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基于光学遥感与InSAR技术的潜在滑坡与老滑坡综合识别
引用本文:吴明辕,罗明,刘岁海.基于光学遥感与InSAR技术的潜在滑坡与老滑坡综合识别[J].中国地质灾害与防治学报,2022,33(3):84-93.
作者姓名:吴明辕  罗明  刘岁海
作者单位:1.西南科技大学环境与资源学院, 四川 绵阳 621010
基金项目:全国地质灾害高易发区灾害隐患识别(0733-20180876)
摘    要:我国滇西北区域地质灾害频发,主要灾害类型为滑坡,对该区域进行滑坡类地质灾害隐患识别是有效的防灾减灾措施,传统的地质灾害隐患识别手段较为单一,且依赖大量的人力,调查效率较低。利用WordView2、Sentinel-1A、ALOS-2几种遥感卫星数据,进行Stacking-InSAR等技术的处理,得到多种光学卫星影像和InSAR处理的地表形变图,建立滇西北区域潜在滑坡与老滑坡的光学解译标志和InSAR识别标志,并进行多次目视解译和人工交互式解译。依据解译、识别成果,总结识别方法并进行野外调查验证。共识别潜在滑坡与老滑坡696处,为今后滇西北区域地质灾害调查与评价提供新的调查思路和技术参考。

关 键 词:滇西北    滑坡隐患识别    遥感    InSAR
收稿时间:2021-04-27

Comprehensive identification of potential and old landslides based on optical remote sensing and InSAR technologies: A case study in northwestern Yunnan Province
Affiliation:1.Southwest University of Science and Technology, Mianyang, Sichuan 621010 , China2.Sichuan Institute of Geological Survey, Chengdu, Sichuan 610081, China
Abstract:Potential geological disasters frequently occur in northwestern Yunnan. Landslide is the main type of geohazard. The identification of landslide in this area is an effective disaster prevention and mitigation measure. The traditional methods of identifying potential geological hazards are relatively single and rely on a large number of manpower and the investigation efficiency are not satisfactory. This paper processes the data from WordView2, Sentinel-1A, and ALOS-2 remote sensing satellite by using the Stacking-InSAR and other technologies, and a variety of optical satellite images and InSAR-processed surface deformation maps were obtained. Optical interpretation signs and InSAR identification signs had undergone multiple visual interpretations and manual interactive interpretations, and based on the interpretation and recognition results, the identification methods are summarized and field investigations were also carried out to verify the results. A total of 806 potential landslides and old landslides were identified, providing new survey ideas and technical references for the future investigation and evaluation of geological disasters in northwestern Yunnan.
Keywords:
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