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InSAR技术和孕灾背景指标相结合的地灾隐患识别

董佳慧 牛瑞卿 亓梦茹 丁赞 徐航 何睿

董佳慧, 牛瑞卿, 亓梦茹, 丁赞, 徐航, 何睿. InSAR技术和孕灾背景指标相结合的地灾隐患识别[J]. 地质科技通报, 2022, 41(2): 187-196. doi: 10.19509/j.cnki.dzkq.2022.0024
引用本文: 董佳慧, 牛瑞卿, 亓梦茹, 丁赞, 徐航, 何睿. InSAR技术和孕灾背景指标相结合的地灾隐患识别[J]. 地质科技通报, 2022, 41(2): 187-196. doi: 10.19509/j.cnki.dzkq.2022.0024
Dong Jiahui, Niu Ruiqin, Qi Mengru, Ding Zan, Xu Hang, He Rui. Identification of geological hazards based on the combination of InSAR technology and disaster background indicators[J]. Bulletin of Geological Science and Technology, 2022, 41(2): 187-196. doi: 10.19509/j.cnki.dzkq.2022.0024
Citation: Dong Jiahui, Niu Ruiqin, Qi Mengru, Ding Zan, Xu Hang, He Rui. Identification of geological hazards based on the combination of InSAR technology and disaster background indicators[J]. Bulletin of Geological Science and Technology, 2022, 41(2): 187-196. doi: 10.19509/j.cnki.dzkq.2022.0024

InSAR技术和孕灾背景指标相结合的地灾隐患识别

doi: 10.19509/j.cnki.dzkq.2022.0024
基金项目: 

2019年中央自然灾害防治体系建设补助资金项目"恩施州重大隐患区区域综合遥感监测与隐患识别" HBYM-GTJ-2020-GK-1002

中国地质调查局武汉地质调查中心项目"三峡库区专业监测建设和预警分析指导" 0001212012AC50021

详细信息
    作者简介:

    董佳慧(1996—), 女, 现正攻读地球探测与信息技术专业博士学位, 主要从事地灾遥感和环境遥感研究。E-mail: ivy.dong@cug.edu.cn

    通讯作者:

    牛瑞卿(1969—), 男, 教授, 主要从事3S和地质灾害研究工作。E-mail: rqniu@163.com

  • 中图分类号: X87

Identification of geological hazards based on the combination of InSAR technology and disaster background indicators

  • 摘要: 合成孔径雷达干涉测量(interferometric synthetic aperture radar, 简称InSAR)是获取地表形变的重要手段, 由于InSAR数据获取的限制和数据处理中产生的精度误差等问题, 在地灾隐患识别方面的工作还需要联合地质灾害本身进行分析。为此提出了一种基于InSAR技术与研究区孕灾背景指标相结合的方法, 并将其应用于三峡库区巴东段的地灾隐患识别研究中。研究结果表明, 使用ALOS-2 PALSAR雷达影像, 应用时序InSAR技术得到了研究区的变形空间分布和变化速率, 并结合研究区的孕灾背景, 将易发性等级、坡度、工程岩组和是否与灾害目录重叠4个指标作为地灾隐患判别的指标, 综合识别出19处疑似地灾隐患区, 然后对疑似地灾隐患区进行了逐一野外核查, 经验证地灾隐患识别成功率为78.9%。研究成果证明了将InSAR技术和孕灾背景相结合进行地灾隐患识别方法的可行性, 可在区域灾害识别中发挥重要作用。

     

  • 图 1  研究区位置

    Figure 1.  Location map of the study area

    图 2  时空基线图

    1~8为影像编号

    Figure 2.  Spatial and temporal baselines of SAR datasets

    图 3  雷达视线方向的年均形变速率

    Figure 3.  Average variable speed of deformation along the radar line of sight

    图 4  因子分级图

    Figure 4.  Hierarchical graphs of factors

    图 5  易发性分区图

    Figure 5.  Zoning map of susceptibility using the CNN-LSTM model

    图 6  研究区内已知灾害点坡度柱状图

    Figure 6.  Slope histogram of disasters known in the study area

    图 7  地灾隐患区分布图

    Figure 7.  Distribution map of potential hazard areas

    图 8  P2变形区InSAR监测形变速率(a)及现场照片(b, c)

    a.雷达视线向形变速率; b.地面裂缝现场照片; c.路基裂缝

    Figure 8.  InSAR monitoring deformation rate (a) and on-site photos (b, c) of the deformation zone P2

    图 9  累积形变量曲线图

    Figure 9.  Curve of cumulative deformation

    表  1  ALOS-2数据成像时间表

    Table  1.   Timeline of ALOS-2 digital imaging

    序号 成像时间
    1 2020/04/11
    2 2020/05/23
    3 2020/06/20
    4 2020/07/04
    5 2020/08/01
    6 2020/09/12
    7 2020/10/10
    8 2020/11/07
    下载: 导出CSV

