi }{\lambda ·R·\sin \theta }·B_i^{\perp }·{\epsilon }_i+\frac{4\pi }{\lambda }·T_i·v_i+{\phi }_i^{res}$$

(2)

where ${\phi }_{int\_i}$ denotes the differential interference phase of the $i$th interference pair, and $B_i^{\perp }$ is the spatial vertical baseline of the interference pair. $T_i$ denotes the time baseline for interference pairs. $\lambda ,R,\theta$ are the wavelength, the distance from the sensor to the monitoring point, and the corresponding angle of incidence, respectively. ${\epsilon }_i$ is the residual phase of the elevation due to the inaccuracy of the topographic data used. $v_i$ is the linear deformation rate of the monitoring point in the direction of the satellite line of sight. ${\phi }_i^{res}$ contains the nonlinear deformation phase, the atmospheric delay phase difference between the two SAR images generating the interferogram at the time of capture, and the random noise component.

To obtain the signals of each component, the differential interference phases of adjacent highly coherent target points can be differenced again as follows below (Equation (3)):

$$\Delta {\phi }_{int\_i}=\frac{4\pi }{\lambda ·\overline{R}·\sin \overline{\theta }}·{\overline{B}}_i^{\perp }·\Delta {\epsilon }_i+\frac{4\pi }{\lambda }·T_i·\Delta v_i+\Delta {\phi }_i^{res}$$

(3)

where ${\overline{B}}_i^{\perp }$, $\overline{R}$, $\overline{\theta }$ are the distance between the sensor and the image element, and the angle of incidence of the two highly coherent target points. respectively. $\Delta {\epsilon }_i$ denotes the incremental elevation error. $\Delta v_i$ is the linear deformation rate increment and $\Delta {\phi }_i^{res}$ is the residual phase difference between two highly coherent target points.

Due to the high spatial autocorrelation of atmospheric and surface deformation, the phase differences associated with atmospheric delay and nonlinear settling at adjacent highly coherent target points can be considered as small values, and the highly coherent target points themselves are less affected by noise, so it can be assumed that $\left|\Delta {\phi }_i^{res}\right|\le \pi$. Under this condition, it becomes possible to estimate $\Delta {\epsilon }_i$ and $\Delta v_i$ from M differential interferograms. It is transformed into a problem of solving the maximum of the following objective function (Equation (4)):

$$\gamma =|\frac{1}{M}{\displaystyle \sum }_{i=1}^M\left(\cos \Delta {\omega }_i+j·\sin \Delta {\omega }_i\right)|$$

(4)

where $\gamma$ is temporal coherence, $j=\sqrt{-1}$, and $\Delta {\omega }_i$ denotes the difference between the observed and fitted values as follows in Equation (5):

$$\Delta {\omega }_i=\Delta {\phi }_i-\frac{4\pi }{\lambda ·\overline{R}·\sin \overline{\theta }}·{\overline{B}}_i^{\perp }·\Delta {\epsilon }_i-\frac{4\pi }{\lambda }·T_i·\Delta v_i$$

(5)

The maximum temporal coherence $\gamma$ is obtained by using the two-dimensional periodogram method or the spatial search method, and then the optimal solutions of $\Delta {\epsilon }_i$ and $\Delta v_i$ are solved to determine the linear deformation rate and elevation error of the highly coherent target points using the least-squares parity method based on the PS network established by the irregular triangular network. The atmospheric phase components are then separated from the nonlinear phases using a filtering method based on their high frequency in time and low frequency in space, while the nonlinear deformation phases are of low frequency in time and space domains, and the linear and nonlinear deformation of the monitored objects are finally obtained.

In this paper, the PS-InSAR technique was used to extract deformation information from Sentinel 1A data by SARProZ software. Based on the PS-InSAR principle described above, we selected cloud-free as the master image, and the other slave images were individually aligned with the master image and interfered with the master image by Equation (3). Then, the differential interferogram was obtained by removing the flat earth phase from the baseline parameters and the topographic undulation phase from the external SRTM DEM. Surface settlement information was obtained by solving the model parameters by building a phase-difference model of adjacent PS points.

4. Results

4.1. Micro-Terrain Changes

The DSM of Pit 4 conducted from the UAV images in August and December 2020 are shown in Figure 3a, which revealed the microtopography of Pit 4 after a long-time excavation. As shown in Figure 3a, the deepest excavation depth in Pit 4 went up to 150 m, and the slag hill piled up around it could reach up to 100 m. Due to the influx of groundwater, Pit 4 was filled with the influx and appeared as a flat surface in the DSM. The deep excavation and waste dumping also created steep slopes around the pit and slag hill. After a terrain reshaping for three months, the southern edge of Pit 4 was leveled to improve the original fragmented landscape. At the same time, the eastern portion of Pit 4 was filled in, raising the ground level in this site.

