星载InSAR技术在地质灾害监测领域的应用

云烨 吕孝雷 付希凯 薛飞扬

云烨, 吕孝雷, 付希凯, 等. 星载InSAR技术在地质灾害监测领域的应用[J]. 雷达学报, 2020, 9(1): 73–85. doi: 10.12000/JR20007
引用本文: 云烨, 吕孝雷, 付希凯, 等. 星载InSAR技术在地质灾害监测领域的应用[J]. 雷达学报, 2020, 9(1): 73–85. doi: 10.12000/JR20007
YUN Ye, LÜ Xiaolei, FU Xikai, et al. Application of spaceborne interferometric synthetic aperture radar to geohazard monitoring[J]. Journal of Radars, 2020, 9(1): 73–85. doi: 10.12000/JR20007
Citation: YUN Ye, LÜ Xiaolei, FU Xikai, et al. Application of spaceborne interferometric synthetic aperture radar to geohazard monitoring[J]. Journal of Radars, 2020, 9(1): 73–85. doi: 10.12000/JR20007

星载InSAR技术在地质灾害监测领域的应用

doi: 10.12000/JR20007
基金项目: 国家自然科学基金(41801356),国家重点研发计划(2018YFC1505101)
详细信息
    作者简介:

    云 烨(1989–),女,博士,助理研究员。2015年在北京大学获得博士学位,现担任中国科学院空天信息创新研究院助理研究员。目前正在负责高分专项、国家自然科学基金、十三五预研等项目,主要研究方向为干涉处理及其应用,SAR 3维重建,InSAR大气校正,大气数值模式的应用。E-mail: yunye@aircas.ac.cn

    吕孝雷(1981–),男,中国科学院空天信息创新研究院研究员,博士生导师,中国科学院“百人计划”入选者。2009年在西安电子科技大学获得博士学位,2009年至2013年先后在新加坡南洋理工大学、美国伦斯勒理工学院从事博士后工作。主要研究方向为SAR数据处理、成像、运动目标检测、干涉SAR、遥感形变监测等,已在IEEE、IET等国外著名SCI期刊发表学术论文四十余篇。E-mail: academism2017@sina.com

    付希凯(1992–),男,博士,助理研究员。2019年在中国科学院电子学研究所获得博士学位,现担任中国科学院空天信息创新研究院助理研究员。主要研究方向为分布式干涉SAR数据预处理,干涉处理,几何定位。E-mail: xkfu@mail.ie.ac.cn

    薛飞扬(1993–),男,博士在读。2016年在电子科技大学电子工程学院获得学士学位,现在中国科学院大学攻读博士学位。主要研究方向为InSAR、时序InSAR关键技术研究及其应用。E-mail: xuefeiyang16@mails.ucas.ac.cn

    通讯作者:

    云烨 yunye@aircas.ac.cn

    吕孝雷 academism2017@sina.com

  • 中图分类号: P237

Application of Spaceborne Interferometric Synthetic Aperture Radar to Geohazard Monitoring

Funds: The National Natural Science Foundation of China (41801356), The National Key R&D Program of China (2018YFC1505101)
More Information
  • 摘要: 近年来,星载InSAR技术在地质灾害监测领域显示出越来越大的应用潜力。该文首先介绍了InSAR形变监测的原理;然后系统性回顾了InSAR技术的发展,分析了差分InSAR、时序InSAR等方法的技术特点和适用范围;进而从地质灾害监测应用的角度分析了InSAR技术在地震、滑坡、水利工程、地面沉降等领域的应用现状和发展趋势;最后总结了当前地灾监测应用中InSAR技术在大气效应校正、复杂地区形变信息获取、多维形变信息获取中的关键问题,以期服务于地质灾害动态监测与防治工作。从当前InSAR技术在地质灾害监测的应用来看,该技术正处在广泛的业务应用阶段,随着未来星载SAR卫星系统的发展和行业的驱动,必将发展成为一项成熟的高精度对地观测技术,对地质灾害监测产生巨大的影响。

     

  • 图  1  日本熊本地震形变结果

    Figure  1.  DInSAR deformation map of the Kumamoto earthquakes

    图  2  采用常规PSI技术和JSInSAR技术获得的四川地区某滑坡形变速率图

    Figure  2.  Deformation rate map of the landslide in Sichuan Province obtained by PSI and JSInSAR

    图  3  利用升轨数据获得的拉西瓦水电站周边形变速率图

    Figure  3.  Deformation map around the Laxiwa Hydropower Station obtained from the ascending orbit data

    图  4  利用降轨数据获得的拉西瓦水电站坝体及周边形变速率图

    Figure  4.  Deformation map of the dam and surrounding area of the Laxiwa Hydropower Station obtained from the descending orbit data

    图  5  拉西瓦水电站果卜岸坡区域形变速率图

    Figure  5.  Deformation rate map of the Guobu slope of the Laxiwa Hydropower Station

    图  6  北京市局部地区形变速率图

    Figure  6.  Deformation rate map of local areas in Beijing

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出版历程
  • 收稿日期:  2020-01-22
  • 修回日期:  2020-02-20
  • 网络出版日期:  2020-02-28

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