Machine learning for landslides prevention: a survey (2020-06-24T00:00:00.000000Z)

TL;DR

A comprehensive survey of relevant research on machine learning applied in landslides prevention is presented, mainly focusing on landslides detection based on images, landslides susceptibility assessment, and the development of landslide warning systems.

Abstract

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 negative effects, landslides prevention has become an urgent task, which includes investigating landslide-related information and predicting potential landslides. Machine learning is a state-of-the-art analytics tool that has been widely used in landslides prevention. This paper presents a comprehensive survey of relevant research on machine learning applied in landslides prevention, mainly focusing on (1) landslides detection based on images, (2) landslides susceptibility assessment, and (3) the development of landslide warning systems. Moreover, this paper discusses the current challenges and potential opportunities in the application of machine learning algorithms for landslides prevention.

Authors

F. Piccialli

2 papers

Zhengjing Ma

1 papers

Gang Mei

1 papers

References215 items

High-field superconductivity in C-doped MgB2 bulk samples prepared by a rapid synthesis route

A Survey of Internet of Things (IoT) for Geohazard Prevention: Applications, Technologies, and Challenges

Comparative study of landslide susceptibility mapping with different recurrent neural networks

Mapping landslide susceptibility at the Three Gorges Reservoir, China, using gradient boosting decision tree, random forest and information value models

TL;DR

Abstract

Authors

References215 items

High-field superconductivity in C-doped MgB2 bulk samples prepared by a rapid synthesis route

A Survey of Internet of Things (IoT) for Geohazard Prevention: Applications, Technologies, and Challenges

Comparative study of landslide susceptibility mapping with different recurrent neural networks

Mapping landslide susceptibility at the Three Gorges Reservoir, China, using gradient boosting decision tree, random forest and information value models

Recent advances in deep learning

Convolutional Neural Network—Optimized Moth Flame Algorithm for Shallow Landslide Susceptible Analysis

Landslide detection from an open satellite imagery and digital elevation model dataset using attention boosted convolutional neural networks

Landslide spatial modelling using unsupervised factor optimisation and regularised greedy forests

A Gentle Introduction to Deep Learning for Graphs

Forecasting of landslide displacements using a chaos theory based wavelet analysis-Volterra filter model

The performance of using an autoencoder for prediction and susceptibility assessment of landslides: A case study on landslides triggered by the 2018 Hokkaido Eastern Iburi earthquake in Japan

Interpretable Machine Learning

Convolutional Neural Networks enable efficient, accurate and fine-grained segmentation of plant species and communities from high-resolution UAV imagery

Deep Learning Architectures

Coupling logistic model tree and random subspace to predict the landslide susceptibility areas with considering the uncertainty of environmental features

Improved landslide assessment using support vector machine with bagging, boosting, and stacking ensemble machine learning framework in a mountainous watershed, Japan

Dry Spells and Extreme Precipitation are The Main Trigger of Landslides in Central Europe

Use of Very High-Resolution Optical Data for Landslide Mapping and Susceptibility Analysis along the Karnali Highway, Nepal

A deep learning algorithm using a fully connected sparse autoencoder neural network for landslide susceptibility prediction

Landslide Detection Using Residual Networks and the Fusion of Spectral and Topographic Information

Machine learning-based prediction system for rainfall-induced landslides in Benguet First Engineering District

Recent advances and applications of machine learning in solid-state materials science

Deep learning: new computational modelling techniques for genomics

Machine learning based landslide assessment of the Belgrade metropolitan area: Pixel resolution effects and a cross-scaling concept

Correction to: An object-based approach for semi-automated landslide change detection and attribution of changes to landslide classes in northern Taiwan

Deep learning in remote sensing applications: A meta-analysis and review

Optimizing Sample Patches Selection of CNN to Improve the mIOU on Landslide Detection

Exploring the effects of the design and quantity of absence data on the performance of random forest-based landslide susceptibility mapping

Comparison of convolutional neural networks for landslide susceptibility mapping in Yanshan County, China.