    表  2  地灾隐患区判别指标情况

    Table  2.   Conditions of evaluation indicators of potential dazard areas

    编号 判别指标 判别指标个数
    易发性等级 坡度/(°) 工程岩组 是否与灾害目录重叠
    P1 极高易发 10~20 较软 4
    P2 极高易发 20~30 较软 4
    P3 高易发 10~20 极软 3
    P4 极高易发 20~30 极软 3
    P5 极高易发 20~30 坚硬 3
    P6 高易发 10~20 极软 4
    P7 极高易发 20~30 较软 4
    P8 极高易发 20~30 极软 3
    P9 中易发 20~30 软岩 4
    P10 中易发 30~40 软岩 4
    P11 中易发 10~20 软岩 3
    P12 中易发 30~40 软岩 4
    P13 极高易发 20~30 较软 4
    P14 极高易发 20~30 坚硬 3
    P15 极高易发 10~20 坚硬 3
    P16 高易发 20~30 较软 4
    P17 极高易发 10~20 较软 4
    P18 极高易发 10~20 坚硬 3
    P19 极高易发 10~20 坚硬 2
    下载: 导出CSV

    表  3  潜在地灾点位及变形特征统计

    Table  3.   Statistics table of potential hazard sites and deformation characteristics

    编号 最大沉降速率/ (mm·a-1) 经度 纬度 变形特征 证实灾种
    P1 -156.746 110° 23' 10.470" E 31° 2' 30.743" N 公路发育多条沉降变形裂缝,已废弃建筑物墙开裂,公路变形长度约10 m 滑坡
    P2 -186.597 110° 27' 11.149" E 31° 1' 57.373" N 道路存在裂缝,走向220°,深度约40 cm 滑坡
    P3 -166.277 110° 26' 1.313" E 31° 3' 40.856" N 可见公路发育弧形裂缝,走向195°,缝宽约1 cm,长约8 m 滑坡
    P4 -203.549 110° 26' 31.105" E 31° 4' 29.182" N 公路存在多处弧形裂缝(2020年),走向266°,宽约3 cm,长约5 m,最深处约10 cm 滑坡
    P5 -164.861 110° 24' 5.021" E 31° 5' 2.746" N 公路前缘,橘树发育下挫裂缝,走向188°,长约8 m,最大下挫深度约0.5 m,呈直线型,缝宽1~2 cm,多级干砌石挡墙存在局部垮塌 滑坡
    P6 -106.729 110° 24' 43.590" E 31° 3' 20.615" N 道路存在裂缝,走向308°,宽约2 cm,地表下座0.5 m,东瀼口村9组38号,经调查为煤矿开采引起地面下沉 地面沉降
    P7 -176.093 110° 25' 32.555" E 31° 2' 8.815" N 变形区西侧为冲沟,坡度约50°,坡面存在大量松散堆积体;变形区东侧为道路切坡,坡高2~4 m 滑坡
    P8 -262.390 110° 27' 19.755" E 31° 3' 14.473" N 该处主要为农田及林地,表层土体结构松散 非地灾
    P9 -164.571 110° 26' 7.869" E 31° 1' 25.261" N 未见公路及斜坡变形裂缝,位于沿江处,考虑为水体对InSAR的影响 非地灾
    P10 -238.687 110° 24' 28.435" E 31° 1' 36.568" N 位于茶麻沟泥石流附近,为沿公路的林地 滑坡
    P11 -130.077 110° 27' 12.314" E 31° 1' 17.071" N 顺公路方向出现裂缝,宽1~2 mm,长约15 m,外沿开裂,斜坡较陡 滑坡
    P12 -123.997 110° 25' 5.682" E 31° 1' 30.042" N 位于红龙坪滑坡附近 滑坡
    P13 -130.387 110° 21' 18.590" E 31° 3' 4.134" N 位于已知隐患点附近,在长江南岸公路边坡,有锚杆治理护坡,可见变形监测墩 滑坡
    P14 -110.139 110° 18' 54.160" E 31° 3' 23.752" N 位于杜公祠滑坡附近 滑坡
    P15 -89.087 110° 21' 19.359" E 31° 3' 51.381" N 居民房前见裂缝,走向198°,长约12 m,宽1~5 m,房前地坪开裂,地坪前挡墙存在明显鼓胀变形和多条平行裂缝,公路内侧干砌石挡墙变形 滑坡
    P16 -150.895 110° 21' 50.151" E 31° 2' 11.801" N 公路内测有治理的高陡边坡,为已知隐患点 滑坡
    P17 -127.195 110° 23' 22.820" E 31° 3' 53.268" N 坡面种植橘树,坡度大,降雨时坡面汇水易使水土流失,坡面覆盖层为粉质黏土夹碎石 非地灾
    P18 -124.919 110° 20' 26.353" E 31° 3' 34.400" N 该点为太矶头集镇垃圾处理填埋场,由于填埋生活垃圾,局部挖填取土 非地灾
    P19 -106.789 110° 21' 11.969" E 31° 4' 18.647" N 现场为一施工工地,大量抗滑桩正在建设,地表土体有明显的施工开挖迹象,土层厚6~8 m。坐标点北侧房屋前于2020年4-5月发生滑移 滑坡
    下载: 导出CSV
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