Using UAV photogrammetry technology to extract the quantitative parameters of earthquake surface rupture zone:A case study of the southern Zhongwei M7½ earthquake in 1709
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摘要: 本文首先介绍了无人机摄影测量技术获取数字高程模型(digital elevation model,缩写为DEM)和地貌数据(正射影像)的作业流程,对比分析了三种不同质量密集点云生成的DEM在水平位置和高程上的差异;然后以1709年中卫南M7½大地震的主体地表破裂带为例,提取其上地震断层的垂直位错量和水平位移量。研究结果显示:高质量密集点云生成的DEM分辨率可达厘米级,且处理时间不需太长,其水平位置和高程与另外两种质量密集点云生成的DEM差异均小于0.100 m;基于高质量密集点云可生成6.33 cm/pix分辨率的DEM,提取1709年中卫南地震地表破裂带上地震断层的垂直位错量为(0.704±0.293) m,水平位移量为5.1 m,与前人的研究结果相吻合,因此可以代表该地震的同震位移,这表明无人机摄影测量技术能够获取地震地表破裂带典型场点的高分辨率地形地貌数据,并基于生成的DEM可进一步提取地震断层的定量参数。Abstract: This paper firstly introduces the operation flow for obtaining digital elevation model (DEM) and geomorphic data (digital orthophoto map) by unmanned aerial vehicle (UAV)photogrammetry technology, and compares and analyzes the differences in horizontal position and elevation of DEM generated by three kinds of dense point clouds with different masses. Then, the vertical and horizontal displacements of seismic faults on the main surface rupture zone of the south of Zhongwei M7½ earthquake in 1709 were extracted. The results showed that, as for the DEM generated by dense point cloud of high quality, its resolution was in centimeters, and the processing time was not too long. Compared with DEM generated from the other two kinds of dense point clouds, the difference in horizontal position and elevation is less than 0.100 m. Based on high quality dense point cloud we can generate the DEMs with resolution of 6.33 cm/pix, extract the vertical dislocation of the fault on the surface rupture of 1709 earthquake as long as (0.704±0.293) m, horizontal displacement of 5.1 m, which was consistent with previous studies and therfore represented the co-seismic slip of the 1709 earthquake. This suggests that by the UAV photogrammetry technology we can obtain high resolution topography data of typical sites on the earthquake surface rupture zone, and seismic fault quantitative parameters can be further extracted based on the generated DEM.
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图 3 由地形剖面确定的垂直断错量
图(b)和(c)中,黑色虚线为上、下盘拟合线,蓝色虚线是根据坡度绘制的上、下盘分界线(a) 地形剖面位置;(b) 由l1剖面确定的垂直断错量;(c) 由 l2剖面确定的垂直断错量
Figure 3. The vertical displacement of the fault extracted from the terrain profiles
In Figs. (b) and (c),the black dashed lines are the fitting lines for the hanging wall and footwall,and the blue vertical lines are the boundary lines between hanging wall and footwall determined by slope. (a) The position of the terrain profiles l1 and l2;(b) The vertical displacement of the fault from the l1;(c) The vertical displacement of the fault from the l2
图 4 基于坡度图和等高线图确定的水平位移量及野外实测水平位移值
(a) 坡度图;(b) 坡度图与1 m间隔等高线的叠置图;(c) 水平位错量;(d) 野外实测水平位移
Figure 4. The horizontal displacement of the fault extracted from the superposition of slope map and 1 m interval contour map as well as that measured in the field
(a) The slope map;(b) Overlapping of slope map and 1 m interval contour map;(c) The horizontal displacement of the fault;(d) The horizontal displacement measured in the field
表 1 对齐照片、生成密集点云和生成网格的参数设置
Table 1 Parameter setting for aligning photo,generating dense point clouds,and generating grids
对齐照片 生成密集点云 生成网格 精度 成对预选 质量 深度过滤 表面类型 源数据 面数 高 参考 超高,高,中 进取 高度场 密集点云 中 表 2 不同质量密集点云生成的DEM和正射影像的分辨率及其它相关参数
Table 2 Resolution of DEM and orthophoto map generated by dense point clouds of different masses and the other parameters
密集点云
的质量处理时间/h DEM 正射影像分辨率
/(cm·pix−1)点云密度/(点·m−2) 分辨率/(cm·pix−1) 超高 15 876 3.38 3.38 高 3 219 6.76 3.38 中 0.6 55 13.50 3.38 表 3 相机位置误差估计值
Table 3 The error estimates of camera locations
x误差/m y误差/m xy误差/m z误差/m 0.540 0.338 0.637 3.127 表 4 DEM中点的投影坐标和高程范围
Table 4 The projected coordinates and elevation ranges of midpoint in DEM
不同质量密集点云 x/m y/m 最低高程/m 最高高程/m 高程差/m 超高 495639.212 4142958.128 1281.045 1338.719 57.674 超高与高的差异 0.000 0.007 0.057 0.079 0.022 高 495639.212 4142958.135 1281.102 1338.798 57.696 高与中等的差异 0.089 0.041 0.008 0.046 0.038 中等 495639.123 4142958.176 1281.094 1338.752 57.658 -
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