基于SPH方法和LiDAR数据的滑坡模拟

N. Lukač, B. Žalik
{"title":"基于SPH方法和LiDAR数据的滑坡模拟","authors":"N. Lukač, B. Žalik","doi":"10.1109/ICESI.2019.8862991","DOIUrl":null,"url":null,"abstract":"In recent years, the amount of available remote sensing data such as LiDAR (Light Detection And Ranging) has increased immensely. This has enabled numerous new applications for analysing and studying different environmental phenomena. New environmental simulations have been developed, which also utilize high performance computing reachable in today's time. In this paper, a new environmental simulation is proposed that focuses on 3D landslides simulation by using surface topography from LiDAR data and SPH (Smoothed Particle Hydrodynamics), which is a well-established Lagrangian fluid simulation method. By transforming the surface data into regularly distributed particle type mesh, different particles can be augmented with surface-based properties. Classified surface data also provide a new way of representing obstacles (e.g. vegetation and buildings), and simulation boundary conditions that act differently on a landslide's velocity. The results of this paper demonstrate the applicability of dynamic boundary conditions when simulating landslides over vegetated areas based on classified LiDAR data.","PeriodicalId":249316,"journal":{"name":"2019 International Conference on Engineering, Science, and Industrial Applications (ICESI)","volume":"435 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Landslide simulation by using the SPH method and LiDAR data\",\"authors\":\"N. Lukač, B. Žalik\",\"doi\":\"10.1109/ICESI.2019.8862991\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In recent years, the amount of available remote sensing data such as LiDAR (Light Detection And Ranging) has increased immensely. This has enabled numerous new applications for analysing and studying different environmental phenomena. New environmental simulations have been developed, which also utilize high performance computing reachable in today's time. In this paper, a new environmental simulation is proposed that focuses on 3D landslides simulation by using surface topography from LiDAR data and SPH (Smoothed Particle Hydrodynamics), which is a well-established Lagrangian fluid simulation method. By transforming the surface data into regularly distributed particle type mesh, different particles can be augmented with surface-based properties. Classified surface data also provide a new way of representing obstacles (e.g. vegetation and buildings), and simulation boundary conditions that act differently on a landslide's velocity. The results of this paper demonstrate the applicability of dynamic boundary conditions when simulating landslides over vegetated areas based on classified LiDAR data.\",\"PeriodicalId\":249316,\"journal\":{\"name\":\"2019 International Conference on Engineering, Science, and Industrial Applications (ICESI)\",\"volume\":\"435 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Conference on Engineering, Science, and Industrial Applications (ICESI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICESI.2019.8862991\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Engineering, Science, and Industrial Applications (ICESI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICESI.2019.8862991","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

近年来,可用的遥感数据量,如激光雷达(光探测和测距)有了极大的增加。这为分析和研究不同的环境现象提供了许多新的应用。新的环境模拟已经开发出来,它也利用了当今时代可以达到的高性能计算。本文提出了一种新的环境模拟方法,利用LiDAR数据和SPH (Smoothed Particle Hydrodynamics,光滑粒子流体动力学)对三维滑坡进行模拟。通过将表面数据转换为规则分布的粒子类型网格,可以用基于表面的属性来增强不同的粒子。分类的地表数据还提供了一种表示障碍物(如植被和建筑物)的新方法,以及模拟对滑坡速度起不同作用的边界条件。本文的研究结果证明了动态边界条件在基于分类激光雷达数据模拟植被区滑坡时的适用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Landslide simulation by using the SPH method and LiDAR data
In recent years, the amount of available remote sensing data such as LiDAR (Light Detection And Ranging) has increased immensely. This has enabled numerous new applications for analysing and studying different environmental phenomena. New environmental simulations have been developed, which also utilize high performance computing reachable in today's time. In this paper, a new environmental simulation is proposed that focuses on 3D landslides simulation by using surface topography from LiDAR data and SPH (Smoothed Particle Hydrodynamics), which is a well-established Lagrangian fluid simulation method. By transforming the surface data into regularly distributed particle type mesh, different particles can be augmented with surface-based properties. Classified surface data also provide a new way of representing obstacles (e.g. vegetation and buildings), and simulation boundary conditions that act differently on a landslide's velocity. The results of this paper demonstrate the applicability of dynamic boundary conditions when simulating landslides over vegetated areas based on classified LiDAR data.
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:481959085
Book学术官方微信