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A Study on Recent Ground Deformation Near Patras, Greece

机译:希腊帕特雷附近最近的地面变形研究

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In recent years urbanized areas have been expanding more and more into hillside areas, which increases therisk for landslides to destroy or gravely damage human settlements, industrial establishments and importantinfrastructure. Greece and in particular the northwestern tip of the Peloponnese Peninsula are often affected bylandslides. A well-known and documented landslide south-east of Patras is located in that area and was chosenas the main focus for this study. The landslide collapsed and thus submerged the main road connecting the smallvillage Moira and Patras on January 20, 2016. Immediately afterwards the geometry and geology of the affectedarea have been determined using GNSS Measurements, UAV Campaigns and DInSAR techniques. However, thevelocity of the post-collapse movement has not been investigated.In order to make this determination two time series of SAR images acquired by the two Sentinel-1 satellites froman ascending and descending orbit were evaluated using the advanced InSAR technique of persistent scattererinterferometry. The result is a map of the mean velocities the identified persistent scatterers were experiencingin the time period from January 2017 to June 2019. The persistent scatterer density in the rural areas of theregion was sufficient enough to identify the landslide within the results. Roughly 80 persistent scatterer witha velocity of more than ± 8 mm/a in the line of sight of the sensor were identified within the outlines of thelandslide (approximately 750 m~2), indicating that the landslide is experiencing post-collapse movement.
机译:近年来,城市化地区已越来越多地扩展到山坡地带,这增加了 滑坡破坏或严重破坏人类住区,工业场所和重要建筑物的风险 基础设施。希腊,尤其是伯罗奔尼撒半岛的西北端,经常受到 滑坡。该地区位于帕特雷(Patras)东南部,是一个著名的有文献记载的滑坡,它被选中。 作为这项研究的主要重点。滑坡塌陷,淹没了连接小路的主要道路。 于2016年1月20日到达Moira和Patras村。 已使用GNSS测量,UAV运动和DInSAR技术确定了该区域。但是,那 塌陷后运动的速度尚未研究。 为了进行此确定,两个Sentinel-1卫星从以下位置获取了两个时间序列的SAR图像: 使用先进的InSAR持久散射体技术评估了上升和下降轨道 干涉仪。结果是确定的持久性散射体正在经历的平均速度的图 在2017年1月至2019年6月期间。 区域足以识别结果中的滑坡。大约80个持久散射体 在传感器的轮廓内识别出传感器视线内的速度超过±8 mm / a。 滑坡(约750 m〜2),表明滑坡正在经历崩塌后的运动。

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