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《地球科学与环境学报》[ISSN:1672-6561/CN:61-1423/P]

卷:

第45卷

期数:

2023年第03期

页码:

535-547

栏目:

大地测量、遥感与地学大数据

出版日期:

2023-05-15

文章信息/Info

Title:

Thickness Estimation of Xiongba Landslide in Gongjue Area of Tibet, China by Combining InSAR and Mass Conservation Method

文章编号:

1672-6561(2023)03-0535-13

作者:

朱 武¹; 2; 3; 杨璐瑶¹; 张金敏¹; 李振洪¹; 2; 3; 许炫宇¹

(1. 长安大学 地质工程与测绘学院,陕西 西安 710054; 2. 长安大学 自然资源部生态地质与灾害防控重点实验室,陕西 西安 710054; 3. 长安大学 地学与卫星大数据研究中心,陕西 西安 710054)

Author(s):

ZHU Wu¹; 2; 3;  YANG Lu-yao¹;  ZHANG Jin-min¹;  LI Zhen-hong¹; 2; 3;  XU Xuan-yu¹

(1. School of Geological Engineering and Geomatics, Chang'an University, Xi'an 710054, Shaanxi, China; 2. Key Laboratory of Ecological Geology and Disaster Prevention of Ministry of Natural Resources, Chang'an University, Xi'an 710054, Shaanxi, China; 3. Big Data Center for Geosciences and Satellites, Chang'an University, Xi'an 710054, Shaanxi, China)

关键词:

InSAR技术;  厚度反演;  质量守恒法;  三维形变场;  坡面坐标系;  空间几何参数;  流变参数;  雄巴滑坡

Keywords:

InSAR technology;  thickness inversion;  mass conservation method;  three-dimensional deformation field;  slope coordinate system;  spatial geometric parameter;  rheological parameter;  Xiongba landslide

分类号:

P237; P642.22

DOI:

10.19814/j.jese.2022.12081

文献标志码:

A

摘要:

滑坡厚度是灾害风险评估和防控的关键参数。传统的滑坡厚度估计方法只能确定滑坡体局部稀疏点的深度,无法反映整个坡体深度分布情况,且存在探测成本高、效率低等问题。基于此,提出了一种联合合成孔径雷达干涉测量(InSAR)和质量守恒法估计平移式滑坡厚度分布的方法,并将其应用于西藏贡觉地区雄巴滑坡。使用时序InSAR技术分别计算Sentinel-1A升轨、Sentinel-1A降轨和ALOS-2升轨影像的一维雷达视线向(LOS)形变速度场,联合SAR成像参数与滑坡空间几何关系构建坡面坐标系,解算得到滑坡沿坡面的三维形变场; 在此基础上,联合InSAR三维形变场和质量守恒准则估计滑坡厚度。实验共收集了覆盖雄巴滑坡的140景Sentinel-1A升轨、138景Sentinel-1A降轨和12景ALOS-2升轨数据。结果表明:雄巴滑坡总运动面积约为5.33 km²,当流变参数取值0.5时,滑坡厚度为0～109.57 m,集中分布在9～73 m,滑坡体积约3.12×10⁸ m³,估算结果与现场测量结果一致。本文提出的方法可以获取滑坡连续的厚度分布情况,可为灾害风险评估、分析与预防提供关键性数据支撑。

Abstract:

The landslide thickness is a key parameter for disaster risk assessment, prevention and control. The traditional landslide thickness estimation method can only determine the depth of the local sparse points of the slope, and can not reflect the depth distribution of the whole landslide, and has the problems of high detection cost and low efficiency. Based on this, a method to estimate the thickness distribution of translational landslide was proposed by combining InSAR and mass conservation method, and was applied to Xiongba landslide in Gongjue area of Tibet. The time-series InSAR technology was used to calculate the one-dimensional LOS deformation velocity fields of SAR images of Sentinel-1A ascending orbit and descending orbit, and ALOS-2 ascending orbit, and the slope coordinate system was constructed by combining the SAR imaging parameters and the spatial geometric relationship of the landslide, and the three-dimensional deformation field of the landslide along the slope was calculated. On this basis, the landslide thickness was estimated by combining InSAR three-dimensional deformation field and mass conservation criterion. The experiment collected 140 views of Sentinel-1A ascending orbit, 138 views of Sentinel-1A descending orbit and 12 views of ALOS-2 ascending orbit covering Xiongba landslide. The results show that the total movement area of Xiongba landslide is about 5.33 km²; when the rheological parameter is 0.5, the landslide thickness ranges from 0 to 109.57 m, distributes in 9 to 73 m, and the landslide volume is about 3.12×10⁸ m³, the estimated results are consistent with the field measurement results. The method proposed can obtain the continuous thickness distribution of landslides and provide key data support for disaster risk assessment, analysis and prevention.

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[1]张永红,刘冰,吴宏安,等.雄安新区2012~2016年地面沉降InSAR监测[J].地球科学与环境学报,2018,40(05):652.
　ZHANG Yong-hong,LIU Bing,WU Hong-an,et al.Ground Subsidence in Xiong’an New Area from 2012 to 2016 Monitored by InSAR Technique[J].Journal of Earth Sciences and Environment,2018,40(03):652.
[2]戴可人,吴明堂,卓冠晨,等.西南山区大型水电工程库岸滑坡InSAR早期识别与监测研究进展[J].地球科学与环境学报,2023,45(03):559.[doi:10.19814/j.jese.2022.12080]
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备注/Memo

备注/Memo:

收稿日期:2022-12-31; 修回日期:2023-02-23
基金项目:国家自然科学基金项目(41941019,42074040); 陕西省自然科学基础研究计划项目(2023-JC-JQ-24); 陕西省科技创新团队项目(2021TD-51); 陕西省地学大数据与地质灾害防治创新团队项目(2022)
作者简介:朱 武(1982-),男,陕西柞水人,教授,博士研究生导师,哲学博士,E-mail:zhuwu@chd.edu.cn。

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更新日期/Last Update: 2023-05-30