The Application of Long Short-Term Memory(LSTM) Method on Displacement Prediction of Multifactor-Induced Landslides

Applications of machine learning in drug discovery and development

Estimating the rainfall threshold of a deep-seated landslide by integrating models for predicting the groundwater level and stability analysis of the slope

Landslide susceptibility modeling using Reduced Error Pruning Trees and different ensemble techniques: Hybrid machine learning approaches

A graph convolutional neural network for classification of building patterns using spatial vector data

Machine learning for data-driven discovery in solid Earth geoscience

Survey on deep learning with class imbalance

Deep learning and process understanding for data-driven Earth system science

Landslide Inventory Mapping From Bitemporal Images Using Deep Convolutional Neural Networks

Effects of smoking on cognition and BDNF levels in a male Chinese population: relationship with BDNF Val66Met polymorphism

Time series analysis and long short-term memory neural network to predict landslide displacement

Landslide Susceptibility Mapping Based on Weighted Gradient Boosting Decision Tree in Wanzhou Section of the Three Gorges Reservoir Area (China)

A shallow slide prediction model combining rainfall threshold warnings and shallow slide susceptibility in Busan, Korea

Landslide Susceptibility Assessment Using Integrated Deep Learning Algorithm along the China-Nepal Highway

Sensitivity analysis of automatic landslide mapping: numerical experiments towards the best solution

Global fatal landslide occurrence from 2004 to 2016

The Impact of Imbalanced Training Datasets on CNN Performance in Typical Remote Scenes Classification

Genetic Algorithm

Combination of Rainfall Thresholds and Susceptibility Maps for Dynamic Landslide Hazard Assessment at Regional Scale

To: “On vertical resolution of seismic acquisition geometries in complex 3D media,” Jun Su, Li-Yun Fu, Wei Wei, Weijia Sun, and Junhua Hu, Geophysics, 82, no. 6, P75–P87, doi: 10.1190/geo2017-0028.1.

Overcoming the legal and regulatory barriers to drug repurposing

RGCNN: Regularized Graph CNN for Point Cloud Segmentation

Landslide susceptibility modelling using GIS-based machine learning techniques for Chongren County, Jiangxi Province, China.

Random mesh projectors for inverse problems

A hybrid deep learning based traffic flow prediction method and its understanding

Dynamic Sampling in Convolutional Neural Networks for Imbalanced Data Classification

Landslide susceptibility mapping using J48 Decision Tree with AdaBoost, Bagging and Rotation Forest ensembles in the Guangchang area (China)

Understanding Autoencoders with Information Theoretic Concepts

Lithologic mapping using Random Forests applied to geophysical and remote-sensing data: A demonstration study from the Eastern Goldfields of Australia

Satellite‐Based Assessment of Rainfall‐Triggered Landslide Hazard for Situational Awareness

Displacement prediction of Baijiabao landslide based on empirical mode decomposition and long short-term memory neural network in Three Gorges area, China

Advanced MT-InSAR Landslide Monitoring: Methods and Trends

Method for Meteorological Early Warning of Precipitation-Induced Landslides Based on Deep Neural Network

Assessment of the effects of training data selection on the landslide susceptibility mapping: a comparison between support vector machine (SVM), logistic regression (LR) and artificial neural networks (ANN)

Disaster detection from aerial imagery with convolutional neural network

Comparison of four kernel functions used in support vector machines for landslide susceptibility mapping: a case study at Suichuan area (China)

A Comparison of Class Imbalance Techniques for Real-World Landslide Predictions

Large-Scale Point Cloud Semantic Segmentation with Superpoint Graphs

Recent developments in machine learning applications in landslide susceptibility mapping

Machine Learning for the Geosciences: Challenges and Opportunities

Generative Adversarial Networks-Based Semi-Supervised Learning for Hyperspectral Image Classification

AutoEncoder by Forest

Evaluating fuzzy operators of an object-based image analysis for detecting landslides and their changes

Focal Loss for Dense Object Detection

A landslide intelligent detection method based on CNN and RSG_R

Method for prediction of landslide movements based on random forests

Integration of LiDAR and QuickBird Data for Automatic Landslide Detection Using Object-Based Analysis and Random Forests