Machine Learning in Disaster Management: Recent Developments in Methods and Applications

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Machine Learning and Knowledge Extraction(2022)

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TL;DR

This paper aims to provide an overview of the research studies, presented since 2017, focusing on ML and DL developed methods for disaster management, with focus on studies in the areas of disaster and hazard prediction, risk and vulnerability assessment, disaster detection, early warning systems, disaster monitoring, damage assessment and post-disaster response.

Abstract

Recent years include the world’s hottest year, while they have been marked mainly, besides the COVID-19 pandemic, by climate-related disasters, based on data collected by the Emergency Events Database (EM-DAT). Besides the human losses, disasters cause significant and often catastrophic socioeconomic impacts, including economic losses. Recent developments in artificial intelligence (AI) and especially in machine learning (ML) and deep learning (DL) have been used to better cope with the severe and often catastrophic impacts of disasters. This paper aims to provide an overview of the research studies, presented since 2017, focusing on ML and DL developed methods for disaster management. In particular, focus has been given on studies in the areas of disaster and hazard prediction, risk and vulnerability assessment, disaster detection, early warning systems, disaster monitoring, damage assessment and post-disaster response as well as cases studies. Furthermore, some recently developed ML and DL applications for disaster management have been analyzed. A discussion of the findings is provided as well as directions for further research.

Authors

Vasileios Linardos

1 papers

M. Drakaki

1 papers

P. Tzionas

1 papers

References76 items

Interconnected Disaster Risks

Information fusion as an integrative cross-cutting enabler to achieve robust, explainable, and trustworthy medical artificial intelligence

Investigating the impact of site management on distress in refugee sites using Fuzzy Cognitive Maps

Novel ensemble machine learning models in flood susceptibility mapping

Earthquake disaster avoidance learning system using deep learning

Machine Learning in Disaster Management: Recent Developments in Methods and Applications

Published in

Machine Learning and Knowledge Extraction(2022)

External Links:

Generate Graph DownloadPDF

TL;DR

Abstract

Authors

Vasileios Linardos

1 papers

M. Drakaki

1 papers

P. Tzionas

1 papers

References76 items

Interconnected Disaster Risks

Information fusion as an integrative cross-cutting enabler to achieve robust, explainable, and trustworthy medical artificial intelligence

Investigating the impact of site management on distress in refugee sites using Fuzzy Cognitive Maps

Novel ensemble machine learning models in flood susceptibility mapping

Earthquake disaster avoidance learning system using deep learning

Y. L. Karnavas

1 papers

Machine Learning based Classification of Online News Data for Disaster Management

A Hybrid Model based on Fused Features for Detection of Natural Disasters from Satellite Images

Rapid Structure Detection in Support of Disaster Response: A Case Study of the 2018 Kilauea Volcano Eruption

Multi-task Multimodal Learning for Disaster Situation Assessment

Assessing Building Damage by Learning the Deep Feature Correspondence of Before and After Aerial Images

Applications of artificial intelligence for disaster management

Automated Identification of Disaster News for Crisis Management using Machine Learning and Natural Language Processing

EagleEYE: Aerial Edge-enabled Disaster Relief Response System

A big data-driven dynamic estimation model of relief supplies demand in urban flood disaster

#Outage: Detecting Power and Communication Outages from Social Networks

Management of humanitarian relief operations using satellite big data analytics: the case of Kerala floods

Disaster Assessment from Satellite Imagery by Analysing Topographical Features Using Deep Learning

Exploring the role of deep neural networks for post-disaster decision support

A Hybrid Machine Learning Pipeline for Automated Mapping of Events and Locations From Social Media in Disasters

Predicting landslide susceptibility and risks using GIS-based machine learning simulations, case of upper Nyabarongo catchment

Individual Status Recognition System Assisted by UAV in Post-Disaster

An Experimental Research on the Use of Recurrent Neural Networks in Landslide Susceptibility Mapping

Harnessing the power of machine learning: Can Twitter data be useful in guiding resource allocation decisions during a natural disaster?

