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Landslide susceptibility mapping in an area of underground mining using the multicriteria decision analysis method
Landslides are geomorphological phenomena that affect anthropogenic and natural features on the Earth’s surface. Many previous studies have identified several factors that have contributed to landslides. Among these factors are physical characteristics, such as slope, aspect, and land cover, of Eart...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6244970/ https://www.ncbi.nlm.nih.gov/pubmed/30430322 http://dx.doi.org/10.1007/s10661-018-7085-5 |
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author | Arca, Deniz Kutoğlu, Hakan Ş. Becek, Kazimierz |
author_facet | Arca, Deniz Kutoğlu, Hakan Ş. Becek, Kazimierz |
author_sort | Arca, Deniz |
collection | PubMed |
description | Landslides are geomorphological phenomena that affect anthropogenic and natural features on the Earth’s surface. Many previous studies have identified several factors that have contributed to landslides. Among these factors are physical characteristics, such as slope, aspect, and land cover, of Earth’s surface. Moreover, landslides can be triggered by human activities such as underground mining. This study aims to identify landslide susceptibility areas by analyzing landslide-related factors, including land subsidence triggered by underground mining. The area of interest was Kozlu, Turkey, where underground mining has been in progress for the past 100 years. Thus, to identify landslide risk zones, the multicriteria decision analysis method, together with the analytical hierarchy method, was used. The datasets included were topography, land cover, geological settings, and mining-induced land subsidence. The spatial extent of land subsidence was estimated using a previously published model. A landslide susceptibility map (LSM) was developed using a purposely developed GIS-based software. The results were compared with a terrain deformation map, which was developed in a separate study using the differential synthetic aperture radar interferometry (DInSAR) technique. The results showed a substantial correlation between the LSM and DInSAR map. Furthermore, it was found that ~ 88% of the very high and high landslide risk areas coincided with location of the past landslide events. These facts suggest that the algorithm and data sources used were sufficient to produce a sufficiently accurate LSM, which may be used for various purposes such as urban planning. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s10661-018-7085-5) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6244970 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-62449702018-12-04 Landslide susceptibility mapping in an area of underground mining using the multicriteria decision analysis method Arca, Deniz Kutoğlu, Hakan Ş. Becek, Kazimierz Environ Monit Assess Article Landslides are geomorphological phenomena that affect anthropogenic and natural features on the Earth’s surface. Many previous studies have identified several factors that have contributed to landslides. Among these factors are physical characteristics, such as slope, aspect, and land cover, of Earth’s surface. Moreover, landslides can be triggered by human activities such as underground mining. This study aims to identify landslide susceptibility areas by analyzing landslide-related factors, including land subsidence triggered by underground mining. The area of interest was Kozlu, Turkey, where underground mining has been in progress for the past 100 years. Thus, to identify landslide risk zones, the multicriteria decision analysis method, together with the analytical hierarchy method, was used. The datasets included were topography, land cover, geological settings, and mining-induced land subsidence. The spatial extent of land subsidence was estimated using a previously published model. A landslide susceptibility map (LSM) was developed using a purposely developed GIS-based software. The results were compared with a terrain deformation map, which was developed in a separate study using the differential synthetic aperture radar interferometry (DInSAR) technique. The results showed a substantial correlation between the LSM and DInSAR map. Furthermore, it was found that ~ 88% of the very high and high landslide risk areas coincided with location of the past landslide events. These facts suggest that the algorithm and data sources used were sufficient to produce a sufficiently accurate LSM, which may be used for various purposes such as urban planning. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s10661-018-7085-5) contains supplementary material, which is available to authorized users. Springer International Publishing 2018-11-14 2018 /pmc/articles/PMC6244970/ /pubmed/30430322 http://dx.doi.org/10.1007/s10661-018-7085-5 Text en © The Author(s) 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Article Arca, Deniz Kutoğlu, Hakan Ş. Becek, Kazimierz Landslide susceptibility mapping in an area of underground mining using the multicriteria decision analysis method |
title | Landslide susceptibility mapping in an area of underground mining using the multicriteria decision analysis method |
title_full | Landslide susceptibility mapping in an area of underground mining using the multicriteria decision analysis method |
title_fullStr | Landslide susceptibility mapping in an area of underground mining using the multicriteria decision analysis method |
title_full_unstemmed | Landslide susceptibility mapping in an area of underground mining using the multicriteria decision analysis method |
title_short | Landslide susceptibility mapping in an area of underground mining using the multicriteria decision analysis method |
title_sort | landslide susceptibility mapping in an area of underground mining using the multicriteria decision analysis method |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6244970/ https://www.ncbi.nlm.nih.gov/pubmed/30430322 http://dx.doi.org/10.1007/s10661-018-7085-5 |
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