## 1 Introduction
The intensive study of landslides has achieved many useful outcomes, but there are still some problems with the application of GNSS monitoring systems for use on high-steep slopes in coal mining subsidence areas, and there has been insufficient research on the specific influences of high-steep slopes in mines, the surrounding topography, rainfall, and other associated parameters. GNSS is used to monitor the crustal deformation of the post-earthquake, such as a detailed crustal deformation model using three-component GNSS data in 2000-2010 was construct for the 2016 Kumamoto earthquakes in central Kyushu, Japan [19], and also used for other seismic analyses, such as the Izmit earthquake [20] in the north-west of Turkey on 17 August 1999, Wenchuan earthquake [21] on 12 May 2008 and Jiuzhaigou earthquake [22] on 8 August 2017 in Sichuan province, China. GNSS monitoring results of crustal deformation are often applied to earthquake prediction, for example, 31 GNSS stations from the Crustal Movement Observation Network of China (CMONOC) were used to study regional crustal deformation characteristics in Xinjiang, China [23]. Block modeling of crustal deformation in Tierra del Fuego from GNSS velocities of 41 sites was established [24]. A regional GNSS network consisting of 202 permanent GNSS stations established to study the recent crustal strain deformation in the Ukrainian territory [25]. A right-lateral shear zone in the San-in region, southwest Japan, has been proposed by previous geological and seismological studies, and was proved using GNSS velocity data [26]. Crustal deformation across the Southern Patagonian Icefield was observed by 43 GNSS sites [27]. Small crustal deformation caused by slow slip events in southwest Japan was detected using GNSS and tremor data [28]. GNSS also is applied in frost heave deformation [29; 30], volcanic deformation [31; 32], mining subsidence [33], bridge deformation [34; 35], and dam deformation [36; 37], and so on. The advantages of GNSS monitoring are (a) allow sampling at any time interval, (b) remote and severe weather data collection can be achieved, (c) avoid human errors caused by manual readings and records, (d) 24 h a day for continuous monitoring. The disadvantages are single point data, and the high cost to form lines or networks. In the long wall coal mining method, the mining area is divided along the working direction into several strip-shaped sections. Along the coal seam at the lower elevation level there is a roadway for coal transport, while in the upper elevation level there is a return air roadway. The first cut of the coal mining face is arranged between two sections of the roadway, along the dip direction of the coal seam. Coal mining advances along the direction of the coal seam. After underground coal mining, the rock formation around the mining space loses its support and gradually moves, bends, and deforms into the goat. This process gradually extends from the slope outwards and upward to the surface as the mining face continues to push forward, causing the surface to sink, and forming a subsidence basin. The movement of the overlying rocks and surface deformation is inevitable as new equilibrium conditions for mine failure are formed due to changes in the original stress state of the rocks. In this study, a GNSS real-time monitoring system was used for the first time to assess the dynamic deformation of the overlying rock mass and the high-steep slope in long wall mining. The dynamic changes of the overlying rock layer and slope body were determined based on the moving velocity and material displacement at the monitoring point. The study demonstrated the applicability of a GNSS real-time monitoring and warning system in a high-steep slope, and proposed a new way to assess the evolution of dynamic deformation and stability of a high-steep slope under mining conditions.