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.

采矿诱发地裂缝的识别和处理对矿山安全和生态环境保护具有重要意义。在这项研究中，提出了一种基于无人机（UAV）的红外遥感地裂缝识别和探测的新方法。使用这种方法，上湾煤矿 12401 号长壁面中间正上方的地裂缝包括地裂缝在内的感兴趣区域 (ROI) 在白天和夜间连续监测。还进行了地裂缝特性的直接现场测量，以提供无人机测量的校准数据集。以下午5:00的直接可见光图像为参考，我从晚上9:00至次日凌晨5:00的红外图像中得到的裂隙长度和最大宽度的平均误差，估计分别为 1.8% 和 6.5%。裂隙温度的日变化呈正弦曲线，裂隙内温度变化幅度随着深度的增加而减小。两种常见类型的裂缝之间存在明显差异，具体取决于裂缝是否与含水层或采空区有直接联系。在这项研究中，无人机、红外热像仪和可见光相机数据被成功地用于有效识别采矿引起的地裂缝。此外，验证了裂缝检测误差，并获得了使用该方法的适当时间。我们的结果表明，要识别上述两种类型的裂缝，应在凌晨 3:00 至 5:00 之间进行监测。