Monitoring Based on InSAR for the Xinmo Village Landslide in Western Sichuan, China

Zezhong Zheng, Shuang Yu, Chuhang Xie, Jiali Yang, Mingcang Zhu, He Yong
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Abstract

A devastating landslide incident occurred on 24 June 2017, causing huge losses for Xinmo Village in western Sichuan. In this paper, we used two interferometric synthetic aperture radar (InSAR) methods, permanent scatterer (PS)-InSAR and small baseline subset (SBAS)- InSAR, to analyze deformation signals in the area in the 2 years leading up to the landslide event using Sentinel-1A ascending data. Our experimental findings from PS-InSAR and SBAS-InSAR revealed that the deformation rates in the study region ranged between –50 to 20 mm/year and –30 to 10 mm/year, respectively. Furthermore, the deformation rates of the same points, as determined by these methods, exhibited a significant increase prior to the event. We also investigated the causal relationship between rainfall and landslide events, demonstrating that deformation rates correlate with changes in rainfall, albeit with a time lag. Therefore, using time-series InSAR for landslide monitoring in Xinmo Village is a viable approach.
基于 InSAR 对中国四川西部新磨村滑坡的监测
2017 年 6 月 24 日,四川西部新磨村发生破坏性山体滑坡事件,造成巨大损失。在本文中,我们使用两种干涉合成孔径雷达(InSAR)方法,即永久散射体(PS)-InSAR 和小基线子集(SBAS)-InSAR,利用 Sentinel-1A 升空数据分析了滑坡事件发生前两年该地区的形变信号。PS-InSAR 和 SBAS-InSAR 的实验结果表明,研究区域的变形率分别为 -50 至 20 毫米/年和 -30 至 10 毫米/年。此外,根据这些方法测定的相同点的形变率在事件发生前有显著增加。我们还研究了降雨量与滑坡事件之间的因果关系,结果表明,变形率与降雨量的变化相关,尽管存在时滞。因此,使用时间序列 InSAR 监测新磨村滑坡是一种可行的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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