文献检索文档翻译深度研究
Suppr Zotero 插件Zotero 插件
邀请有礼套餐&价格历史记录

新学期,新优惠

限时优惠:9月1日-9月22日

30天高级会员仅需29元

1天体验卡首发特惠仅需5.99元

了解详情
不再提醒
插件&应用
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
高级版
套餐订阅购买积分包
AI 工具
文献检索文档翻译深度研究
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2025

Characterizing Surface Deformation of the Earthquake-Induced Daguangbao Landslide by Combining Satellite- and Ground-Based InSAR.

作者信息

Wang Xiaomeng, Zhang Wenjun, Cai Jialun, Wang Xiaowen, Wu Zhouhang, Fan Jing, Yao Yitong, Deng Binlin

机构信息

School of Environment and Resources, Southwest University of Science and Technology, Mianyang 621010, China.

Mianyang Science and Technology City Division, The National Remote Sensing Center of China, Mianyang 621010, China.

出版信息

Sensors (Basel). 2024 Dec 26;25(1):66. doi: 10.3390/s25010066.


DOI:10.3390/s25010066
PMID:39796857
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11722685/
Abstract

The Daguangbao landslide (DGBL), triggered by the 2008 Wenchuan earthquake, is a rare instance of super-giant landslides globally. The post-earthquake evolution of the DGBL has garnered significant attention in recent years; however, its deformation patterns remain poorly characterized owing to the complex local topography. In this study, we present the first observations of the surface dynamics of DGBL by integrating satellite- and ground-based InSAR data complemented by kinematic interpretation using a LiDAR-derived Digital Surface Model (DSM). The results indicate that the maximum line-of-sight (LOS) displacement velocity obtained from satellite InSAR is approximately 80.9 mm/year between 1 January 2021, and 30 December 2023, with downslope displacement velocities ranging from -60.5 mm/year to 69.5 mm/year. Ground-based SAR (GB-SAR) enhances satellite observations by detecting localized apparent deformation at the rear edge of the landslide, with LOS displacement velocities reaching up to 1.5 mm/h. Our analysis suggests that steep and rugged terrain, combined with fragile and densely jointed lithology, are the primary factors contributing to the ongoing deformation of the landslide. The findings of this study demonstrate the effectiveness of combining satellite- and ground-based InSAR systems, highlighting their complementary role in interpreting complex landslide deformations.

摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/57d5/11722685/0750873a3c9c/sensors-25-00066-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/57d5/11722685/b60e53de8fda/sensors-25-00066-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/57d5/11722685/4b1ce64ce115/sensors-25-00066-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/57d5/11722685/4e60f0a73ea3/sensors-25-00066-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/57d5/11722685/a27ded1578b4/sensors-25-00066-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/57d5/11722685/619cb1ceb5ee/sensors-25-00066-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/57d5/11722685/3c985e8e7d6a/sensors-25-00066-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/57d5/11722685/033d68f7bc11/sensors-25-00066-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/57d5/11722685/b899157af749/sensors-25-00066-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/57d5/11722685/f6147fba0492/sensors-25-00066-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/57d5/11722685/4ae3bc4fdc32/sensors-25-00066-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/57d5/11722685/bea9f19d3e9f/sensors-25-00066-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/57d5/11722685/0750873a3c9c/sensors-25-00066-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/57d5/11722685/b60e53de8fda/sensors-25-00066-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/57d5/11722685/4b1ce64ce115/sensors-25-00066-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/57d5/11722685/4e60f0a73ea3/sensors-25-00066-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/57d5/11722685/a27ded1578b4/sensors-25-00066-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/57d5/11722685/619cb1ceb5ee/sensors-25-00066-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/57d5/11722685/3c985e8e7d6a/sensors-25-00066-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/57d5/11722685/033d68f7bc11/sensors-25-00066-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/57d5/11722685/b899157af749/sensors-25-00066-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/57d5/11722685/f6147fba0492/sensors-25-00066-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/57d5/11722685/4ae3bc4fdc32/sensors-25-00066-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/57d5/11722685/bea9f19d3e9f/sensors-25-00066-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/57d5/11722685/0750873a3c9c/sensors-25-00066-g012.jpg

相似文献

[1]
Characterizing Surface Deformation of the Earthquake-Induced Daguangbao Landslide by Combining Satellite- and Ground-Based InSAR.

Sensors (Basel). 2024-12-26

[2]
Deformation Monitoring and Analysis of Baige Landslide (China) Based on the Fusion Monitoring of Multi-Orbit Time-Series InSAR Technology.

Sensors (Basel). 2024-10-21

[3]
Detection and analysis of potential landslides based on SBAS-InSAR technology in alpine canyon region.

Environ Sci Pollut Res Int. 2024-1

[4]
Landslide Monitoring along the Dadu River in Sichuan Based on Sentinel-1 Multi-Temporal InSAR.

Sensors (Basel). 2023-3-23

[5]
Landslide Susceptibility Mapping Using Machine Learning Algorithm Validated by Persistent Scatterer In-SAR Technique.

Sensors (Basel). 2022-4-19

[6]
EZ-InSAR: An easy-to-use open-source toolbox for mapping ground surface deformation using satellite interferometric synthetic aperture radar.

Earth Sci Inform. 2023

[7]
A Deep-Learning-Based Algorithm for Landslide Detection over Wide Areas Using InSAR Images Considering Topographic Features.

Sensors (Basel). 2024-7-15

[8]
Evolutionary analysis of slope direction deformation in the Gaojiawan landslide based on time-series InSAR and Kalman filtering.

PLoS One. 2024-12-31

[9]
Landslide Susceptibility Mapping with Integrated SBAS-InSAR Technique: A Case Study of Dongchuan District, Yunnan (China).

Sensors (Basel). 2022-7-26

[10]
Landslide detection and inventory updating using the time-series InSAR approach along the Karakoram Highway, Northern Pakistan.

Sci Rep. 2023-5-9

引用本文的文献

[1]
Application of the YOLOv11-seg algorithm for AI-based landslide detection and recognition.

Sci Rep. 2025-4-11

本文引用的文献

[1]
A modified Goldstein filter for interferogram denoising of interferometric imaging radar altimeter based on multiple quality-guided graphs.

PLoS One. 2024-8-8

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

推荐工具

医学文档翻译智能文献检索