[HTML][HTML] Ensemble learning framework for landslide susceptibility mapping: Different basic classifier and ensemble strategy
The application of ensemble learning models has been continuously improved in recent
landslide susceptibility research, but most studies have no unified ensemble framework …
landslide susceptibility research, but most studies have no unified ensemble framework …
Landslide susceptibility prediction considering neighborhood characteristics of landslide spatial datasets and hydrological slope units using remote sensing and GIS …
Landslides are affected not only by their own environmental factors, but also by the
neighborhood environmental factors and the landslide clustering effect, which are …
neighborhood environmental factors and the landslide clustering effect, which are …
Hybrid ensemble machine learning approaches for landslide susceptibility mapping using different sampling ratios at East Sikkim Himalayan, India
Landslide is a big problem in the mountainous region all over the world. Sikkim Himalayan
region is also suffering from landslide problem. This study's main objective was to generate …
region is also suffering from landslide problem. This study's main objective was to generate …
Landslide susceptibility zonation using statistical and machine learning approaches in Northern Lecco, Italy
M Mehrabi - Natural Hazards, 2021 - Springer
This study deals with landslide susceptibility mapping in the northern part of Lecco Province,
Lombardy Region, Italy. In so doing, a valid landslide inventory map and thirteen …
Lombardy Region, Italy. In so doing, a valid landslide inventory map and thirteen …
Spatial modeling and susceptibility zonation of landslides using random forest, naïve bayes and K-nearest neighbor in a complicated terrain
SA Abu El-Magd, SA Ali, QB Pham - Earth Science Informatics, 2021 - Springer
Recently, one of the most frequent natural hazards around several regions in the world is the
landslide events. The area of Jabal Farasan in the northwest Jeddah of Saudi Arabia suffers …
landslide events. The area of Jabal Farasan in the northwest Jeddah of Saudi Arabia suffers …
Intelligent scanning for optimal rock discontinuity sets considering multiple parameters based on manifold learning combined with UAV photogrammetry
Y Liu, J Chen, C Tan, J Zhan, S Song, W Xu, J Yan… - Engineering …, 2022 - Elsevier
Abstract The Sichuan-Tibet railway, which spans many alpine canyon regions, is being built
in southwestern China. Investigating the characteristics of rock discontinuity sets is the basis …
in southwestern China. Investigating the characteristics of rock discontinuity sets is the basis …
Assessment of earthquake-induced landslide inventories and susceptibility maps using slope unit-based logistic regression and geospatial statistics
Inventories of seismically induced landslides provide essential information about the extent
and severity of ground effects after an earthquake. Rigorous assessment of the …
and severity of ground effects after an earthquake. Rigorous assessment of the …
[HTML][HTML] Uncertainties of landslide susceptibility prediction: Influences of different spatial resolutions, machine learning models and proportions of training and testing …
This study aims to reveal the impacts of three important uncertainty issues in landslide
susceptibility prediction (LSP), namely the spatial resolution, proportion of model training …
susceptibility prediction (LSP), namely the spatial resolution, proportion of model training …
Enhanced absence sampling technique for data-driven landslide susceptibility mapping: a case study in Songyang County, China
Accurate prediction of landslide susceptibility relies on effectively handling absence
samples in data-driven models. This study investigates the influence of different absence …
samples in data-driven models. This study investigates the influence of different absence …
Improved landslide susceptibility mapping using unsupervised and supervised collaborative machine learning models
Datasets containing recorded landslide and non-landslide samples can greatly influence the
performance of machine learning (ML) models, which are commonly used in landslide …
performance of machine learning (ML) models, which are commonly used in landslide …