Time Series Analysis of Landslide Dynamics Using an Unmanned Aerial Vehicle (UAV)
Time Series Analysis of Landslide Dynamics Using an Unmanned Aerial Vehicle (UAV)
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DOI：
10.3390/rs70201736
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发表时间：
2015-02
期刊：
影响因子：
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通讯作者：
D. Turner;A. Lucieer;S. M. Jong
中科院分区：
文献类型：
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作者：
D. Turner;A. Lucieer;S. M. Jong
在这项研究中，我们使用无人驾驶飞行器（UAV）在四年内的七个时间节点收集了一系列高分辨率图像，以评估滑坡动态。应用运动结构恢复（SfM）技术创建了滑坡表面的数字表面模型（DSMs），其水平精度为4 - 5厘米，垂直精度为3 - 4厘米。通过比较滑坡的非活动区域来检查和校正后续DSMs的配准精度，这将对齐误差最小化至平均0.07米。测量了滑坡面积和前缘坡度等变量，并发现了时间变化模式。在时间序列上测量了滑坡特定区域的体积变化。使用COSI - Corr图像相关算法跟踪和量化了滑坡的表面移动，但未进行地面验证。利用历史航空照片创建了一个基准DSM，发现滑坡的总位移约为6630立方米。这项研究展示了一种稳健且可重复的算法，该算法允许在相对较长的时间序列内使用无人机对滑坡动态进行测绘和监测。
In this study, we used an Unmanned Aerial Vehicle (UAV) to collect a time series of high-resolution images over four years at seven epochs to assess landslide dynamics. Structure from Motion (SfM) was applied to create Digital Surface Models (DSMs) of the landslide surface with an accuracy of 4–5 cm in the horizontal and 3–4 cm in the vertical direction. The accuracy of the co-registration of subsequent DSMs was checked and corrected based on comparing non-active areas of the landslide, which minimized alignment errors to a mean of 0.07 m. Variables such as landslide area and the leading edge slope were measured and temporal patterns were discovered. Volumetric changes of particular areas of the landslide were measured over the time series. Surface movement of the landslide was tracked and quantified with the COSI-Corr image correlation algorithm but without ground validation. Historical aerial photographs were used to create a baseline DSM, and the total displacement of the landslide was found to be approximately 6630 m3. This study has demonstrated a robust and repeatable algorithm that allows a landslide’s dynamics to be mapped and monitored with a UAV over a relatively long time series.