[HTML][HTML] A review of statistically-based landslide susceptibility models
In this paper, we do a critical review of statistical methods for landslide susceptibility
modelling and associated terrain zonations. Landslide susceptibility is the likelihood of a …
modelling and associated terrain zonations. Landslide susceptibility is the likelihood of a …
[HTML][HTML] Geographical landslide early warning systems
The design, implementation, management, and verification of landslide early warning
systems (LEWSs) are gaining increasing attention in the literature and among government …
systems (LEWSs) are gaining increasing attention in the literature and among government …
Spatial modeling with R‐INLA: A review
Coming up with Bayesian models for spatial data is easy, but performing inference with them
can be challenging. Writing fast inference code for a complex spatial model with realistically …
can be challenging. Writing fast inference code for a complex spatial model with realistically …
[HTML][HTML] An updating of landslide susceptibility prediction from the perspective of space and time
Due to the similarity of conditioning factors, the aggregation feature of landslides and the
multi-temporal landslide inventory, the spatial and temporal effects of landslides need to be …
multi-temporal landslide inventory, the spatial and temporal effects of landslides need to be …
[HTML][HTML] Presenting logistic regression-based landslide susceptibility results
L Lombardo, PM Mai - Engineering geology, 2018 - Elsevier
A new work-flow is proposed to unify the way the community shares Logistic Regression
results for landslide susceptibility purposes. Although Logistic Regression models and …
results for landslide susceptibility purposes. Although Logistic Regression models and …
Decision tree based ensemble machine learning approaches for landslide susceptibility mapping
A Arabameri, S Chandra Pal, F Rezaie… - Geocarto …, 2022 - Taylor & Francis
The concept of leveraging the predictive capacity of predisposing factors for landslide
susceptibility (LS) modeling has been continuously improved in recent work focusing on …
susceptibility (LS) modeling has been continuously improved in recent work focusing on …
Assessment of the importance of gully erosion effective factors using Boruta algorithm and its spatial modeling and mapping using three machine learning algorithms
M Amiri, HR Pourghasemi, GA Ghanbarian, SF Afzali - Geoderma, 2019 - Elsevier
The Maharloo watershed has witnessed many gullies in the recent due to the specific topo-
climatic conditions and man-made activities in that area. The present study is set out to …
climatic conditions and man-made activities in that area. The present study is set out to …
GIS-based groundwater potential mapping in Shahroud plain, Iran. A comparison among statistical (bivariate and multivariate), data mining and MCDM approaches
In arid and semi-arid areas, groundwater resource is one of the most important water
sources by the humankind. Knowledge of groundwater distribution over space, associated …
sources by the humankind. Knowledge of groundwater distribution over space, associated …
Literature review and bibliometric analysis on data-driven assessment of landslide susceptibility
In recent decades, data-driven landslide susceptibility models (DdLSM), which are based on
statistical or machine learning approaches, have become popular to estimate the relative …
statistical or machine learning approaches, have become popular to estimate the relative …
[HTML][HTML] National-scale data-driven rainfall induced landslide susceptibility mapping for China by accounting for incomplete landslide data
China is one of the countries where landslides caused the most fatalities in the last decades.
The threat that landslide disasters pose to people might even be greater in the future, due to …
The threat that landslide disasters pose to people might even be greater in the future, due to …