Assessing loess landslide volume using high-precision UAV-derived DEM: A case study of the 15 March 2019 landslide in Zaoling Township, Xiangning County in North China

Peng Du , Yueren Xu , Yali Guo , Haofeng Li
{"title":"Assessing loess landslide volume using high-precision UAV-derived DEM: A case study of the 15 March 2019 landslide in Zaoling Township, Xiangning County in North China","authors":"Peng Du ,&nbsp;Yueren Xu ,&nbsp;Yali Guo ,&nbsp;Haofeng Li","doi":"10.1016/j.nhres.2023.07.006","DOIUrl":null,"url":null,"abstract":"<div><div>Landslides pose significant hazards on China's Loess Plateau, potentially resulting in catastrophic consequences for human life and property. A prompt assessment of landslide disasters is crucial in providing scientific decision support for post-disaster relief efforts and serves as a fundamental basis for risk assessment of secondary disasters such as debris flow. On March 15, 2019, a loess landslide occurred in Zaoling Town, Xiangning County, Shanxi Province. This event led to the collapse of three buildings, resulting in 20 fatalities and 13 injuries. Subsequently, high-resolution orthophotos and an unmanned aerial vehicle-derived digital elevation model (UAV-DEM) of the landslide area were obtained through photogrammetry. By analyzing the shape of the exposed main scarp of the landslide in the 0.2 ​m UAV-DEM and the softened layer, this study successfully identified an unexposed underground sliding surface. Through further analysis of the shape of the exposed main scarp of the landslide in the 0.2 ​m UAV-DEM and the softened layer, this study accurately reconstructed the unexposed underground sliding surface. To reconstruct the pre-landslide digital elevation model (DEM), Google Earth images depicting the pre-landslide terrain features were utilized. The volume of each component of the landslide was then calculated using the pre-, post- DEM, and the sliding surface. The calculation results reveal that volume of the landslide is about 54,000 ​m<sup>3</sup>, the expansion rate was determined to be 13.9%.</div></div>","PeriodicalId":100943,"journal":{"name":"Natural Hazards Research","volume":"3 4","pages":"Pages 640-645"},"PeriodicalIF":0.0000,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Natural Hazards Research","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666592123000756","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Landslides pose significant hazards on China's Loess Plateau, potentially resulting in catastrophic consequences for human life and property. A prompt assessment of landslide disasters is crucial in providing scientific decision support for post-disaster relief efforts and serves as a fundamental basis for risk assessment of secondary disasters such as debris flow. On March 15, 2019, a loess landslide occurred in Zaoling Town, Xiangning County, Shanxi Province. This event led to the collapse of three buildings, resulting in 20 fatalities and 13 injuries. Subsequently, high-resolution orthophotos and an unmanned aerial vehicle-derived digital elevation model (UAV-DEM) of the landslide area were obtained through photogrammetry. By analyzing the shape of the exposed main scarp of the landslide in the 0.2 ​m UAV-DEM and the softened layer, this study successfully identified an unexposed underground sliding surface. Through further analysis of the shape of the exposed main scarp of the landslide in the 0.2 ​m UAV-DEM and the softened layer, this study accurately reconstructed the unexposed underground sliding surface. To reconstruct the pre-landslide digital elevation model (DEM), Google Earth images depicting the pre-landslide terrain features were utilized. The volume of each component of the landslide was then calculated using the pre-, post- DEM, and the sliding surface. The calculation results reveal that volume of the landslide is about 54,000 ​m3, the expansion rate was determined to be 13.9%.
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
基于高精度无人机DEM的黄土滑坡体积评估——以2019年3月15日湘宁县早岭乡滑坡为例
山体滑坡对中国黄土高原造成重大危害,可能对人类生命财产造成灾难性后果。滑坡灾害的及时评估对于为灾后救援工作提供科学决策支持至关重要,也是泥石流等次生灾害风险评估的基础。2019年3月15日,山西省香宁县早岭镇发生黄土滑坡。这一事件导致三座建筑物倒塌,造成20人死亡,13人受伤。随后,通过摄影测量获得滑坡区域的高分辨率正射影像图和无人机衍生数字高程模型(UAV-DEM)。通过分析0.2 m无人机- dem中滑坡裸露的主陡坡和软化层的形态,成功识别出未暴露的地下滑动面。通过进一步分析0.2 m无人机- dem中滑坡裸露的主陡坡形态和软化层,准确重建了未暴露的地下滑动面。为了重建滑坡前的数字高程模型(DEM),利用谷歌地球图像描绘滑坡前的地形特征。然后利用预DEM、后DEM和滑动面计算滑坡各分量的体积。计算结果表明,滑坡体积约为5.4万m3,膨胀率为13.9%。
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
4.10
自引率
0.00%
发文量
0
期刊最新文献
Report on the 2024 annual academic conference of the committee on earthquake hazard chain, Seismological Society of China,6–9 December 2024, Shanghai, China Assessment of three satellite precipitation products for hydrological studies in a data-scarce context: Ouarzazate basin, southern Morocco Geometry and late Quaternary slip rate of the Tuolai Shan-Hala Hu segment of the Haiyuan fault, northeastern Tibetan Plateau Exploring the dynamics of extreme rainfall in the Cauvery river basin, Southern India: Spatio-temporal insights and adaptive strategies Assessing coastal exposure to Sea Level Rise: A coupled approach of qualitative modeling and spatial autocorrelation analysis
×
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:604180095
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