Abstract: As an important coal production base in China, the long-term exploitation of mineral resources in the Northern Shaanxi Coal Mining Area has given rise to a series of ecological and environmental problems, including surface subsidence, vegetation degradation, and water resource damage. To achieve precise management, control, and restoration of the mining area's ecological environment, and in response to the issues that existing technologies are insufficient to meet the requirements for dynamic and precise monitoring, a comprehensive monitoring system framework integrating the "Air-Space-Ground" integrated monitoring technology is proposed. This system combines multiple technical means such as satellite remote sensing, UAV remote sensing, ground sensor networks, and manual field surveys, covering five major monitoring themes: geological hazards, vegetation ecology, water environment, atmospheric environment, and soil environment. By designing a multi-level monitoring index system, the monitoring content, technical methods, and early warning thresholds are clearly defined. Finally, an application practice was conducted in a production coal mine within the Northern Shaanxi Coal Mining Area. The results show that during the period from January to December 2024:the surface deformation in the mining area reached the millimeter level (the cumulative deformation of Areas A-D ranged from -45.49 mm to -23.60 mm); land damage was mainly characterized by subsidence (1 254.70 hm²) and occupation (12.33 hm²); vegetation coverage was dominated by medium coverage (20.36%) and medium-high + high coverage (33.49%); groundwater was classified as Class V water; soil heavy metals generally met the risk control standards for soil pollution in agricultural land. A mine ecological environment monitoring system was developed based on the monitoring data, realizing the closed-loop management of "perception-analysis-early warning-decision-making". The research indicates that this system can achieve dynamic, real-time, and quantitative monitoring of the ecological environment in large-scale mining areas, providing effective data support and a decision-making basis for the ecological environment supervision of mining areas.