Application Assessments of Using Scarp Boundary-Fitted, Volume Constrained, Smooth Minimal Surfaces as Failure Interfaces of Deep-Seated Landslides
More than 9,000 potential deep-seated landslide sites in the mountain ranges of Taiwan have been identified by a series of renewed governmental hazard mitigation initiatives after the 2009 Morakot typhoon. Among these sites, 186 sites have protection targets where thorough mitigation strategies are...
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Frontiers Media S.A.
2020-07-01
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Series: | Frontiers in Earth Science |
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Online Access: | https://www.frontiersin.org/article/10.3389/feart.2020.00211/full |
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author | Chih-Yu Kuo Pi-Wen Tsai Yih-Chin Tai Ya-Hsin Chan Rou-Fei Chen Ching-Weei Lin |
author_facet | Chih-Yu Kuo Pi-Wen Tsai Yih-Chin Tai Ya-Hsin Chan Rou-Fei Chen Ching-Weei Lin |
author_sort | Chih-Yu Kuo |
collection | DOAJ |
description | More than 9,000 potential deep-seated landslide sites in the mountain ranges of Taiwan have been identified by a series of renewed governmental hazard mitigation initiatives after the 2009 Morakot typhoon. Among these sites, 186 sites have protection targets where thorough mitigation strategies are to be implemented. One of the important tasks in the hazard mitigation initiative is to estimate the volume, failure interface and related quantities of each landslide site. In addition, with this number of sites, an automated tool is needed to generate predictions at low operational costs. We propose to use volume-constrained smooth minimal surfaces to approximate the landslide failure interfaces. A volume-constrained smooth minimal surface in the current context is defined as a differentiable surface that encloses a given landslide volume with the minimal surface area. Although the stratigraphy and geological structures are omitted, the smooth minimal surface method is verified with 24 known landslides and is shown to be able to generate acceptable, approximated failure interfaces. A collection of assessment indices is employed to measure the fitness of the predictions. Finally, the prediction fitness vs. the landslide scarp geometry is investigated. |
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issn | 2296-6463 |
language | English |
last_indexed | 2024-12-10T21:43:08Z |
publishDate | 2020-07-01 |
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spelling | doaj.art-cc675e83878e4c7cbd1d986f915b9ad92022-12-22T01:32:27ZengFrontiers Media S.A.Frontiers in Earth Science2296-64632020-07-01810.3389/feart.2020.00211537710Application Assessments of Using Scarp Boundary-Fitted, Volume Constrained, Smooth Minimal Surfaces as Failure Interfaces of Deep-Seated LandslidesChih-Yu Kuo0Pi-Wen Tsai1Yih-Chin Tai2Ya-Hsin Chan3Rou-Fei Chen4Ching-Weei Lin5Research Center for Applied Sciences, Academia Sinica, Taipei, TaiwanDepartment of Mathematics, National Taiwan Normal University, Taipei, TaiwanDepartment of Hydraulic and Ocean Engineering, National Cheng Kung University, Tainan, TaiwanResearch Center for Applied Sciences, Academia Sinica, Taipei, TaiwanDepartment of Geology, Chinese Culture University, Taipei, TaiwanDepartment of Earth Sciences, National Cheng Kung University, Tainan, TaiwanMore than 9,000 potential deep-seated landslide sites in the mountain ranges of Taiwan have been identified by a series of renewed governmental hazard mitigation initiatives after the 2009 Morakot typhoon. Among these sites, 186 sites have protection targets where thorough mitigation strategies are to be implemented. One of the important tasks in the hazard mitigation initiative is to estimate the volume, failure interface and related quantities of each landslide site. In addition, with this number of sites, an automated tool is needed to generate predictions at low operational costs. We propose to use volume-constrained smooth minimal surfaces to approximate the landslide failure interfaces. A volume-constrained smooth minimal surface in the current context is defined as a differentiable surface that encloses a given landslide volume with the minimal surface area. Although the stratigraphy and geological structures are omitted, the smooth minimal surface method is verified with 24 known landslides and is shown to be able to generate acceptable, approximated failure interfaces. A collection of assessment indices is employed to measure the fitness of the predictions. Finally, the prediction fitness vs. the landslide scarp geometry is investigated.https://www.frontiersin.org/article/10.3389/feart.2020.00211/fulldeep-seated landslidelandslide volume-area relationlandslide failure surface predictionFreeFem++ IpOPTfailure surface accuracy assessment |
spellingShingle | Chih-Yu Kuo Pi-Wen Tsai Yih-Chin Tai Ya-Hsin Chan Rou-Fei Chen Ching-Weei Lin Application Assessments of Using Scarp Boundary-Fitted, Volume Constrained, Smooth Minimal Surfaces as Failure Interfaces of Deep-Seated Landslides Frontiers in Earth Science deep-seated landslide landslide volume-area relation landslide failure surface prediction FreeFem++ IpOPT failure surface accuracy assessment |
title | Application Assessments of Using Scarp Boundary-Fitted, Volume Constrained, Smooth Minimal Surfaces as Failure Interfaces of Deep-Seated Landslides |
title_full | Application Assessments of Using Scarp Boundary-Fitted, Volume Constrained, Smooth Minimal Surfaces as Failure Interfaces of Deep-Seated Landslides |
title_fullStr | Application Assessments of Using Scarp Boundary-Fitted, Volume Constrained, Smooth Minimal Surfaces as Failure Interfaces of Deep-Seated Landslides |
title_full_unstemmed | Application Assessments of Using Scarp Boundary-Fitted, Volume Constrained, Smooth Minimal Surfaces as Failure Interfaces of Deep-Seated Landslides |
title_short | Application Assessments of Using Scarp Boundary-Fitted, Volume Constrained, Smooth Minimal Surfaces as Failure Interfaces of Deep-Seated Landslides |
title_sort | application assessments of using scarp boundary fitted volume constrained smooth minimal surfaces as failure interfaces of deep seated landslides |
topic | deep-seated landslide landslide volume-area relation landslide failure surface prediction FreeFem++ IpOPT failure surface accuracy assessment |
url | https://www.frontiersin.org/article/10.3389/feart.2020.00211/full |
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