岩石和山体变形监测的创新方法

A. Hormes, Marc Adams, A. Amabile, Franz Blauensteiner, C. Demmler, C. Fey, M. Ostermann, C. Rechberger, T. Sausgruber, Filippo Vecchiotti, L. Vick, C. Zangerl
{"title":"岩石和山体变形监测的创新方法","authors":"A. Hormes, Marc Adams, A. Amabile, Franz Blauensteiner, C. Demmler, C. Fey, M. Ostermann, C. Rechberger, T. Sausgruber, Filippo Vecchiotti, L. Vick, C. Zangerl","doi":"10.1002/geot.201900074","DOIUrl":null,"url":null,"abstract":"Displacement rates of mountain slope deformations that can affect entire valley mountain flanks are often measured spatially distributed in‐situ without spatial significance. The spatially explicit measurement and recording of time series of slope deformations is a challenge, as the unstable slopes are often disintegrated into several subdomains, which move with different deformation rates. The current state‐of‐the‐art monitoring systems detect slow to very slow deformation rates between mm/a and several m/a. Using the examples of slope deformations in Saalbach‐Hinterglemm and the deep rock slide Marzellkamm in Austria this paper presents the results of terrestrial laser scans, extensometer measurements, Spaceborne InSAR data, unmanned Aerial System Photogrammetry (UAS‐P), and fixed‐point measurements. The different measurements complement each other and are optimally aligned for different application areas. InSAR data can help to identify hot spots on regional and local scale, while UAS‐P enables for spatially high level accuracy in the detection of subdomains moving at different speeds. For local warning systems TLS, extensometers and GBInSAR deliver higher accuracy.","PeriodicalId":170042,"journal":{"name":"Geomechanics and Tunnelling","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Innovative methods to monitor rock and mountain slope deformation\",\"authors\":\"A. Hormes, Marc Adams, A. Amabile, Franz Blauensteiner, C. Demmler, C. Fey, M. Ostermann, C. Rechberger, T. Sausgruber, Filippo Vecchiotti, L. Vick, C. Zangerl\",\"doi\":\"10.1002/geot.201900074\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Displacement rates of mountain slope deformations that can affect entire valley mountain flanks are often measured spatially distributed in‐situ without spatial significance. The spatially explicit measurement and recording of time series of slope deformations is a challenge, as the unstable slopes are often disintegrated into several subdomains, which move with different deformation rates. The current state‐of‐the‐art monitoring systems detect slow to very slow deformation rates between mm/a and several m/a. Using the examples of slope deformations in Saalbach‐Hinterglemm and the deep rock slide Marzellkamm in Austria this paper presents the results of terrestrial laser scans, extensometer measurements, Spaceborne InSAR data, unmanned Aerial System Photogrammetry (UAS‐P), and fixed‐point measurements. The different measurements complement each other and are optimally aligned for different application areas. InSAR data can help to identify hot spots on regional and local scale, while UAS‐P enables for spatially high level accuracy in the detection of subdomains moving at different speeds. For local warning systems TLS, extensometers and GBInSAR deliver higher accuracy.\",\"PeriodicalId\":170042,\"journal\":{\"name\":\"Geomechanics and Tunnelling\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Geomechanics and Tunnelling\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1002/geot.201900074\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geomechanics and Tunnelling","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/geot.201900074","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11

摘要

可以影响整个山谷山体侧翼的山体边坡变形的位移率通常是在空间上就地分布的,没有空间意义。边坡变形时间序列的空间显式测量和记录是一个挑战,因为不稳定的边坡经常分解成几个子域,这些子域以不同的变形速率运动。目前最先进的监测系统可以检测到毫米/a到几米/a之间的缓慢到非常缓慢的变形速率。本文以奥地利Saalbach‐hinterglmm和Marzellkamm的斜坡变形为例,介绍了地面激光扫描、延伸计测量、星载InSAR数据、无人机系统摄影测量(UAS‐P)和定点测量的结果。不同的测量值相互补充,并针对不同的应用领域进行最佳对齐。InSAR数据可以帮助识别区域和局部尺度的热点,而UAS‐P可以在检测以不同速度移动的子域时实现空间高水平的精度。对于本地预警系统,TLS,扩展计和GBInSAR提供更高的精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Innovative methods to monitor rock and mountain slope deformation
Displacement rates of mountain slope deformations that can affect entire valley mountain flanks are often measured spatially distributed in‐situ without spatial significance. The spatially explicit measurement and recording of time series of slope deformations is a challenge, as the unstable slopes are often disintegrated into several subdomains, which move with different deformation rates. The current state‐of‐the‐art monitoring systems detect slow to very slow deformation rates between mm/a and several m/a. Using the examples of slope deformations in Saalbach‐Hinterglemm and the deep rock slide Marzellkamm in Austria this paper presents the results of terrestrial laser scans, extensometer measurements, Spaceborne InSAR data, unmanned Aerial System Photogrammetry (UAS‐P), and fixed‐point measurements. The different measurements complement each other and are optimally aligned for different application areas. InSAR data can help to identify hot spots on regional and local scale, while UAS‐P enables for spatially high level accuracy in the detection of subdomains moving at different speeds. For local warning systems TLS, extensometers and GBInSAR deliver higher accuracy.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信