The fragile habitat of alpine mining areas can be greatly affected by surface disturbances caused by mining activities, particularly open-pit mining activities, which greatly affect the periglacial environment. SBAS-InSAR technology enables the processing of SAR images to obtain highly accurate surface deformation information. This paper applied SBAS-InSAR technology to obtain three years of surface subsidence information based on the 89-scene Sentinel-1A SLC products, covering a mining area (tailings and active areas) in the Tianshan Mountains and its surroundings from 25th December 2017 to 2nd January 2021. The data were adopted to analyze the characteristics of deformation in the study region and the mining areas, and the subsidence accumulation was compared with field GNSS observation results to verify its accuracy. The results showed that the study area settled significantly, with a maximum settlement rate of −44.80 mm/a and a maximum uplift rate of 28.04 mm/a. The maximum settlement and accumulation of the whole study area over the three-year period were −129.39 mm and 60.49 mm, respectively. The mining area had a settlement value of over 80 mm over the three years. Significantly, the settlement rates of the tailings and active areas were −35 mm/a and −40 mm/a, respectively. Debris accumulation in the eastern portion of the tailings and active areas near the mountain was serious, with accumulation rates of 25 mm/a and 20 mm/a, respectively, and both had accumulation amounts of around 70 mm. For mine tailing pile areas with river flows, the pile locations and environmental restoration should be appropriately adjusted at a later stage. For gravel pile areas, regular cleaning should be carried out, especially around the mining site and at the tunnel entrances and exits, and long-term deformation monitoring of these areas should be carried out to ensure safe operation of the mining site. The SBAS-InSAR measurements were able to yield deformations with high accuracies over a wide area and cost less human and financial resources than the GNSS measurement method. Furthermore, the measurement results were more macroscopic, with great application value for surface subsidence monitoring in alpine areas.

The China–Russia crude oil pipeline (CRCOP) traverses rivers, forests, and mountains over permafrost regions in northeastern China. Water accumulates beside the pipe embankment, which disturbs the hydrothermal balance of permafrost underlying the pipeline. Ground surface flows along the pipeline erode the pipe embankment, which threatens the CRCOP’s operational safety. Additionally, frost heave and thaw settlement can induce differential deformation of the pipes. Therefore, it is necessary to acquire the spatial distribution of water features along the CRCOP, and analyze the various hazard probabilities and their controlling factors. In this paper, information regarding the permafrost type, buried depth of the pipe, soil type, landforms, and vegetation were collected along the CRCOP every 2 km. Ponding and erosive damage caused by surface flows were measured via field investigations and remote sensing images. Two hundred and sixty-four pond sites were extracted from Landsat 8 images, in which the areas of 46.8% of the ponds were larger than 500 m2. Several influential factors related to freeze–thaw hazards and erosive damage were selected and put into a logistic regression model to determine their corresponding risk probabilities. The results reflected the distributions, and forecasted the occurrences, of freeze–thaw hazards and erosive damage. The sections of pipe with the highest risks of freeze–thaw and erosive damage accounted for 2.4% and 6.7%, respectively, of the pipeline. Permafrost type and the position where runoff encounters the pipeline were the dominant influences on the freeze–thaw hazards, while the runoff–pipe position, buried depth of the pipe, and landform types played a dominant role in erosive damage along the CRCOP. Combined with the geographic information system (GIS), field surveys, image interpretation and model calculations are effective methods for assessing the various hazards along the CRCOP in permafrost regions.