96 / 2023-05-26 15:08:00

Combining DInSAR and UAV aerial survey technologies to monitor mining subsidence

mining subsidence monitoring; DInSAR; UAV aerial survey; fusion monitoring; probability integral parameter

With the large-scale and high-intensity mining of coal, it is necessary to effectively monitor and predict the surface subsidence caused by mining. The traditional land subsidence observation technology is time-consuming and labor-intensive, greatly affected by external factors, and it is difficult to carry out large-scale monitoring. DInSAR technology is widely used in the monitoring of small surface deformation areas due to its advantages of all-day, all-weather and high monitoring accuracy. However, due to the limitation of decoherence, it is impossible to achieve accurate monitoring of large gradient subsidence by using this technology alone. UAV aerial survey technology can be used to monitor the large gradient deformation of the surface by obtaining high-precision DEM in different time phases, but the accuracy of monitoring small deformation needs to be improved. How to find a high-precision and high-efficiency mining subsidence monitoring method is an urgent problem to be solved. By combining DInSAR and UAV aerial survey technology, the advantages of the two are complementary to achieve a new method for constructing an efficient, complete and high-precision subsidence basin. The subsidence value of coal mining face in Yangquan Coal Mine was obtained by using DInSAR technology and UAV photogrammetry technology, and the appropriate fusion boundary was selected for the two data sets. The inverse distance weight method can be used to determine the monitoring value of the point in the middle of the fusion boundary, and use the coherence coefficient to verify the fusion results. The correlation coefficient between the fusion data and the leveling data is above 0.90, and the accuracy of the fusion monitoring results is improved compared with the single monitoring method. It is proved that this method can extract the surface subsidence of mining area quickly and accurately, which provides a certain reference value for mining subsidence monitoring. In addition, the parameters of the probability integral method are inverted by using the non-equal precision observation results after fusion, and the parameters under the condition of insufficient mining are obtained. According to the properties of the overburden in the study area, the parameters of the probability integral method are modified to obtain the parameters under the condition of sufficient mining. Compared with the parameters inverted by the measured level data, the parameters inverted by the fusion data are similar to the parameters inverted by the measured data, and the relative error of the sinking coefficient is only 2.5 %. In general, this method can provide some technical support for mining subsidence prediction and geological disaster prevention.