Identification of mining induced ground fissures using UAV and infrared thermal imager: Temperature variation and fissure evolution

The identification and treatment of mining-induced ground fissures are of great significance to mine safety and ecological and environmental protection. In this study, a novel method for ground fissure identification and exploration by infrared remote sensing onboard an unmanned aerial vehicle (UAV) was proposed. Using this method, a region of interest (ROI) that includes ground fissures directly above the middle of a long wall face, No. 12401 in the Shangwan coal mine, was monitored continuously during the day and night. Direct field measurements of ground fissure properties were also conducted to provide a calibration dataset for UAV measurements. Using the direct visible image at 5:00 pm as a reference, the average errors of the length and maximum width of Fissure I obtained from infrared images from 9:00 pm to 5:00 am on the next day, were estimated to be 1.8% and 6.5%, respectively. The diurnal variation of the fissure temperature is sinusoidal, and the range of temperature variation in the fissure decreases with the increase in depth. There is an apparent difference between the two common types of fissures depending on whether the fissure has a direct connection to an aquifer or a goaf. In this study, UAV, infrared thermal imager, and visible light camera data were successfully employed to effectively identify mining-induced ground fissures. In addition, the fissure detection error was validated, and the appropriate time for utilizing this method was obtained. Our results show that to identify the two aforementioned types of fissures, monitoring should be conducted between 3:00 am and 5:00 am. This study lays a foundation for the study and application of UAV and infrared thermal imagers for the identification of ground fissures induced by underground mining in large areas.