藏东冻土区滑坡形变时序InSAR监测分析

受气候暖湿化和冻融作用的影响，近年来西藏东部地区的山体滑坡多发频发，对人民生命财产安全造成严重威胁，制约了当地经济社会发展，因此，迫切需要利用有效手段对滑坡灾害隐患开展大范围调查与早期识别。以藏东317国道矮拉山地区为例，利用小基线集时序InSAR（Interferometric Synthetic Aperture Radar）技术，分别对2017年3月—2019年7月期间Sentinel-1A SAR升、降轨数据集进行地表形变监测分析，获取了该地区滑坡体隐患的分布情况，并讨论了滑坡历史形变演化特征及成因。结果表明：大部分区域较为稳定，滑坡隐患主要集中在山谷两侧，升降轨InSAR提高了滑坡监测识别的准确性和覆盖度；冻融滑坡形变过程与降雨型滑坡存在差异，呈现平稳期和失稳期交替出现的季节性变化特征；形变过程主要受冻融和降雨影响，两者共同作用加速坡体变形。实验结果验证了InSAR技术能够有效弥补传统监测手段的不足，可在高山冻土区滑坡隐患早期识别与监测防治中发挥重要作用。

Monitoring landslides in seasonal frozen regions in eastern Tibet with InSAR:a case study in Aila Mountain section of National Highway 317

Due to the effects of climate warming， wetting， freezing and thawing， landslides occur frequently in eastern Tibet in recent years， which poses a serious threat to the safety of people’s lives and property safety and restricts the local economic and social development. Therefore， an effective method of large-scale landslides hazards investigation and early identification is required urgently. In this study， using Small Baseline Subset （SBAS） InSAR method and sentinel-1A ascending and descending SAR images acquired from March 2017 to July 2019， the surface deformation and distribution of landslide hazards in this area is achieved， and the characteristics of historical deformation evolution and causes of landslide are investigated as well. The results show that： （1） Most of the areas are relatively stable， and the potential landslide hazards mainly concentrate on both sides of the valley. The accuracy and coverage of landslide monitoring and identification are improved by combining ascending and descending InSAR. （2） The deformation process of the freeze-thaw landslide is different from that of the rainfall-induced landslide， showing the seasonal variation characteristics of the stable and the instable period alternatively. （3） The deformation development is mainly affected by freeze-thaw and rainfall process， and both of them accelerate the slope displacement. The results suggest that InSAR technology can be an effective alternative for the shortcomings of traditional monitoring methods， and can play an important role in the early identification， monitoring and prevention of landslide hazards in alpine permafrost regions.