Shi Xuguo, Yang Chao, Zhang Lu, Jiang Houjun, Liao Mingsheng, Zhang Li, Liu Xiuguo
Faculty of Information Engineering, China University of Geosciences (Wuhan), Wuhan 430074, China.
Faculty of Information Engineering, China University of Geosciences (Wuhan), Wuhan 430074, China; National Engineering Research Center of Geographic Information System, China University of Geosciences (Wuhan), Wuhan 430074, China.
Sci Total Environ. 2019 Jul 15;674:200-210. doi: 10.1016/j.scitotenv.2019.04.140. Epub 2019 Apr 11.
Landslides and debris flows in the Loess Plateau pose great threats to human lives and man-made infrastructure, such as buildings and expressways. Thus, the detection and monitoring of the stability of slopes are crucial in geohazard prevention and management. In this study, the time series synthetic aperture radar interferometry (InSAR) analysis method that combines persistent scatters (PSs) and distributed scatters (DSs) is employed to detect and map active slopes along the upstream Yellow River from the Longyang Gorge dam to the Lijia Gorge dam using one ALOS PALSAR data stack from 2006 to 2011 and two Sentinel-1 data stacks from 2015 to 2017. More than 100 active slopes in a total coverage of 222.5 km were identified. Through a time series displacement analysis of active slopes, we found that changes in the water content of loess slopes induced by rainfall or reservoir impoundment might be a major factor that can activate unstable slopes or accelerate the movement of active slopes.
黄土高原的滑坡和泥石流对人类生命以及建筑物和高速公路等人造基础设施构成了巨大威胁。因此,边坡稳定性的检测与监测在地质灾害预防和管理中至关重要。在本研究中,采用结合了永久散射体(PS)和分布式散射体(DS)的时间序列合成孔径雷达干涉测量(InSAR)分析方法,利用2006年至2011年的一组ALOS PALSAR数据以及2015年至2017年的两组Sentinel-1数据,对黄河上游从龙羊峡大坝到李家峡大坝沿线的活动边坡进行检测和制图。共识别出100多个活动边坡,总面积达222.5千米。通过对活动边坡的时间序列位移分析,我们发现降雨或水库蓄水引起的黄土边坡含水量变化可能是激活不稳定边坡或加速活动边坡移动的主要因素。