Mapping landslide displacements using Structure from Motion (SfM) and image correlation of multi-temporal UAV photography
Mapping landslide displacements using Structure from Motion (SfM) and image correlation of multi-temporal UAV photography
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DOI：
10.1177/0309133313515293
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发表时间：
2014-02-01
影响因子：
3.9
通讯作者：
Turner, Darren
中科院分区：
文献类型：
--
作者：
Lucieer, Arko;de Jong, Steven M.;Turner, Darren
在这项研究中，我们提出了一个灵活的，具有成本效益的，准确的方法来监测滑坡使用小型无人机（UAV）收集航空摄影。在第一部分中，我们应用结构从运动（SfM）的工作流程，从多视角无人机摄影在塔斯马尼亚州东南部的山体滑坡的3D模型。3D模型和由此产生的DEM和正射影像镶嵌图的几何精度与大地测量GPS接收器协调的地面控制点进行了测试。水平精度为7厘米，垂直精度为6厘米。在第二部分中，2011年7月16日和2011年11月10日获得的两个DEM和正射镶嵌图进行了比较，以研究滑坡动力学。对COSI-Corr图像相关技术进行了评价，以量化和绘制地形位移图。来自相关的两个hillshaded DEM层的位移矢量的大小和方向对应的滑坡变化的视觉解释。结果表明，该算法可以准确地映射的脚趾，大块的土壤和植被斑块上的滑坡顶部的位移，但不能映射的主要陡坎的撤退。结论是，无人机为基础的图像结合三维场景重建和图像相关算法提供了灵活和有效的工具，以地图和监测滑坡动态。
In this study, we present a flexible, cost-effective, and accurate method to monitor landslides using a small unmanned aerial vehicle (UAV) to collect aerial photography. In the first part, we apply a Structure from Motion (SfM) workflow to derive a 3D model of a landslide in southeast Tasmania from multi-view UAV photography. The geometric accuracy of the 3D model and resulting DEMs and orthophoto mosaics was tested with ground control points coordinated with geodetic GPS receivers. A horizontal accuracy of 7 cm and vertical accuracy of 6 cm was achieved. In the second part, two DEMs and orthophoto mosaics acquired on 16 July 2011 and 10 November 2011 were compared to study landslide dynamics. The COSI-Corr image correlation technique was evaluated to quantify and map terrain displacements. The magnitude and direction of the displacement vectors derived from correlating two hillshaded DEM layers corresponded to a visual interpretation of landslide change. Results show that the algorithm can accurately map displacements of the toes, chunks of soil, and vegetation patches on top of the landslide, but is not capable of mapping the retreat of the main scarp. The conclusion is that UAV-based imagery in combination with 3D scene reconstruction and image correlation algorithms provide flexible and effective tools to map and monitor landslide dynamics.