Detection of geometric change in railway curves caused by earthquakes, using high-resolution stereo satellite images
Detection of geometric change in railway curves caused by earthquakes, using high-resolution stereo satellite images
复制标题
使用高分辨率立体卫星图像检测地震引起的铁路曲线的几何变化
DOI：
10.1007/s11069-015-1849-9
复制
发表时间：
2015-06
期刊：
影响因子：
3.7
通讯作者：
Feng Tienan
中科院分区：
文献类型：
--
作者：
Tong Xiaohua;Hong Zhonghua;Liu Shijie;Chen Peng;Jin Yanmin;Xie Huan;Liu Shuang;Zhang Songlin;Feng Tienan
铁路曲线的快速变化检测对于地震等突发灾害的破坏评估至关重要。铁路曲线几何变化的检测是通过对比地震前后铁路曲线的形状变化来测量铁路曲线的几何变化。本文提出了一种利用地震前数字地形图和地震后立体IKONOS图像进行铁路曲线变化检测的方法。该方法主要包括以下四个部分：(1)首先根据数字地形图上的数字化点，利用最小二乘平差估计地震前铁路曲线的几何参数；(2)从高分辨率立体卫星影像中提取地震后铁路曲线上的特征点，并利用有理函数多项式系数束平差进一步细化这些点的地面坐标。(3)引入位移模型、尺度与位移模型、仿射模型、二阶多项式模型和相似模型五种变化检测模型来描述地震前后铁路曲线的几何变化。在此基础上，基于变化检测模型和震前铁路曲线，建立了一个目标函数，以最小化从高分辨率立体图像中提取的震后点与变换后点之间的距离平方。以都江堰市为研究对象，进行了2008年汶川地震后铁路曲线变化检测的实证研究。实验结果表明了所提几何变化检测方法的可行性，结果表明：(1)地震前铁路曲线几何参数估计的均方根误差为0.068 m，表明所提最小二乘方法利用数字地形图能够以厘米级精度恢复地震前铁路的几何曲线。(2)利用4种偏差补偿模型对震前高分辨率卫星影像提取的地面控制点进行了精化处理，结果表明，二阶多项式模型在纵向上的定位精度最高，分别为0.788 m和0.701 m。结果表明，二阶多项式模型是提高事后立体图像对中地点提取精度的最佳偏差补偿模型。(3)对比5种地震前后铁路曲线位移变化检测模型，仿射模型精度最高，为0.318 m。结果表明，基于地震前数字地形图和震后IKONOS立体图像的变化检测方法可以以分米级的精度检测出地震引起的铁路曲线的几何变化。
Rapid change detection of railway curves is crucial for the damage assessment of unexpected disasters such as earthquakes. Detection of the geometric change in railway curves involves the measurement of the shape change by comparing the pre- and post-seismic railway curves. This paper proposes an approach for change detection in railway curves by the use of a pre-seismic digital topographic map and post-seismic stereo IKONOS images. The proposed approach consists of four main components, they are as follows: (1) The geometric parameters of the pre-seismic railway curves are first estimated based on the digitized points from the digital topographic map by the use of least squares adjustment. (2) The feature points on the post-seismic railway curves are then extracted from the high-resolution stereo satellite imagery, and the ground coordinates of these points are further refined by the use of rational function polynomial coefficients bundle adjustment. (3) Five change detection models—the shift model, the scale and shift model, the affine model, the second-order polynomial model, and the similarity model—are introduced to describe the geometric change between the pre- and post-seismic railway curves. Based on this, an objective function is formulated to minimize the squared distances between the transformed points from the post-seismic points refined from the high-resolution stereo imagery, based on the change detection model and the pre-seismic railway curves. An empirical experiment in change detection in railway curves as a result of the 2008 Wenchuan earthquake in Dujiangyan City, China, was conducted. The experimental results showed the feasibility of the proposed geometric change detection method, they are as follows: (1) The root-mean-square error of the geometric parameter estimation of the pre-seismic railway curve was 0.068 m, which showed that the proposed least squares approach could recover the geometric curve of the pre-event railway with a centimeter-level accuracy by the use of the digital topographic map. (2) The result of the refinement of the ground control points extracted from the pre-seismic high-resolution satellite imagery by the use of the four bias compensation models showed that the second-order polynomial model achieved the highest geo-positioning accuracy of 0.788 and 0.701 m in thex- andy-directions. This result indicated that the second-order polynomial model was the best bias compensation model for improving the accuracy of ground points extracted from the post-event stereo image pairs. (3) A comparison of the five change detection models, in terms of displacement between the pre- and post-seismic railway curves, showed that the affine model obtained the highest accuracy of 0.318 m. This result showed that the geometric change in railway curves due to earthquakes could be detected with a decimeter-level accuracy by the use of the proposed change detection approach, based on a pre-seismic digital topographic map and post-seismic IKONOS stereo images.
登录
查看更多内容
DOI：
10.1061/(asce)0733-9453(2007)133:1(29
发表时间：
2007-02
期刊：
Journal of Surveying Engineering-asce
影响因子：
--
作者：
S. Easa;Haibin Dong;Jonathan Li
通讯作者：
S. Easa;Haibin Dong;Jonathan Li
DOI：
10.1111/phor.12015
发表时间：
2013-06
期刊：
The Photogrammetric Record
影响因子：
--
作者：
Luping Lu;Yong Zhang;Pengjie Tao;Zuxun Zhang;Yongjun Zhang
通讯作者：
Luping Lu;Yong Zhang;Pengjie Tao;Zuxun Zhang;Yongjun Zhang
DOI：
10.1016/j.cageo.2012.12.006
发表时间：
2013-04
期刊：
Comput. Geosci.
影响因子：
--
作者：
N. Zarrinpanjeh;F. Samadzadegan;T. Schenk
通讯作者：
N. Zarrinpanjeh;F. Samadzadegan;T. Schenk
基于最小二乘和方差分量估计引入尺度参数调整GIS中的面积对象
DOI：
10.1080/13658810802077826
发表时间：
2009-10
影响因子：
5.7
作者：
Shi, W.Z.;Tong, X.H.;Liu, D.J.
通讯作者：
Liu, D.J.
影响因子：
1.3
作者：
Fraser, CS;Hanley, HB
通讯作者：
Hanley, HB