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Extraction of landslides in the 2016 Kumamoto earthquake using multi-temporal Lidar data

机译:使用多时相激光雷达数据提取2016年熊本地震中的滑坡

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Extraction of landslides from a pair of Lidar data taken before and after the 2016 Kumamoto, Japan, earthquake was carried out. The spatial correlation coefficient of the two Lidar data was calculated, and the horizontal shift of the April-23 DSM with the maximum correlation coefficient was considered as the crustal movement by the April-16 main-shock. By taking the difference of the co-registered DSMs, the change of the surface elevation was calculated. This elevation change includes many effects due to the earthquake, such as landslides and building collapses, and the other temporal changes, such as parking cars and construction/rescue activities. Thus in this study, only large-scale elevation changes more than plus and minus 2.0 m and the areas of larger than 200 square meters were extracted as possible landslides. The extracted areas were compared with aerial photos taken after the Kumamoto earthquake and other soil movement maps made for this event. The result shows that large-scale landslides were easily extracted by the difference of the DSMs and even ground deformations along surface ruptures, where trees were torn down, could be identified.
机译:从2016年日本熊本地震前后获得的一对激光雷达数据提取了滑坡。计算了两个激光雷达数据的空间相关系数,并将具有最大相关系数的4月23日DSM的水平位移视为4月16日主震的地壳运动。通过考虑共同注册的DSM的差异,可以计算出表面高度的变化。这种高程变化包括由于地震引起的许多影响,例如滑坡和建筑物倒塌,以及其他随时间变化的变化,例如停车场和建筑/救援活动。因此,在本研究中,仅大范围的海拔变化超过正负2.0 m,并且将大于200平方米的区域提取为可能的滑坡。将提取的区域与熊本地震后拍摄的航拍照片以及为此事件制作的其他土壤运动图进行比较。结果表明,由于DSMs的差异,很容易提取大规模的滑坡,甚至可以识别沿树木破裂的表面破裂处的地面变形。

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