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Detection of Earthquake-Induced Landslides during the 2018 Kumamoto Earthquake Using Multitemporal Airborne Lidar Data

机译:使用多时空机载激光雷达数据探测2018年熊本地震中的地震诱发滑坡

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A series of earthquakes hit Kumamoto Prefecture, Japan, continuously over a period of two days in April 2016. The earthquakes caused many landslides and numerous surface ruptures. In this study, two sets of the pre- and post-event airborne Lidar data were applied to detect landslides along the Futagawa fault. First, the horizontal displacements caused by the crustal displacements were removed by a subpixel registration. Then, the vertical displacements were calculated by averaging the vertical differences in 100-m grids. The erosions and depositions in the corrected vertical differences were extracted using the thresholding method. Slope information was applied to remove the vertical differences caused by collapsed buildings. Then, the linked depositions were identified from the erosions according to the aspect information. Finally, the erosion and its linked deposition were identified as a landslide. The results were verified using truth data from field surveys and image interpretation. Both the pair of digital surface models acquired over a short period and the pair of digital terrain models acquired over a 10-year period showed good potential for detecting 70% of landslides.
机译:2016年4月,日本熊本县连续两天遭受了一系列地震。地震造成许多山体滑坡和许多地面破裂。在这项研究中,使用了两组事前和事后机载激光雷达数据,以检测沿二田川断层的滑坡。首先,通过亚像素配准消除了由地壳位移引起的水平位移。然后,通过平均100米网格中的垂直差异来计算垂直位移。使用阈值法提取校正后的垂直差异中的侵蚀和沉积。应用了坡度信息以消除由倒塌的建筑物引起的垂直差异。然后,根据纵横比信息从侵蚀中识别出相关的沉积物。最后,侵蚀及其相关的沉积物被确定为滑坡。使用来自实地调查和图像解释的真实数据验证了结果。在短期内获得的这对数字地面模型和在十年内获得的这对数字地形模型都显示出探测70%滑坡的良好潜力。

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