Flood prediction based on weather parameters using deep learning

Urban Flood Mapping with Residual Patch Similarity Learning

Learn to Detect: Improving the Accuracy of Earthquake Detection

Natural Disaster Application on Big Data and Machine Learning: A Review

A Deep Learning Approach for Tweet Classification and Rescue Scheduling for Effective Disaster Management

Evaluation and comparison of the advanced metaheuristic and conventional machine learning methods for the prediction of landslide occurrence

CrowdLearn: A Crowd-AI Hybrid System for Deep Learning-based Damage Assessment Applications

Using a combination of human insights and ‘deep learning’ for real-time disaster communication

Identifying disaster related social media for rapid response: a visual-textual fused CNN architecture

Extracting Resource Needs and Availabilities From Microblogs for Aiding Post-Disaster Relief Operations

A computationally efficient multi-modal classification approach of disaster-related Twitter images

Multi-Network Vulnerability Causal Model for Infrastructure Co-Resilience

Analysis of remote sensing imagery for disaster assessment using deep learning: a case study of flooding event

A Hybrid Machine Learning Approach for Classifying Aerial Images of Flood-Hit Areas

Detection of Flood Images Posted on Online Social Media for Disaster Response

Identifying disaster-related tweets and their semantic, spatial and temporal context using deep learning, natural language processing and spatial analysis: a case study of Hurricane Irma

Training an Emergency-Response Image Classifier on Signal Data

An intelligent multi-agent based decision support system for refugee settlement siting

Classification of Short-Texts Generated During Disasters: A Deep Neural Network Based Approach

Flood vulnerability assessment using artificial neural networks in Muar Region, Johor Malaysia

Combining machine-learning topic models and spatiotemporal analysis of social media data for disaster footprint and damage assessment

Localizing and Quantifying Damage in Social Media Images

Machine Learning Seismic Wave Discrimination: Application to Earthquake Early Warning

Big Data in Natural Disaster Management: A Review

Disaster Response Aided by Tweet Classification with a Domain Adaptation Approach

Landslide susceptibility modeling applying machine learning methods: A case study from Longju in the Three Gorges Reservoir area, China

Fuzzy neural network and LLE Algorithm for forecasting precipitation in tropical cyclones: comparisons with interpolation method by ECMWF and stepwise regression method

Early fire detection using convolutional neural networks during surveillance for effective disaster management

Damage Assessment from Social Media Imagery Data During Disasters

Image4Act: Online Social Media Image Processing for Disaster Response

Hybrid integration of Multilayer Perceptron Neural Networks and machine learning ensembles for landslide susceptibility assessment at Himalayan area (India) using GIS

TL;DR

Abstract

Authors

References76 items

Interconnected Disaster Risks

Information fusion as an integrative cross-cutting enabler to achieve robust, explainable, and trustworthy medical artificial intelligence

Investigating the impact of site management on distress in refugee sites using Fuzzy Cognitive Maps

Novel ensemble machine learning models in flood susceptibility mapping

Earthquake disaster avoidance learning system using deep learning

TL;DR

Abstract

Authors

References76 items

Interconnected Disaster Risks

Information fusion as an integrative cross-cutting enabler to achieve robust, explainable, and trustworthy medical artificial intelligence

Investigating the impact of site management on distress in refugee sites using Fuzzy Cognitive Maps

Novel ensemble machine learning models in flood susceptibility mapping

Earthquake disaster avoidance learning system using deep learning

Machine Learning based Classification of Online News Data for Disaster Management

A Hybrid Model based on Fused Features for Detection of Natural Disasters from Satellite Images

Rapid Structure Detection in Support of Disaster Response: A Case Study of the 2018 Kilauea Volcano Eruption

Multi-task Multimodal Learning for Disaster Situation Assessment

Assessing Building Damage by Learning the Deep Feature Correspondence of Before and After Aerial Images

Applications of artificial intelligence for disaster management

Automated Identification of Disaster News for Crisis Management using Machine Learning and Natural Language Processing

EagleEYE: Aerial Edge-enabled Disaster Relief Response System

A big data-driven dynamic estimation model of relief supplies demand in urban flood disaster

#Outage: Detecting Power and Communication Outages from Social Networks

Management of humanitarian relief operations using satellite big data analytics: the case of Kerala floods

