Machine learning for landslides prevention: a survey
Landslides are one of the most critical categories of natural disasters worldwide and induce
severely destructive outcomes to human life and the overall economic system. To reduce its …
severely destructive outcomes to human life and the overall economic system. To reduce its …
Landslide mapping with remote sensing: challenges and opportunities
Landslide mapping is the primary step for landslide investigation and prevention. At present,
both the accuracy and the degree of automation of landslide mapping with remote sensing …
both the accuracy and the degree of automation of landslide mapping with remote sensing …
Evaluation of different machine learning methods and deep-learning convolutional neural networks for landslide detection
There is a growing demand for detailed and accurate landslide maps and inventories
around the globe, but particularly in hazard-prone regions such as the Himalayas. Most …
around the globe, but particularly in hazard-prone regions such as the Himalayas. Most …
Improved landslide assessment using support vector machine with bagging, boosting, and stacking ensemble machine learning framework in a mountainous …
Heavy rainfall in mountainous terrain can trigger numerous landslides in hill slopes. These
landslides can be deadly to the community living downslope with their fast pace, turning …
landslides can be deadly to the community living downslope with their fast pace, turning …
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 …
Evaluating scale effects of topographic variables in landslide susceptibility models using GIS-based machine learning techniques
The quality of digital elevation models (DEMs), as well as their spatial resolution, are
important issues in geomorphic studies. However, their influence on landslide susceptibility …
important issues in geomorphic studies. However, their influence on landslide susceptibility …
Different sampling strategies for predicting landslide susceptibilities are deemed less consequential with deep learning
Predictive capability of landslide susceptibilities is assumed to be varied with different
sampling techniques, such as (a) the landslide scarp centroid,(b) centroid of landslide …
sampling techniques, such as (a) the landslide scarp centroid,(b) centroid of landslide …
Landslide susceptibility assesssment in the Uttarakhand area (India) using GIS: a comparison study of prediction capability of naïve bayes, multilayer perceptron …
The objective of this study is to make a comparison of the prediction performance of three
techniques, Functional Trees (FT), Multilayer Perceptron Neural Networks (MLP Neural …
techniques, Functional Trees (FT), Multilayer Perceptron Neural Networks (MLP Neural …
Spatial prediction of landslide susceptibility using hybrid support vector regression (SVR) and the adaptive neuro-fuzzy inference system (ANFIS) with various …
Landslides are natural and sometimes quasi-natural hazards that are destructive to natural
resources and cause loss of human life every year. Hence, preparing susceptibility maps for …
resources and cause loss of human life every year. Hence, preparing susceptibility maps for …
Landslide detection using residual networks and the fusion of spectral and topographic information
Landslide inventories are in high demand for risk assessment of this natural hazard,
particularly in tropical mountainous regions. This research designed residual networks for …
particularly in tropical mountainous regions. This research designed residual networks for …