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Application of a GIS-Based Slope Unit Method for Landslide Susceptibility Mapping along the Longzi River, Southeastern Tibetan Plateau, China

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TLDR
The results show that the high and very high susceptibility areas are distributed throughout the vicinity of the river, with a large component in the north as well as a small portion in the middle and the south, and it is necessary to conduct landslide warnings in these areas.
Abstract
The Longzi River Basin in Tibet is located along the edge of the Himalaya Mountains and is characterized by complex geological conditions and numerous landslides. To evaluate the susceptibility of landslide disasters in this area, eight basic factors were analyzed comprehensively in order to obtain a final susceptibility map. The eight factors are the slope angle, slope aspect, plan curvature, distance-to-fault, distance-to-river, topographic relief, annual precipitation, and lithology. Except for the rainfall factor, which was extracted from the grid cell, all the factors were extracted and classified by the slope unit, which is the basic unit in geological disaster development. The eight factors were superimposed using the information content method (ICM), and the weight of each factor was acquired through an analytic hierarchy process (AHP). The sensitivities of the landslides were divided into four categories: low, moderate, high, and very high, respectively, accounting for 22.76%, 38.64%, 27.51%, and 11.09% of the study area. The accuracies of the area under AUC using slope units and grid cells are 82.6% and 84.2%, respectively, and it means that the two methods are accurate in predicting landslide occurrence. The results show that the high and very high susceptibility areas are distributed throughout the vicinity of the river, with a large component in the north as well as a small portion in the middle and the south. Therefore, it is necessary to conduct landslide warnings in these areas, where the rivers are vast and the population is dense. The susceptibility map can reflect the comprehensive risk of each slope unit, which provides an important reference for later detailed investigations, including research and warning studies.

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Citations
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Journal ArticleDOI

Landslide susceptibility mapping using hybrid random forest with GeoDetector and RFE for factor optimization

TL;DR: The ability of factor optimization methods to improve the performance of landslide susceptibility models is confirmed and the resultant hybrid models GeoDetector-RF and RFE-RF have high reliability and predictability.
Journal ArticleDOI

Is the ROC curve a reliable tool to compare the validity of landslide susceptibility maps

TL;DR: In this article, the receiver operating characteristic (ROC) curve is used for comparing the reliability of landslide susceptibility maps (LSMs) in a basin with a basin basin selection.
Journal ArticleDOI

Landslide Susceptibility Mapping Using Logistic Regression Analysis along the Jinsha River and Its Tributaries Close to Derong and Deqin County, Southwestern China

TL;DR: The objective of this study was to identify the areas that are most susceptible to landslide occurrence, and to find the key factors associated with landslides along Jinsha River and its tributaries close to Derong and Deqin County.
Journal ArticleDOI

A comparison of slope units and grid cells as mapping units for landslide susceptibility assessment

TL;DR: This paper compares the slope unit and grid cell as mapping unit for landslide susceptibility assessment and finds that landslide susceptibility mapping based on slope units performed better than grid cell-based method.
Journal ArticleDOI

Efficient and automatic extraction of slope units based on multi-scale segmentation method for landslide assessments

TL;DR: Wang et al. as discussed by the authors proposed an innovative multi-scale segmentation (MSS) method for extracting slope units, which can accurately and automatically extract the slope units for landslide assessments in hilly and mountainous areas and performs better than the conventional hydrological method.
References
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Journal ArticleDOI

GIS techniques and statistical models in evaluating landslide hazard

TL;DR: In this article, a small drainage basin located in Central Italy, relevant geological and geomorphological factors were collected and processed by applying GIS technology, which both generate high-fidelity digital terrain models and automatically partition the terrain into main slope-units.
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Spatial prediction models for shallow landslide hazards: a comparative assessment of the efficacy of support vector machines, artificial neural networks, kernel logistic regression, and logistic model tree

TL;DR: This study introduces a framework for training and validation of shallow landslide susceptibility models by using the latest statistical methods and demonstrates the benefit of selecting the optimal machine learning techniques with proper conditioning selection method in shallow landslide susceptible mapping.
Journal ArticleDOI

Landslide hazard mapping at Selangor, Malaysia using frequency ratio and logistic regression models

Saro Lee, +1 more
- 09 Feb 2007 - 
TL;DR: In this paper, the authors evaluated the landslide hazards at Selangor area, Malaysia, using Geographic Information System (GIS) and Remote Sensing (RS) using aerial photograph interpretation and field survey.
Journal ArticleDOI

Application of fuzzy logic and analytical hierarchy process (AHP) to landslide susceptibility mapping at Haraz watershed, Iran

TL;DR: In this paper, the authors used fuzzy logic and analytical hierarchy process (AHP) models to produce landslide susceptibility maps of a landslide-prone area (Haraz) in Iran.
Journal ArticleDOI

Estimating the quality of landslide susceptibility models

TL;DR: In this paper, a landslide susceptibility model for the Collazzone area, central Italy, was presented, and a framework for evaluating the model reliability and prediction skill was proposed to evaluate the model.
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