Ground Investigations and Detection and Monitoring of Landslides Using SAR Interferometry in Gangtok, Sikkim Himalaya

IF 6.5 3区 工程技术 Q1 ENGINEERING, GEOLOGICAL Georisk-Assessment and Management of Risk for Engineered Systems and Geohazards Pub Date : 2023-01-13 DOI:10.3390/geohazards4010003
R. Bhasin, Gokhan Aslan, J. Dehls
{"title":"Ground Investigations and Detection and Monitoring of Landslides Using SAR Interferometry in Gangtok, Sikkim Himalaya","authors":"R. Bhasin, Gokhan Aslan, J. Dehls","doi":"10.3390/geohazards4010003","DOIUrl":null,"url":null,"abstract":"The Himalayan state of Sikkim is prone to some of the world’s largest landslides, which have caused catastrophic damage to lives, properties, and infrastructures in the region. The settlements along the steep valley sides are particularly subject to frequent rainfall-triggered landslide events during the monsoon season. The region has also experienced smaller rock slope failures (RSF) after the 2011 Sikkim earthquake. The surface displacement field is a critical observable for determining landslide depth and constraining failure mechanisms to develop effective mitigation techniques that minimise landslide damage. In the present study, the persistent scatterers InSAR (PSI) method is employed to process the series of Sentinel 1-A/B synthetic aperture radar (SAR) images acquired between 2015 and 2021 along ascending and descending orbits for the selected areas in Gangtok, Sikkim, to detect potentially active, landslide-prone areas. InSAR-derived ground surface displacements and their spatio-temporal evolutions are combined with field investigations to better understand the state of activity and landslide risk assessment. Field investigations confirm the ongoing ground surface displacements revealed by the InSAR results. Some urban areas have been completely abandoned due to the structural damage to residential housing, schools, and office buildings caused by displacement. This paper relates the geotechnical investigations carried out on the ground to the data obtained through interferometric synthetic aperture radar (InSAR), focusing on the triggering mechanisms. A strong correlation between seasonal rainfall and landslide acceleration, as well as predisposing geological-structural setting, suggest a causative mechanism of the landslides.","PeriodicalId":48524,"journal":{"name":"Georisk-Assessment and Management of Risk for Engineered Systems and Geohazards","volume":null,"pages":null},"PeriodicalIF":6.5000,"publicationDate":"2023-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Georisk-Assessment and Management of Risk for Engineered Systems and Geohazards","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.3390/geohazards4010003","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, GEOLOGICAL","Score":null,"Total":0}
引用次数: 2

Abstract

The Himalayan state of Sikkim is prone to some of the world’s largest landslides, which have caused catastrophic damage to lives, properties, and infrastructures in the region. The settlements along the steep valley sides are particularly subject to frequent rainfall-triggered landslide events during the monsoon season. The region has also experienced smaller rock slope failures (RSF) after the 2011 Sikkim earthquake. The surface displacement field is a critical observable for determining landslide depth and constraining failure mechanisms to develop effective mitigation techniques that minimise landslide damage. In the present study, the persistent scatterers InSAR (PSI) method is employed to process the series of Sentinel 1-A/B synthetic aperture radar (SAR) images acquired between 2015 and 2021 along ascending and descending orbits for the selected areas in Gangtok, Sikkim, to detect potentially active, landslide-prone areas. InSAR-derived ground surface displacements and their spatio-temporal evolutions are combined with field investigations to better understand the state of activity and landslide risk assessment. Field investigations confirm the ongoing ground surface displacements revealed by the InSAR results. Some urban areas have been completely abandoned due to the structural damage to residential housing, schools, and office buildings caused by displacement. This paper relates the geotechnical investigations carried out on the ground to the data obtained through interferometric synthetic aperture radar (InSAR), focusing on the triggering mechanisms. A strong correlation between seasonal rainfall and landslide acceleration, as well as predisposing geological-structural setting, suggest a causative mechanism of the landslides.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
锡金-喜马拉雅地区甘托克滑坡的地面调查与SAR干涉检测与监测
喜马拉雅地区的锡金邦是世界上最严重的山体滑坡的多发地区,这些山体滑坡对该地区的生命、财产和基础设施造成了灾难性的破坏。在季风季节,沿着陡峭山谷的定居点特别容易受到降雨引发的山体滑坡事件的影响。该地区在2011年锡金地震后也经历了较小的岩石边坡破坏(RSF)。地表位移场是确定滑坡深度和约束破坏机制的关键观测数据,有助于开发有效的缓解技术,最大限度地减少滑坡损害。在本研究中,采用持续散射体InSAR (PSI)方法对2015年至2021年间在锡金Gangtok选定地区沿上升和下降轨道获取的Sentinel 1-A/B合成孔径雷达(SAR)图像进行处理,以检测潜在活跃的滑坡易发区域。insar反演的地表位移及其时空演变与现场调查相结合,以更好地了解活动状态和滑坡风险评估。现场调查证实了InSAR结果所揭示的持续的地表位移。由于居民住宅、学校和办公楼的结构被破坏,一些城市地区已经完全被遗弃。本文将在地面进行的岩土工程调查与干涉合成孔径雷达(InSAR)获得的数据联系起来,重点讨论了触发机制。季节性降雨与滑坡加速之间的强相关性以及易诱发的地质构造环境提示了滑坡的成因机制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
CiteScore
8.70
自引率
10.40%
发文量
31
期刊介绍: Georisk covers many diversified but interlinked areas of active research and practice, such as geohazards (earthquakes, landslides, avalanches, rockfalls, tsunamis, etc.), safety of engineered systems (dams, buildings, offshore structures, lifelines, etc.), environmental risk, seismic risk, reliability-based design and code calibration, geostatistics, decision analyses, structural reliability, maintenance and life cycle performance, risk and vulnerability, hazard mapping, loss assessment (economic, social, environmental, etc.), GIS databases, remote sensing, and many other related disciplines. The underlying theme is that uncertainties associated with geomaterials (soils, rocks), geologic processes, and possible subsequent treatments, are usually large and complex and these uncertainties play an indispensable role in the risk assessment and management of engineered and natural systems. Significant theoretical and practical challenges remain on quantifying these uncertainties and developing defensible risk management methodologies that are acceptable to decision makers and stakeholders. Many opportunities to leverage on the rapid advancement in Bayesian analysis, machine learning, artificial intelligence, and other data-driven methods also exist, which can greatly enhance our decision-making abilities. The basic goal of this international peer-reviewed journal is to provide a multi-disciplinary scientific forum for cross fertilization of ideas between interested parties working on various aspects of georisk to advance the state-of-the-art and the state-of-the-practice.
期刊最新文献
Evaluating the Impact of Engineering Works in Megatidal Areas Using Satellite Images—Case of the Mont-Saint-Michel Bay, France Assessment of a Machine Learning Algorithm Using Web Images for Flood Detection and Water Level Estimates Digital geotechnics: from data-driven site characterisation towards digital transformation and intelligence in geotechnical engineering Induced Seismicity Hazard Assessment for a Potential CO2 Storage Site in the Southern San Joaquin Basin, CA Novel evaluation methodology for mechanical behaviour and instability risk of roof structure using limited investigation data
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1