Disaster Assessment from Satellite Imagery by Analysing Topographical Features Using Deep Learning

Exploring the role of deep neural networks for post-disaster decision support

A Hybrid Machine Learning Pipeline for Automated Mapping of Events and Locations From Social Media in Disasters

Predicting landslide susceptibility and risks using GIS-based machine learning simulations, case of upper Nyabarongo catchment

Individual Status Recognition System Assisted by UAV in Post-Disaster

An Experimental Research on the Use of Recurrent Neural Networks in Landslide Susceptibility Mapping

Harnessing the power of machine learning: Can Twitter data be useful in guiding resource allocation decisions during a natural disaster?

Flood prediction based on weather parameters using deep learning

Urban Flood Mapping with Residual Patch Similarity Learning

Learn to Detect: Improving the Accuracy of Earthquake Detection

Natural Disaster Application on Big Data and Machine Learning: A Review

A Deep Learning Approach for Tweet Classification and Rescue Scheduling for Effective Disaster Management

Evaluation and comparison of the advanced metaheuristic and conventional machine learning methods for the prediction of landslide occurrence

CrowdLearn: A Crowd-AI Hybrid System for Deep Learning-based Damage Assessment Applications

Using a combination of human insights and ‘deep learning’ for real-time disaster communication

Identifying disaster related social media for rapid response: a visual-textual fused CNN architecture

Extracting Resource Needs and Availabilities From Microblogs for Aiding Post-Disaster Relief Operations

A computationally efficient multi-modal classification approach of disaster-related Twitter images

Multi-Network Vulnerability Causal Model for Infrastructure Co-Resilience

Analysis of remote sensing imagery for disaster assessment using deep learning: a case study of flooding event

A Hybrid Machine Learning Approach for Classifying Aerial Images of Flood-Hit Areas

Detection of Flood Images Posted on Online Social Media for Disaster Response

Identifying disaster-related tweets and their semantic, spatial and temporal context using deep learning, natural language processing and spatial analysis: a case study of Hurricane Irma

Training an Emergency-Response Image Classifier on Signal Data

An intelligent multi-agent based decision support system for refugee settlement siting

Classification of Short-Texts Generated During Disasters: A Deep Neural Network Based Approach

Flood vulnerability assessment using artificial neural networks in Muar Region, Johor Malaysia

Combining machine-learning topic models and spatiotemporal analysis of social media data for disaster footprint and damage assessment

Localizing and Quantifying Damage in Social Media Images

Machine Learning Seismic Wave Discrimination: Application to Earthquake Early Warning

Big Data in Natural Disaster Management: A Review

Disaster Response Aided by Tweet Classification with a Domain Adaptation Approach

Landslide susceptibility modeling applying machine learning methods: A case study from Longju in the Three Gorges Reservoir area, China

Fuzzy neural network and LLE Algorithm for forecasting precipitation in tropical cyclones: comparisons with interpolation method by ECMWF and stepwise regression method

Early fire detection using convolutional neural networks during surveillance for effective disaster management

Damage Assessment from Social Media Imagery Data During Disasters

Image4Act: Online Social Media Image Processing for Disaster Response

DeepMob

Hybrid integration of Multilayer Perceptron Neural Networks and machine learning ensembles for landslide susceptibility assessment at Himalayan area (India) using GIS

A Convolutional Neural Network Approach for Assisting Avalanche Search and Rescue Operations with UAV Imagery

Shallow landslide susceptibility assessment using a novel hybrid intelligence approach

Deep learning in neural networks: An overview

Kernel methods in machine learning

OR/MS research in disaster operations management

HAZUS-MH Flood Loss Estimation Methodology. I: Overview and Flood Hazard Characterization

Humanitarian aid logistics: supply chain management in high gear

HAZUS-MH Flood Loss Estimation Methodology. II. Damage and Loss Assessment

A support vector clustering method

Geneva, Switzerland, 2009

Automated Machine Learning Approaches for Emergency Response and Coordination via Social Media in the Aftermath of a Disaster: A Review

Analysis of medical rescue strategies based on a rough set and genetic algorithm: A disaster classification perspective