[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 …
Review on landslide susceptibility mapping using support vector machines
Y Huang, L Zhao - Catena, 2018 - Elsevier
Landslides are natural phenomena that can cause great loss of life and damage to property.
A landslide susceptibility map is a useful tool to help with land management in landslide …
A landslide susceptibility map is a useful tool to help with land management in landslide …
[HTML][HTML] Landslide susceptibility mapping using hybrid random forest with GeoDetector and RFE for factor optimization
X Zhou, H Wen, Y Zhang, J Xu, W Zhang - Geoscience Frontiers, 2021 - Elsevier
The present study aims to develop two hybrid models to optimize the factors and enhance
the predictive ability of the landslide susceptibility models. For this, a landslide inventory …
the predictive ability of the landslide susceptibility models. For this, a landslide inventory …
Assessment of advanced random forest and decision tree algorithms for modeling rainfall-induced landslide susceptibility in the Izu-Oshima Volcanic Island, Japan
Landslides represent a part of the cascade of geological hazards in a wide range of geo-
environments. In this study, we aim to investigate and compare the performance of two state …
environments. In this study, we aim to investigate and compare the performance of two state …
Spatial cross-validation is not the right way to evaluate map accuracy
For decades scientists have produced maps of biological, ecological and environmental
variables. These studies commonly evaluate the map accuracy through cross-validation with …
variables. These studies commonly evaluate the map accuracy through cross-validation with …
Application of alternating decision tree with AdaBoost and bagging ensembles for landslide susceptibility mapping
Landslides are a common type of natural disaster that brings great threats to the human lives
and economic development around the world, especially in the Chinese Loess Plateau …
and economic development around the world, especially in the Chinese Loess Plateau …
Hyperparameter tuning and performance assessment of statistical and machine-learning algorithms using spatial data
While the application of machine-learning algorithms has been highly simplified in the last
years due to their well-documented integration in commonly used statistical programming …
years due to their well-documented integration in commonly used statistical programming …
[HTML][HTML] GIS-based landslide susceptibility modeling: A comparison between fuzzy multi-criteria and machine learning algorithms
Hazards and disasters have always negative impacts on the way of life. Landslide is an
overwhelming natural as well as man-made disaster that causes loss of natural resources …
overwhelming natural as well as man-made disaster that causes loss of natural resources …
Importance of spatial predictor variable selection in machine learning applications–Moving from data reproduction to spatial prediction
Abstract Machine learning algorithms find frequent application in spatial prediction of biotic
and abiotic environmental variables. However, the characteristics of spatial data, especially …
and abiotic environmental variables. However, the characteristics of spatial data, especially …
[HTML][HTML] Uncertainties of landslide susceptibility prediction considering different landslide types
Most literature related to landslide susceptibility prediction only considers a single type of
landslide, such as colluvial landslide, rock fall or debris flow, rather than different landslide …
landslide, such as colluvial landslide, rock fall or debris flow, rather than different landslide …