无人机低空遥感裂缝识别与采动地表变形指标的相关性研究

Study on the Correlation Between the Identification of Low-altitude Remote Sensing Cracks and the Surface Deformation Index Induced Mining by UAV

山西煤炭资源丰富,随着煤炭资源大规模开采利用诱发了一系列地质灾害,地表裂缝即为地质灾害的主要表现形式之一。目前对地表裂缝监测多采用人工野外调查识别和卫星影像解译识别方法,存在成本高、效率低、分辨率低、易受天气影响等不足。利用飞马D2000无人机对山西省华阳二矿某地质灾害易发区进行了航空摄影测量,得到了测区数字正射影像模型(DOM)、数字表面模型(DSM)和三维点云模型(3DPCM),基于这3种模型数据解译得到地表裂缝发育与分布特征。同时,根据地质采矿条件进行地表移动变形预计,分析了地表变形指标与采动裂缝分布之间的关系。结果表明:利用DOM与3DPCM模型数据可以高效、准确地识别地表裂缝,且裂缝分布情况与采动引起的地表曲率变形、水平变形高度相关。研究结果对于预测评估开采引起的地表裂缝发育情况具有参考意义。

Shanxi is rich in coal resources.With the large-scale exploitation and utilization of coal resources,a series of geological disasters have been induced.Surface cracks are one of the main manifestations of geological disasters.At present,manual field investigation and identification and satellite image interpretation and identification are mostly used for surface crack monitoring,which has the disadvantages of high cost,low efficiency,low resolution and easy to be affected by weather.In this paper,Feima D2000 UAV is used to carry out aerial photogrammetry in a geological disaster prone area of Huayang No.2 Coal Mine in Shanxi Province.The digital orthophoto model(DOM),digital surface model(DSM)and three-dimensional point cloud model(3DPCM)are obtained.Based on the interpretation of these three model data,the development and distribution characteristics of surface cracks are obtained.At the same time,according to the geological and mining conditions,the surface movement and deformation are predicted,and the relationship between the surface deformation index and the distribution of mining cracks is analyzed.The results show that the use of DOM and 3DPCM model data can efficiently and accurately identify surface cracks,and the distribution of cracks is highly correlated with the surface curvature deformation,horizontal deformation caused by mining.The study results have certain reference significance for predicting and evaluating the development of surface cracks caused by mining.