A north–south (marked in a blue line) and east–west (marked in a red line) profile was made along the pit and slag hill of Pit 4 (Figure 3a). It can be seen from the profile in Figure 3b that the pit along the east–west direction was maintained at the same height, and only the middle site had been leveled. Conversely, the profile lines along the north–south direction showed that elevation reductions were made at the edge of the slag hill.

Due to waste dumping and natural accumulation, a steep slope had developed on the south slag hill of Pit 4, generally between 15 and 30 degrees (Figure 4a). Similarly, excavation activities on the eastern side of Pit 4 created two smaller pits with a steeper slope ranging from 30 to 45 degrees (Figure 4a).

After carrying out mine rehabilitation, the southern side of Pit 4 was leveled to a flat area with smaller gradients and fragmentation. On the east side, the slag hill was partially leveled, and the leveled portion was used to fill two small pits. At the same time, the formerly steep slope was adjusted to 0–30 degrees, effectively ensuring the safety of the reclaimed slope (Figure 4b).

The results in Figure 3 and Figure 4 show that the topographic leveling at the Muli Mine had resulted in a significant reduction in topographic fragmentation and an increase in the overall integrity of the study area.

4.2. Dod Results

Following the ecological reclamation works, geomorphological changes occurred mainly on the slopes and the slag hill. The DoD map in Figure 5a shows the distribution of excavation areas and landfill areas, which corresponded to the location of slope reshaping. Figure 5b,c presents the area and volumetric elevation change distribution (ECD) of DoDs. The histograms can be considered an effective discrimination of the balance between cutting and filling during the reclamation process. The ECD of DoDs in Figure 5c showed roughly equal total excavation and landfill, which is very useful for balancing the earthwork volume in reclamation projects.

4.3. Deformation before and after Landfill

Figure 6a shows the deformation results from August 2017.8 to August 2020 (before stopping mining). In three years, the mining area showed a sinking and lifting trend; cumulative change over three years ranged from −1655.2 to 1403.9 mm (illustrated in Figure 6b,c). The maximum cumulative lifting was 1183 mm in three years (Figure 6b), and the maximum cumulative surface subsidence was −772.3 mm in three years (Figure 6c). On the other hand, the alpine permafrost zone around the mine site showed a trend of stability and seasonal variation shown in Figure 6d. Different pits and slag hills showed various features. Based on the interpolation result of the pit and slag hill, the annual cumulative deformation map was selected to indicate the difference between the pits and slag hills.

In August 2020, the Chinese government discovered that the Muli coal mine was still being developed. At the end of the same year, remediation of the coal mines began. Due to the different slope and hydrological conditions of the various pits at the Muli mine, different remediation methods were adopted for the mines. The trend of subsidence and uplift shown in Figure 7a was consistent with Figure 6a. Meanwhile, two typical areas also kept the same trend shown in Figure 7b,c. The maximum velocity in typical area A was 435.9 mm/year. The maximum sinking velocity in typical area B was −250.1 mm/year.

The slope-shaping and filling of Pit 4 resulted in uneven localized subsidence but maintained the same variation in the overall trend. The largest subsidence still occurred on the southern slag hill and eastern side of Pit 4. The same varying degree of uplift occurred on the slag hill to the north of Pit 4.

5. Discussion

5.1. Analysis of Slope Change

The reclamation of the mining ecosystem is usually divided into five stages: geomorphological reshaping, soil reconstruction, vegetation reconstruction, landscape reconstruction, biodiversity reorganization, and protection. As the Muli mine is in an alpine mountainous area with special permafrost and cold temperatures, a different approach to reclamation should be adopted. The reshaping of the landscape needs to consider the original topography of the mine, with the aim of reshaping a new landscape that is in harmony with the surrounding landscape while minimizing the occurrence of geological hazards.

The Muli mine had eleven pits varied in terms of pit size, slope stability and hydrogeological conditions, as well as the degree of connection to the surrounding water system. Therefore, the current mining status and hydrogeological conditions of each pit should be considered when ecological restoration is undertaken. For Pit 4, the most appropriate method of ecological restoration is the retention of the plateau lake formed by the water, the reshaping of the slope and slag hill, and the revegetation [10].

The northern and southern slopes of Pit 4 and the slag hill to the east of Pit 4 are occupied mainly by slopes between 15 and 30 degrees. According to the evaluation index of coal mine reclamation, the slope of the pit should be arranged below 15 degrees to prevent the occurrence of geological hazards such as erosion and landslides [11]. In the Muli mine, the side slopes of the pits have been covered by permafrost due to the long exploitation and the cold weather. Therefore, it would not be appropriate to reshape the entire steep slope of Pit 4. Figure 4 shows the change post-reclamation of Pit 4. The side slopes of Pit 4 remained unchanged at their original slope angle, while the slag hill to the east had undergone more substantial slope shaping, with most of the slope changing from 30 to 45 degrees to less than 30 degrees. The slope of the south slag hill was under 15 degrees before reclamation, which is a relatively safe angle according to reclamation evaluation criteria. However, as the southern slope had been subject to a landslide, the area was also modified to create a level slope to reduce the impact of surface settlement.

