Wei Lianhuan, Feng Qiuyue, Liu Feiyue, Mao Yachun, Liu Shanjun, Yang Tianhong, Tolomei Cristiano, Bignami Christian, Wu Lixin
Institute for Geo-Informatics and Digital Mine Research, School of Resources and Civil Engineering, Northeastern University, Shenyang 110819, China.
Center for Rock Instability and Seismicity Research, School of Resources and Civil Engineering, Northeastern University, Shenyang 110819, China.
Sensors (Basel). 2020 Nov 21;20(22):6674. doi: 10.3390/s20226674.
Due to the intrinsic side-looking geometry of synthetic aperture radar (SAR), time series interferometric SAR is only able to monitor displacements in line-of-sight (LOS) direction, which limits the accuracy of displacement measurement in landslide monitoring. This is because the LOS displacement is only a three dimensional projection of real displacement of a certain ground object. Targeting at this problem, a precise digital elevation model (DEM) assisted slope displacement retrieval method is proposed and applied to a case study over the high and steep slope of the Dagushan open pit mine. In the case study, the precise DEM generated by laser scanning is first used to minimize topographic residuals in small baseline subsets analysis. Then, the LOS displacements are converted to slope direction with assistance of the precise DEM. By comparing with ground measurements, relative root mean square errors (RMSE) of the estimated slope displacements reach approximately 12-13% for the ascending orbit, and 5.4-9.2% for the descending orbit in our study area. In order to validate the experimental results, comparison with microseism monitoring results is also conducted. Moreover, both results have found that the largest slope displacements occur on the slope part, with elevations varying from -138 m to -210 m, which corresponds to the landslide area. Moreover, there is a certain correlation with precipitation, as revealed by the displacement time series. The outcome of this article shows that rock mass structure, lithology, and precipitation are main factors affecting the stability of high and steep mining slopes.
由于合成孔径雷达(SAR)固有的侧视几何特性,时间序列干涉SAR仅能够监测视线(LOS)方向上的位移,这限制了滑坡监测中位移测量的精度。这是因为LOS位移只是某一地面物体实际位移的三维投影。针对这一问题,提出了一种精确数字高程模型(DEM)辅助的边坡位移反演方法,并将其应用于大孤山露天矿高陡边坡的案例研究中。在案例研究中,首先使用激光扫描生成的精确DEM来最小化小基线子集分析中的地形残差。然后,借助精确DEM将LOS位移转换为边坡方向。通过与地面测量结果进行比较,在我们的研究区域中,估计的边坡位移的相对均方根误差(RMSE)对于升轨约为12 - 13%,对于降轨约为5.4 - 9.2%。为了验证实验结果,还与微震监测结果进行了比较。此外,两个结果均发现最大的边坡位移发生在高程从 - 138 m至 - 210 m变化的边坡部分,这与滑坡区域相对应。而且,位移时间序列显示其与降水量存在一定的相关性。本文的结果表明,岩体结构、岩性和降水量是影响高陡采矿边坡稳定性的主要因素。