甘肃省舟曲县城周边活动滑坡InSAR探测  

Active Landslides Detection in Zhouqu County,Gansu Province Using InSAR Technology

作　　者：代聪 李为乐[1] 陆会燕 杨帆[1] 许强[1] 简季[2] DAI Cong;LI Weile;LU Huiyan;YANG Fan;XU Qiang;JIAN Ji(State Key Laboratory of Geohazard Prevention and Geoenvironment Protection,Chengdu University of Technology,Chengdu 610059,China;College of Earth Sciences,Chengdu University of Technology,Chengdu 610059,China)

机构地区：[1]成都理工大学地质灾害防治与地质环境保护国家重点实验室,四川成都610059 [2]成都理工大学地球科学学院,四川成都610059

出　　处：《武汉大学学报（信息科学版）》2021年第7期994-1002,共9页Geomatics and Information Science of Wuhan University

基　　金：国家自然科学基金川藏铁路专项(41941019);国家创新研究群体科学基金(41521002);四川省科技支撑计划项目(2017JQ0031,2018SZ0339);四川省地震科技创新团队专项(201901)。

摘　　要：甘肃省舟曲县城周边区域是中国典型的滑坡、泥石流高易发区,2018-07-12县城下游江顶崖发生了滑坡堵江,对当地居民生命财产和基础设施安全造成了严重威胁。为查明舟曲县城周边区域潜在的滑坡隐患,利用2017-10—2018-12 Sentinel-1A雷达卫星升降轨数据,基于短基线干涉测量方法对舟曲县城上下游区域活动滑坡进行了探测,共探测出23处活动滑坡。结合光学遥感影像目视解释和现场调查,对江顶崖、门头坪、锁儿头、泄流坡滑坡等4处典型滑坡形变特征进行了详细分析,发现该区域滑坡形变速率主要受降雨影响。研究结果可为舟曲县城防灾减灾提供重要的决策依据。Objectives: Zhouqu County in Gansu Province is highly prone to landslides. On July 12, 2018,a landslide blocked the Bailong River near the county, posing a serious threat to the life and property of local residents and the safety of infrastructure. The early identification of potential landslides around this area is of great significance to protect the life and property of local residents and the security of its infrastructure.Methods: Firstly, small baseline subset interferometry technology(SBAS-InSAR) was adopted to identify the potential active landslides in the surrounding area of Zhouqu County, with the Sentinel-1 A satellite ascending and descending images from October 2017 to December 2018. Then, a combination of optical remote sensing image interpretation and field investigation is used to determine and identify potential landslides. The visual interpretation method can be used to identify landslides that have occurred or are occurring on the optical images. The field investigation was used to verify the landslide results identified by InSAR and optical imagery to increase the effectiveness and accuracy of landslide detection. Results: A total of 23 active landslides were detected in the study area, with 16 active landslides detected on the ascending images and 11 on the descending images, with 4 active landslides having valid deformation information detected on both the ascending and descending images. Combined with the visual interpretation of optical remote sensing images and field investigation, the deformation characteristics of 4 typical landslides, including Jiangdingya, Mentouping, Suoertou, and Xieliupo Landslides, were analyzed. It was found that the deformation rates of Jiangdingya, Mentouping, and Xieliupo Landslides were significantly higher during the rainy season than during the non-rainy season, and the Suoertou Landslide did not show a significant increase in the deformation rate during the rainy season but showed fluctuations in the deformation rate during the rainy season. Conclusions:

关 键 词：舟曲县城 滑坡隐患 早期识别 短基线干涉测量 

分 类 号：P237[天文地球—摄影测量与遥感]