Landslide susceptibility evaluation in the Chemoga watershed, upper Blue Nile, Ethiopia

Desalegn, Hunegnaw; Mulu, Arega; Damtew, Banchiamlak

doi:10.1007/s11069-022-05338-3

Cited by 13 publications

(7 citation statements)

References 38 publications

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“…The proximity to streams is a significant factor for the landslide. The slopy land near the river serves as a marker for landslides and related soil erosional characteristics (Desalegn et al, 2022). Stream data was extracted from the Digital Elevation Model.…”

Section: Distance From Streamsmentioning

confidence: 99%

Geospatial Analysis of Landslide Susceptibility in Pulwama, Jammu and Kashmir: A Multi- Criteria Decision-Making Approach

Bose,

Behera

2024

Preprint

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Landslides poses serious threat to human and environment which involves sliding of rock, soil and debris down a hill. Creating a landslide susceptibility map is crucial for prevention, prediction and mitigation of these disasters. Pulwama district of Jammu & Kashmir faces significant risks due to its rugged topography, intense rainfall, and various anthropogenic activities. This study employs Multi Criteria Decision Making (MCDM) and Analytical Hierarchical Process (AHP), in Geographic Information System (GIS) to identify landslide susceptibility zones in Pulwama, Jammu & Kashmir. Ten factors such as elevation, slope, lithology, rainfall, soil, geology, geomorphology, and distance from lineament, streams, and vegetation cover are evaluated through pairwise comparisons using AHP. Weighted Overlay Analysis (WOA), a spatial analysis method has been applied in ArcGIS Pro to determine weights and is validated by consistency ratio calculation. This study identifies three zones: low, moderate, and high, with approximately one-quarter of the area primarily in northern & north-eastern parts being highly susceptible. Implementing strict mitigation measures, proper land use regulation, slope stabilization techniques, and afforestation is crucial to reduce the impact of landslides.

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Section: Distance From Streamsmentioning

confidence: 99%

Geospatial Analysis of Landslide Susceptibility in Pulwama, Jammu and Kashmir: A Multi- Criteria Decision-Making Approach

Bose,

Behera

2024

Preprint

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“…There are many water systems in the study area, and the rivers near the water systems have a strong erosion effect on the geotechnical body, which can easily lead to landslides. And the closer the water system is, the more serious the erosion is, so DTW (Figure 2m) and SPI (Figure 2f) [37,38] are included in the analysis. TWI (Figure 2e) is a physical indicator of the effect of regional topography on runoff direction and accumulation.…”

Section: Data Preparationmentioning

confidence: 99%

A Novel Heterogeneous Ensemble Framework Based on Machine Learning Models for Shallow Landslide Susceptibility Mapping

Tang,

Wang,

et al. 2023

Remote Sensing

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Landslides are devastating natural disasters that seriously threaten human life and property. Landslide susceptibility mapping (LSM) plays a key role in landslide hazard management. Machine learning (ML) models are widely used in LSM but suffer from limitations such as overfitting and unreliable accuracy. To improve the classification performance of a single machine learning (ML) model, this study selects logistic regression (LR), support vector machine (SVM), random forest (RF), and gradient boosting decision tree (GBDT), and proposes a novel heterogeneous ensemble framework based on Bayesian optimization (BO), namely, stratified weighted averaging (SWA), to test its applicability in a typical landslide area in Yanbian Prefecture, China. Firstly, a dataset consisting of 1531 historical landslides was collected from field investigations and historical records, and a spatial database containing 16 predisposing factors was established. The dataset was divided into a training set and a test set in a ratio of 7:3. The results showed that SWA effectively improved the Accuracy, AUC, and robustness of the model compared to a single ML model. The SWA achieved the best classification results (Accuracy = 91.39% and AUC = 0.967). To verify the generalization ability of SWA, we selected published landslide datasets from Yanshan country and Yongxin country in China for testing. SWA also performed well, with an AUC of 0.871 and 0.860, respectively. As indicated by shapely values (SVs), Normalized Difference Vegetation Index (NDVI) is the factor that has the greatest impact on landslide occurrence. The landslide susceptibility maps obtained from this study will provide an effective reference program for land use planning and disaster prevention and mitigation projects in Yanbian Prefecture, China.

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“…In this paper, the influence of site selection of transmission tower foundation and the risk assessment of geological disasters in transmission lines are studied. Some scholars have performed a series of work on geological disasters and their control measures in the investigation of transmission line engineering in mountainous areas, and regional geological disasters induced by earthquakes [16][17][18][19][20][21][22][23][24][25]. In western Sichuan, what is the impact of frequent geological disasters on the selection of sites for transmission projects, transmission line planning, and design?…”

Section: Introductionmentioning

confidence: 99%

Factors Controlling the Formation of Collapse Disasters and Its Hazards to Power Transmission Projects in Erlang Mountain – Zheduo Mountain, China

Ming,

Fan,

Fan

et al. 2024

Pol. J. Environ. Stud.

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This paper takes the collapse along the transmission corridor of The Deep -Cut Gorge Area of Dadu River in Erlangshan -Zheduo Mountain as the research object. The paper researches the characteristics of the development of the collapse disaster and the factors of the disaster. It is based on the remote sensing interpretation and the geological disaster investigation in the area. The results show that a total of 42 collapses were developed in the study area. The main controlling factors for the collapses in the area are topography, slope direction, geological structure, rock formation, annual rainfall, etc. The collapses were mainly developed in the area of rigid or relatively rigid rocks, and the rainfall was measured between 834-965 mm. There were 22 collapses in this area. The influence of the current collapse development along the transmission corridor in the Deep -Cut Gorge area of the Erlang Mountain -Zheduo Mountain Dadu River on the power transmission project is mainly to threaten the stability of the tower and its foundation. The research results provide a theoretical basis for the evaluation and prevention of geological disaster along the power transmission corridor. In addition, the results provide technical guidance for selecting lines, as well as for designing and constructing power transmission projects.

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Landslide susceptibility evaluation in the Chemoga watershed, upper Blue Nile, Ethiopia

Cited by 13 publications

References 38 publications

Geospatial Analysis of Landslide Susceptibility in Pulwama, Jammu and Kashmir: A Multi- Criteria Decision-Making Approach

Geospatial Analysis of Landslide Susceptibility in Pulwama, Jammu and Kashmir: A Multi- Criteria Decision-Making Approach

A Novel Heterogeneous Ensemble Framework Based on Machine Learning Models for Shallow Landslide Susceptibility Mapping

Factors Controlling the Formation of Collapse Disasters and Its Hazards to Power Transmission Projects in Erlang Mountain – Zheduo Mountain, China

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