Most ecological restoration projects have focused on the impact of slope preparation on geological hazards. It is also important to consider the scale of the project and the calculation of earthwork volumes during project implementation. The results of DoD in Figure 5 showed that two sites on the south and east had distinct changes for excavation and landfill. The east side of Pit 4 was predominantly filled in during slope preparation, and its fill area was greater than the south side of Pit 4. The east side of the landfill area was occupied by 3 m of elevation. The volume change was dominated by infilling, which occurred on the east side of the pit, with the main infill heights ranging from 5 to 25 m. The volumetric histogram showed a certain symmetry, with approximately equal volumes of landfill and excavation. This is related to the policy of one pit one reclamation plan used for the reclamation of the Muli mine, as mentioned in the literature [10]. For Pit 4, instead of traditional refilling, the excavated pit was retained and became a highland lake. Therefore, the reclamation of Pit 4 had focused on the slopes on the south side of the pit and the slag hill on the east side. As a cooperative restoration project, the soil from the shaped southern side slope was used to fill in and reshape the steep slope of slag hill on the eastern side. Therefore, the total volume of excavation and landfill was essentially equal when Pit 4 was taken as a whole restoration project.

Based on the above analysis and application of the DoD maps, we can affirm that the DoD method is a robust method for detecting geomorphological changes in opencast mining and monitoring the entire mining production process when remotely sensed multi-temporal data (e.g., drone surveys) are available.

5.2. Analysis of Subsidence

The stability of the Tibetan plateau is an extremely significant factor in the safety and success of restoration work. Therefore, it is essential to monitor surface deformation to ensure that ecological restoration is carried out smoothly and effectively. The Muli mine site exhibited the non-uniform settlement characteristics inherent to opencast coal mines before reclamation in August 2020. Most of the settlement occurred on the side slopes of the pit, with a small amount of uplift occurring around the piled slag hill (Figure 6). The most significant subsidence occurred on the southern slope of Pit 4, with annual subsidence reaching 320 mm/year. The geological map of the site shows that the site is in a geologically stable area (http://www.ngac.org.cn/Map/ (accessed on 15 February 2022)), with bedrock in the pits and relatively good stability, with few unstable slopes developed. Further exploration of the site revealed that the subsidence resulting in landslides was associated with a subsurface paleochannel [10].

During the three-month restoration project area, the south slope of Pit 4 was treated according to the deformation results before reclamation. To ensure the stability of the landslide hill, the central portion of the back edge of the south landslide hill was cut to reduce the load. A large gentle slope along the north–south side slope was created by lowering the elevation of landslide areas from 4040 to 4010 m to stabilize the side slope by reducing true real-time deformation and displacement.

After completing three months of slope shaping and other remediation work, the PS-InSAR settlement monitoring results for the mine site remained consistent with the pre-reclamation period, with the same slope settlement and uplift of the slag hill. A significant amount of noise in the post-reclamation settlement monitoring results was likely due to other restoration work such as vegetation planting and localized remodeling. A small amount of reclamation work occurs during the PS-InSAR treatment, making the treatment with the PS-InSAR method incoherent and potentially leaving fewer coherent points.

6. Conclusions

In this paper, the different data sources were used to monitor surface coal mines in alpine regions before and after reclamation. Taking one of the pits, Pit 4, as an example, this paper completed the monitoring of DSMs changes and slope changes using UAV tilt photography. At the same time, the surface subsidence of the mining area was monitored by the PS-InSAR method. At last, this paper analyzed the possible causes of the subsidence and the influence of terrain reshaping on the subsidence.

The results of monitoring the reclamation of opencast mines in alpine areas showed that, due to special permafrost, different reclamation methods should be adopted for various pits depending on the pit depth, surrounding water sources, and other different pit conditions. For example, Pit 4, due to the pit’s depth, was not suitable for adoption of the slag hill filling method for reclamation; otherwise, it would lead to a considerable engineering workload and affect the destruction of the surrounding permafrost and further deterioration of the ecological environment. Meanwhile, the DoD method extends the initial application of watershed erosion and deposition to the calculation of the balance between excavation and slag hills’ reshaping when reclaiming coal mines. Integrated different data sources to monitor subsidence is a practical approach to the reclamation of mines in alpine regions. Attention should also be paid to the effects of permafrost thawing in alpine areas, etc., on the monitoring effects and reclamation effectiveness to provide strong support for more alpine mine reclamation monitoring in the future.