Abstract: In the monitoring of ecological environment in mines, traditional monitoring methods are constrained by factors such as complex terrain and harsh environment, which makes it difficult to obtain comprehensive data and timely detect potential ecological threats. Therefore, this study designs a real-time feedback mining ecological environment monitoring system based on unmanned aerial vehicle remote sensing images. The system adopts a hierarchical architecture, divided into four levels. In the drone route planning unit, the fish eagle algorithm is used to simulate the hunting behavior of fish eagles. Based on the terrain, meteorological data, and task objectives of the monitoring area, the optimal flight path is automatically generated to achieve reasonable route planning in complex environments, improve data collection efficiency, and reduce drone energy consumption. The real-time feedback unit for drone images constructs a coordinate system, sets up ground control points, and combines LoRa self-organizing network technology for data transmission to achieve fast and accurate transmission of remote sensing images, ensuring stable data transmission in complex terrains. Improve the remote sensing ecological index calculation unit, introduce soil erosion indicators based on the ecological characteristics of mines, and normalize and perform principal component analysis on multiple indicators to comprehensively reflect the quality of the mining ecological environment. The unit for analyzing the spatiotemporal differentiation characteristics of ecological environment quality uses Sen slope estimation and Mann Kendall test to analyze the temporal evolution characteristics, and quantifies the spatial variation characteristics with coefficient of variation. The results indicate that under the application of the system, the decrease in remote sensing ecological index indicates an overall deterioration in the quality of the mining ecological environment. In the face of different wind conditions, the spatial coverage meets the requirements of data collection integrity and has higher processing capacity, providing strong support for monitoring and governance of the mining ecological environment.