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Landslide susceptibility assessment using the Weight of Evidence method: A case study in Xunyang area, China

PloS one, 2021-01, Vol.16 (1), p.e0245668 [Peer Reviewed Journal]

COPYRIGHT 2021 Public Library of Science ;COPYRIGHT 2021 Public Library of Science ;2021 Cao et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2021 Cao et al 2021 Cao et al ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0245668 ;PMID: 33493200

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Title:
Landslide susceptibility assessment using the Weight of Evidence method: A case study in Xunyang area, China
Author: Cao, Yanbo ; Wei, Xinsheng ; Fan, Wen ; Nan, Yalin ; Xiong, Wei ; Zhang, Shilin
Ribeiro da Silva, Claudionor
Subjects: Artificial intelligence ; Case studies ; Casualties ; China ; Design ; Earth Sciences ; Ecology and Environmental Sciences ; Economic impact ; Editing ; Engineering ; Engineering and Technology ; Environmental aspects ; Environmental risk ; Evaluation ; Extreme weather ; Funding ; Geological engineering ; Geological mapping ; Geology ; Laboratories ; Land use ; Landslide effects ; Landslides ; Landslides & mudslides ; Methods ; Mineral resources ; Mountains ; Neural networks ; Physical Sciences ; Rainfall ; Risk analysis ; Risk assessment ; Statistical analysis ; Statistical methods ; Susceptibility
Is Part Of: PloS one, 2021-01, Vol.16 (1), p.e0245668
Description: The aim of this study is to provide a landslide susceptibility map of the Xunyang District of a mountainous terrain, at the southern part of the Qin-Ba Mountain Region, which has been highly exposed to widely distributed shallow landslides over the past few decades. The Weight of Evidence (WoE) method was adopted in this research considering both the presence of a certain landslide causative factor class and the absence of remaining classes, which was used for determining a clearly spatial correlation between a landslide occurrence and the causative factors. Intrinsic factors, including geomorphological factors, geological factors, and river flow networks, and external factors of anthropogenic engineering activities in terms of density of road network were all considered and involved in the Geological Information System (GIS) environment for reconstructing the thematic layers of factor dataset. Significant assumptions prior to the analysis were emphasized to ensure conditional independence between each pair of factors for this bivariate statistical approach. In addition, a detailed landslide inventory map was constructed through field investigation and a remote sensing interpretation process at a scale of 1:50000. The thematic layers and landslide map were overlapped to obtain a spatial statistical relationship by using the frequency ratio method. At last, the validation process for the derived susceptibility map was conducted by applying the ROC curve, indicating that more than 90% of the landslides were in categories of high and moderate susceptibility zones. The causative factor classes, including the slope angles ranging from 20 to 40°, strong weathered and fractured strata, and road network density were identified to considerably influence the landslide distribution in the study area. The results have proven to be significantly meaningful for landslide hazard risk mitigation and land use management for the local authorities responsible for these fields.
Publisher: United States: Public Library of Science
Language: English
Identifier: ISSN: 1932-6203
EISSN: 1932-6203
DOI: 10.1371/journal.pone.0245668
PMID: 33493200
Source: Public Library of Science (PLoS) Journals Open Access
Geneva Foundation Free Medical Journals at publisher websites
PubMed Central
ProQuest Central
DOAJ Directory of Open Access Journals

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Landslide susceptibility assessment using the Weight of Evidence method: A case study in Xunyang area, China

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