Liquefaction within a bedding fault: Understanding the initiation and movement of the Daguangbao landslide triggered by the 2008 Wenchuan Earthquake (Ms = 8.0)
Shenghua Cui,Shenghua Cui,Xiangjun Pei,Yao Jiang,Gonghui Wang,Xuanmei Fan,Qingwen Yang,Runqiu Huang +7 more
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In this article, the authors examined whether the shear behavior of the bedding material could have favored the initiation and movement of the Daguangbao landslide, which was the most catastrophic mass movement triggered by the 2008 Wenchuan earthquake with a magnitude scale of 8.0.About:
This article is published in Engineering Geology.The article was published on 2021-12-20 and is currently open access. It has received 78 citations till now. The article focuses on the topics: Landslide & Fault (geology).read more
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Characterizing the spatial distribution, frequency, geomorphological and geological controls on landslides triggered by the 1933 Mw 7.3 Diexi Earthquake, Sichuan, China
TL;DR: Wang et al. as discussed by the authors presented a detailed landslide inventory map caused by the 1933 Mw 7.3 Diexi Earthquake through a multi-temporal inventory, field investigations, and the previous landslide inventory in the Diexi region (885 km2).
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Hydrochemical Characteristics and Groundwater Quality Assessment Using an Integrated Approach of the PCA, SOM, and Fuzzy c-Means Clustering: A Case Study in the Northern Sichuan Basin
TL;DR: In this paper , a combination of the SOM and FCM classifies neurons into two categories: the first category where NO2 − and NH4 + are most similar, perhaps as anthropogenic sources of pollution, which pose serious threats to human health; and the second category, where the total dissolved solids, Ca2+, Na+, Cl−, SO4 2, Mg2+, and K+ are more similar, explained as the influence of natural factors.
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Comparing Convolutional Neural Network and Machine Learning Models in Landslide Susceptibility Mapping: A Case Study in Wenchuan County
TL;DR: This research presented a model which was based on the CNN for LSM and methodically compare its capability with the traditional machine learning approaches, namely, support vector machine (SVM), logistic regression (LR), and random forest (RF).
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Landslide susceptibility assessment using statistical and machine learning techniques: A case study in the upper reaches of the Minjiang River, southwestern China
TL;DR: Wang et al. as discussed by the authors examined the landslides in the Minjiang catchment and aimed to compare the prediction ability of the statistical and machine learning (ML) models in landslide susceptibility assessment.
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Assessment of landslide susceptibility, exposure, vulnerability, and risk in shahpur valley, eastern hindu kush
Ghani Rahman,Alam Sher Bacha,Muhammad Farhan Ul Moazzam,Atta-ur-Rahman,Shakeel Mahmood,Hussein Almohamad,Ahmed Abdullah Al Dughairi,Motrih Al-Mutiry,Mona Alrasheedi,Hazem Ghassan Abdo +9 more
TL;DR: In this article , landslide susceptibility in Shahpur valley, situated in the eastern Hindu Kush, was assessed by applying "weight of evidence" (WoE) and "information value" (IV) models, which showed that the very high susceptible zone covered an area of 14.49% and 12.84% according to the WoE and IV models, respectively.
References
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Effects of Earthquakes on Dams and Embankments
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Lateral slab deformation and the origin of the western Mediterranean arcs
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