Research on the identification and condition assessment of surface cracks in western mining areas based on drone infrared imaging

Mining-induced ground fissures can lead to significant subsidence, causing serious damage to the ecological environment of mining areas. This study developed a drone and infrared camera system for fissure detection by using image processing techniques. The main conclusions are: collecting infrared images during periods of significant temperature difference yields better monitoring results for mining-induced fissures, particularly from 10:50 a. m. to 2:50 p. m, by calculating convolution, the temperature gradients in infrared images can be effectively delineated, allowing for more accurate identification of fissure locations, and the temperature variations of surface fissures are influenced by specific heat capacity and thermal convection, with the thermal convection between the air inside the fissures and the ambient air.