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Formation of the 2015 Shenzhen landslide as observed by SAR shape-from-shading
The time-series topography change of a landfill site before its failure has rarely been surveyed in detail. However, this information is important for both landfill management and early warning of landslides. Here, we take the 2015 Shenzhen landslide as an example, and we use the radar shape-from-sh...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5335704/ https://www.ncbi.nlm.nih.gov/pubmed/28256522 http://dx.doi.org/10.1038/srep43351 |
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author | Wang, Chisheng Li, Qingquan Zhu, Jiasong Gao, Wei Shan, Xinjian Song, Jun Ding, Xiaoli |
author_facet | Wang, Chisheng Li, Qingquan Zhu, Jiasong Gao, Wei Shan, Xinjian Song, Jun Ding, Xiaoli |
author_sort | Wang, Chisheng |
collection | PubMed |
description | The time-series topography change of a landfill site before its failure has rarely been surveyed in detail. However, this information is important for both landfill management and early warning of landslides. Here, we take the 2015 Shenzhen landslide as an example, and we use the radar shape-from-shading (SFS) technique to retrieve time-series digital elevation models of the landfill. The results suggest that the total filling volume reached 4,074,300 m(3) in the one and a half years before the landslide, while 2,817,400 m(3) slid down in the accident. Meanwhile, the landfill rate in most areas exceeded 2 m/month, which is the empirical upper threshold in landfill engineering. Using topography captured on December 12, 2015, the slope safety analysis gives a factor of safety of 0.932, suggesting that this slope was already hazardous before the landslide. We conclude that the synthetic aperture radar (SAR) SFS technique has the potential to contribute to landfill failure monitoring. |
format | Online Article Text |
id | pubmed-5335704 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-53357042017-03-07 Formation of the 2015 Shenzhen landslide as observed by SAR shape-from-shading Wang, Chisheng Li, Qingquan Zhu, Jiasong Gao, Wei Shan, Xinjian Song, Jun Ding, Xiaoli Sci Rep Article The time-series topography change of a landfill site before its failure has rarely been surveyed in detail. However, this information is important for both landfill management and early warning of landslides. Here, we take the 2015 Shenzhen landslide as an example, and we use the radar shape-from-shading (SFS) technique to retrieve time-series digital elevation models of the landfill. The results suggest that the total filling volume reached 4,074,300 m(3) in the one and a half years before the landslide, while 2,817,400 m(3) slid down in the accident. Meanwhile, the landfill rate in most areas exceeded 2 m/month, which is the empirical upper threshold in landfill engineering. Using topography captured on December 12, 2015, the slope safety analysis gives a factor of safety of 0.932, suggesting that this slope was already hazardous before the landslide. We conclude that the synthetic aperture radar (SAR) SFS technique has the potential to contribute to landfill failure monitoring. Nature Publishing Group 2017-03-03 /pmc/articles/PMC5335704/ /pubmed/28256522 http://dx.doi.org/10.1038/srep43351 Text en Copyright © 2017, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Wang, Chisheng Li, Qingquan Zhu, Jiasong Gao, Wei Shan, Xinjian Song, Jun Ding, Xiaoli Formation of the 2015 Shenzhen landslide as observed by SAR shape-from-shading |
title | Formation of the 2015 Shenzhen landslide as observed by SAR shape-from-shading |
title_full | Formation of the 2015 Shenzhen landslide as observed by SAR shape-from-shading |
title_fullStr | Formation of the 2015 Shenzhen landslide as observed by SAR shape-from-shading |
title_full_unstemmed | Formation of the 2015 Shenzhen landslide as observed by SAR shape-from-shading |
title_short | Formation of the 2015 Shenzhen landslide as observed by SAR shape-from-shading |
title_sort | formation of the 2015 shenzhen landslide as observed by sar shape-from-shading |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5335704/ https://www.ncbi.nlm.nih.gov/pubmed/28256522 http://dx.doi.org/10.1038/srep43351 |
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