[HTML][HTML] Landslide susceptibility map** using machine learning algorithms and comparison of their performance at Abha Basin, Asir Region, Saudi Arabia

AM Youssef, HR Pourghasemi - Geoscience Frontiers, 2021 - Elsevier
The current study aimed at evaluating the capabilities of seven advanced machine learning
techniques (MLTs), including, Support Vector Machine (SVM), Random Forest (RF) …

Prediction of the landslide susceptibility: Which algorithm, which precision?

HR Pourghasemi, O Rahmati - Catena, 2018 - Elsevier
Coupling machine learning algorithms with spatial analytical techniques for landslide
susceptibility modeling is a worth considering issue. So, the current research intend to …

A GIS-based landslide susceptibility map** and variable importance analysis using artificial intelligent training-based methods

P Zhao, Z Masoumi, M Kalantari, M Aflaki… - Remote Sensing, 2022 - mdpi.com
Landslides often cause significant casualties and economic losses, and therefore landslide
susceptibility map** (LSM) has become increasingly urgent and important. The potential …

[HTML][HTML] An investigation of the combined effect of rainfall and road cut on landsliding

S Pradhan, DG Toll, NJ Rosser, MJ Brain - Engineering Geology, 2022 - Elsevier
The reduction of soil suction and consequent loss of shear strength due to infiltration is
known to trigger shallow landslides during periods of concentrated rainfall. In the …

Assessment of landslide-prone areas and their zonation using logistic regression, logitboost, and naïvebayes machine-learning algorithms

HR Pourghasemi, A Gayen, S Park, CW Lee, S Lee - Sustainability, 2018 - mdpi.com
The occurrence of landslide in the hilly region of South Korea is a matter of serious concern.
This study tries to produce landslide susceptibility maps for Jumun** Country in South …

Rainfall-induced landslide susceptibility map** using machine learning algorithms and comparison of their performance in Hilly area of Fujian Province, China

P Ye, B Yu, W Chen, K Liu, L Ye - Natural Hazards, 2022 - Springer
The rainfall can contribute significantly to landslide events, especially in hilly areas. The
landslide susceptibility map (LSM) usually helps to mitigate disasters. However, how to …

Hybrid machine learning approach for landslide prediction, Uttarakhand, India

P Kainthura, N Sharma - Scientific reports, 2022 - nature.com
Natural disasters always have a damaging effect on our way of life. Landslides cause
serious damage to both human and natural resources around the world. In this paper, the …

Is the push-pull paradigm useful to explain rural-urban migration? A case study in Uttarakhand, India

EM Hoffmann, V Konerding, S Nautiyal, A Buerkert - PloS one, 2019 - journals.plos.org
The present study explored the motivation of rural-urban migrants who moved from the
Himalaya foothills of Uttarakhand to its capital city, Dehradun. A survey of 100 migrant …

Estimation of soil erosion and sediment yield concentration across the Kolleru Lake catchment using GIS

MK Kolli, C Opp, M Groll - Environmental Earth Sciences, 2021 - Springer
Flat lakes with a large catchment area are especially affected by sediment inputs. The
Kolleru Lake catchment (south-eastern India) with a surface area of approximately 6121 km …

Direct impacts of landslides on socio-economic systems: a case study from Aranayake, Sri Lanka

ENC Perera, DT Jayawardana, P Jayasinghe… - Geoenvironmental …, 2018 - Springer
Background Landslides area controversial issue worldwide and cause a wide range of
impacts on the socio-economic systems of the affected community. However, empirical …