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Refined Zoning of Landslide Susceptibility: A Case Study in Enshi County, Hubei, China
At present, landslide susceptibility assessment (LSA) based on the characteristics of landslides in different areas is an effective prevention measure for landslide management. In Enshi County, China, the landslides are mainly triggered by high-intensity rainfall, which causes a large number of casu...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9368755/ https://www.ncbi.nlm.nih.gov/pubmed/35954770 http://dx.doi.org/10.3390/ijerph19159412 |
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author | Wang, Zhiye Ma, Chuanming Qiu, Yang Xiong, Hanxiang Li, Minghong |
author_facet | Wang, Zhiye Ma, Chuanming Qiu, Yang Xiong, Hanxiang Li, Minghong |
author_sort | Wang, Zhiye |
collection | PubMed |
description | At present, landslide susceptibility assessment (LSA) based on the characteristics of landslides in different areas is an effective prevention measure for landslide management. In Enshi County, China, the landslides are mainly triggered by high-intensity rainfall, which causes a large number of casualties and economic losses every year. In order to effectively control the landslide occurrence in Enshi County and mitigate the damages caused by the landslide. In this study, eight indicators were selected as assessment indicators for LSA in Enshi County. The analytic hierarchy process (AHP) model, information value (IV) model and analytic hierarchy process-information value (AHP-IV) model were, respectively, applied to assess the landslide distribution of landslides in the rainy season (RS) and non-rainy season (NRS). Based on the three models, the study area was classified into five levels of landslide susceptibility, including very high susceptibility, high susceptibility, medium susceptibility, low susceptibility, and very low susceptibility. The receiver operating characteristic (ROC) curve was applied to verify the model accuracy. The results showed that the AHP-IV model (ROC = 0.7716) was more suitable in RS, and the IV model (ROC = 0.8237) was the most appropriate model in NRS. Finally, combined with the results of landslide susceptibility in RS and NRS, an integrated landslide susceptibility map was proposed, involving year-round high susceptibility, RS high susceptibility, NRS high susceptibility and year-round low susceptibility. The integrated landslide susceptibility results provide a more detailed division in terms of the different time periods in a year, which is beneficial for the government to efficiently allocate landslide management funds and propose effective landslide management strategies. Additionally, the focused arrangement of monitoring works in landslide-prone areas enable collect landslide information efficiently, which is helpful for the subsequent landslide preventive management. |
format | Online Article Text |
id | pubmed-9368755 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-93687552022-08-12 Refined Zoning of Landslide Susceptibility: A Case Study in Enshi County, Hubei, China Wang, Zhiye Ma, Chuanming Qiu, Yang Xiong, Hanxiang Li, Minghong Int J Environ Res Public Health Article At present, landslide susceptibility assessment (LSA) based on the characteristics of landslides in different areas is an effective prevention measure for landslide management. In Enshi County, China, the landslides are mainly triggered by high-intensity rainfall, which causes a large number of casualties and economic losses every year. In order to effectively control the landslide occurrence in Enshi County and mitigate the damages caused by the landslide. In this study, eight indicators were selected as assessment indicators for LSA in Enshi County. The analytic hierarchy process (AHP) model, information value (IV) model and analytic hierarchy process-information value (AHP-IV) model were, respectively, applied to assess the landslide distribution of landslides in the rainy season (RS) and non-rainy season (NRS). Based on the three models, the study area was classified into five levels of landslide susceptibility, including very high susceptibility, high susceptibility, medium susceptibility, low susceptibility, and very low susceptibility. The receiver operating characteristic (ROC) curve was applied to verify the model accuracy. The results showed that the AHP-IV model (ROC = 0.7716) was more suitable in RS, and the IV model (ROC = 0.8237) was the most appropriate model in NRS. Finally, combined with the results of landslide susceptibility in RS and NRS, an integrated landslide susceptibility map was proposed, involving year-round high susceptibility, RS high susceptibility, NRS high susceptibility and year-round low susceptibility. The integrated landslide susceptibility results provide a more detailed division in terms of the different time periods in a year, which is beneficial for the government to efficiently allocate landslide management funds and propose effective landslide management strategies. Additionally, the focused arrangement of monitoring works in landslide-prone areas enable collect landslide information efficiently, which is helpful for the subsequent landslide preventive management. MDPI 2022-08-01 /pmc/articles/PMC9368755/ /pubmed/35954770 http://dx.doi.org/10.3390/ijerph19159412 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Wang, Zhiye Ma, Chuanming Qiu, Yang Xiong, Hanxiang Li, Minghong Refined Zoning of Landslide Susceptibility: A Case Study in Enshi County, Hubei, China |
title | Refined Zoning of Landslide Susceptibility: A Case Study in Enshi County, Hubei, China |
title_full | Refined Zoning of Landslide Susceptibility: A Case Study in Enshi County, Hubei, China |
title_fullStr | Refined Zoning of Landslide Susceptibility: A Case Study in Enshi County, Hubei, China |
title_full_unstemmed | Refined Zoning of Landslide Susceptibility: A Case Study in Enshi County, Hubei, China |
title_short | Refined Zoning of Landslide Susceptibility: A Case Study in Enshi County, Hubei, China |
title_sort | refined zoning of landslide susceptibility: a case study in enshi county, hubei, china |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9368755/ https://www.ncbi.nlm.nih.gov/pubmed/35954770 http://dx.doi.org/10.3390/ijerph19159412 |
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