Geological and geotechnical investigations of the Sataun landslide along the Active Sirmauri Tal Fault, Sataun, Northwestern Himalaya, India

Thakur, Mahesh; Kumar, Neeraj; Dhiman, Raj Kiran; Malik, Javed N.

doi:10.1007/s10346-023-02038-2

Cited by 7 publications

(2 citation statements)

References 52 publications

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“…Landslides cause widespread damage to social and economic infrastructure, as well as to natural features (Sarro et al, 2018). They have indirect and direct in uence on major infrastructure, including human habitations, critically impacting land use change and rural to urban migration (Miura, 2019;Thakur et al, 2023). Landslide analysis commonly aims both to detect the failures, and to present the areas affected to generate inventories.…”

Section: Introductionmentioning

confidence: 99%

Detection of Sinkholes and Landslides in a Semi-Arid Environment Using Deep-Learning Methods, UAV images, and Topographical Derivatives

Kariminejad

Mondini

Hosseinalizadeh

et al. 2023

Preprint

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Sinkholes and landslides occur when parts of a soil collapse mainly in more gentle or steeper slopes respectively, both often triggered by intensive rainfall. These processes often cause problems in the hilly regions in the “Golestan province” of Iran, and their detection is the essential aim for this research. The production of soil landforms maps is typically based on visual interpretation of aerial and satellite images eventually supported by field surveys. Recent advances in the acquisition of images from “unmanned aerial vehicles (UAV)” and of “deep learning (DL)” methods inherited from computer vision have made it feasible to propose semi-automated soil landforms detection methodologies for large areas at an unprecedented spatial resolution. In this study, we evaluate the potential of two cutting-edge DL segmentation models, the vanilla “U-Net model” and the “Attention Deep Supervision Multi-Scale U-Net” model, applied to “UAV”-derived products, to map landslides and sinkholes in a semi-arid environment, the “Golestan Province” (north-east Iran) Results show that our framework can successfully map landslides in a challenging environment (with an F1-score of 69%), and that topographical derivates from “UAV-derived DSM” decrease the capacity of mapping sinkholes of the models calibrated with optical data.

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Section: Introductionmentioning

confidence: 99%

Detection of Sinkholes and Landslides in a Semi-Arid Environment Using Deep-Learning Methods, UAV images, and Topographical Derivatives

Kariminejad

Mondini

Hosseinalizadeh

et al. 2023

Preprint

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“…Among the geological factors that can be mentioned are the presence of incompetent lithology, fault zones, slopes with high critical angles, and seismic activity. In terms of anthropogenic factors, there are modifications of slope gradients, constructions on slopes, and vibrations produced by heavy traffic [19]. Furthermore, a combination of factors, such as dense urban development, mountainous terrain, and intense seasonal rainfall, has led to serious landslide issues [20].…”

Section: Introductionmentioning

confidence: 99%

Geotechnical Characterization of Quito’s North-Central Zone as Applied to Deep Excavation in the Urban Setting

et al. 2023

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This paper describes an in-depth soil characterization study in the La Carolina financial district of Quito (Ecuador). As there was very little information available on the geotechnical structure of Quito’s volcanic soil, particularly in this area, where large-scale property development has taken place, the aim was to provide information on soil parameters to engineers working on large geotechnical and civil engineering projects based on the results of a thorough and comprehensive study of such properties. A series of field tests were performed at three different sites, where thin-walled tube samples were collected for lab testing to estimate the index properties and mechanical parameters. These index properties were then combined with conventional two-way drainage oedometer tests and stress-path triaxial testing to evaluate compressibility, stiffness and strength. The subsoil was found to be partly composed of slightly overconsolidated volcanic soils. X-ray Diffraction (XRD) and Scanning Electron Microscopy (SEM) analyses were also conducted to determine mineralogical and microstructural features and evaluate their influence on the mechanical behavior of the volcanic soil. This type of research is frequently applied to the study of landslides in urban environments, where it is essential to understand their failure mechanisms, especially in slopes generated by the construction of important engineering works. Therefore, based on this geotechnical characterization study, parameters were subsequently determined for the Mohr–Coulomb (MC), Hardening Soil (HS), and Hardening Soil with Small-Strain Stiffness (HSsmall) soil constitutive models, and these were applied to a numerical study of the Soil Nailing system behavior for the construction of a five-level underground car parking structure of an important building located in the north-central sector of the city of Quito. It was verified that the HSsmall and HS constitutive soil models better reproduce the behavior of this type of structure. Finally, the multiple geotechnical parameters determined in this study significantly contribute to the analysis of these structures in this soil type.

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Correlating Circular Failure Charts, Limit Equilibrium and Finite Element Method Based Safety Factor for Circular Failure Type Landslides

Varshney,

Siddique,

Ahamad

et al. 2024

Advances in Natural and Technological Hazards Research

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Geological and geotechnical investigations of the Sataun landslide along the Active Sirmauri Tal Fault, Sataun, Northwestern Himalaya, India

Cited by 7 publications

References 52 publications

Detection of Sinkholes and Landslides in a Semi-Arid Environment Using Deep-Learning Methods, UAV images, and Topographical Derivatives

Detection of Sinkholes and Landslides in a Semi-Arid Environment Using Deep-Learning Methods, UAV images, and Topographical Derivatives

Geotechnical Characterization of Quito’s North-Central Zone as Applied to Deep Excavation in the Urban Setting

Correlating Circular Failure Charts, Limit Equilibrium and Finite Element Method Based Safety Factor for Circular Failure Type Landslides

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