An observatory was established at the Ningtiaota Mine (China) in order to investigate the surface deformation pattern of N00 method workings mining in shallow buried thick coal seams in a windy-sand area. The observatory allows one to measure the coupling between the periodic changes of parameters related to ground subsidence and ground cracks with workings advancement. The data monitored in the field indicate that when the adjacent mining workings are mined below the ground, a sinkhole basin with a larger impact area will be formed. New ground fractures are formed above the mining area to connect with the fractures above the mining face. As a consequence a new pattern of “O” circle distribution beyond the working face is formed, which develops rapidly during the working face recovery. In addition, the dynamic fractures in coal mining are characterized by the phenomenon of self-healing. Our findings will help to protect the surface environment of the mine area during shallow buried high-intensity mining activities in the Lime Tower coal mine, and are also an important guideline in other windy beach mining areas.

Farmland protection and food security is highly focused on in China. However, coal mining has caused negative consequences to cropland in coal–crop overlapped areas (COA), especially in eastern China. Thus, revealing the spatiotemporal impact of coal mining on farmland on a large scale is crucial for coordinating coal mining and grainland protection. In this study, Shandong Province, a representative coal–grain composite area, was selected as a research case to evaluate the damage of mining subsidence on farmland. Firstly, the field investigation and mining subsidence prediction revealed the current situation and trend of farmland damage caused by mining in 2021 and 2030. Then, we evaluated the impact of cropland damage on grain yield. Finally, farmland landscape patterns, ecological environment, and social stability due to mining subsidence were discussed. The results show that: (1) the damaged cropland in 2021 was 6.40 × 10⁴ ha, of which 1.40 × 10⁴ ha was non-yield. By 2030, the accumulative area of damaged cropland is estimated to reach 7.52 × 10⁴ ha. (2) By 2025 and 2030, the farmland yield will be reduced by 16.44 × 10⁴ t and 18.45 × 10⁴ t in overlapped areas of Shandong. (3) The subsidence led to cropland fragmentation, and the terrestrial ecosystem became an aquatic ecosystem, further intensifying the contradiction between more people and less land. This study provides a reference for coordinating coal and grain production and formulating cropland protection strategies in similar regions. Meanwhile, it also provides a scientific basis for the government to formulate land reclamation indicators, technology, management, and acceptance standards and establish and implement the reclamation reward and punishment system.

Coal is the primary energy source in China, while underground mining is the mainstream way of coal mining. By triggering surface movement and deformation, underground mining can cause damage to arable land, buildings, roads, and so on, which is detrimental to the ecological environment in the mining area. In order to assess the severity of damage caused by this to the ground buildings and ecological environment in the mining area, it is necessary to predict mining-induced surface subsidence before the mining activities are carried out. Currently, the most used prediction method is the Probability Integral Method. It is based on probabilistic theory to mathematically demonstrate that the surface downwelling caused by underground extraction conforms to normal distribution. However, there is a lack of validation with measured subsidence basin data. Since the 1960s, China has been paying increased attention to the study of mining subsidence. However, there are still few network stations built across China to monitor subsidence basin. Herein, SPSS software is applied to re-analyze these valuable historical data. By analyzing the observation results and comparing them with the calculation results as obtained by using the probability integral method, it can be found out that the surface subsidence in the center of the subsidence basin conforms to normal distribution, not the subsidence at the edge of the subsidence basin. Therefore, it is inevitable for errors to occur at the edge of the subsidence basin when the normal distribution function is used as the mining influence function to calculate the surface subsidence. This conclusion is expected to provide practical reference for the prediction of surface subsidence in coal mines, and this experience can be extended to the mining of other solid minerals.