A systematic review of applications of machine learning techniques for wildfire management decision support

K Bot, JG Borges - Inventions, 2022 - mdpi.com
Wildfires threaten and kill people, destroy urban and rural property, degrade air quality,
ravage forest ecosystems, and contribute to global warming. Wildfire management decision …

Artificial neural network approaches for disaster management: A literature review

S Guha, RK Jana, MK Sanyal - International Journal of Disaster Risk …, 2022 - Elsevier
Disaster management (DM) is one of the leading fields that deal with the humanitarian
aspects of emergencies. The field has attracted researchers because of its ever-increasing …

Machine learning based wildfire susceptibility mapping using remotely sensed fire data and GIS: A case study of Adana and Mersin provinces, Turkey

MC Iban, A Sekertekin - Ecological Informatics, 2022 - Elsevier
In recent years, the number of wildfires has increased all over the world. Therefore, mapping
wildfire susceptibility is crucial for prevention, early detection, and supporting wildfire …

[HTML][HTML] Explainable artificial intelligence (XAI) for interpreting the contributing factors feed into the wildfire susceptibility prediction model

A Abdollahi, B Pradhan - Science of the Total Environment, 2023 - Elsevier
One of the worst environmental catastrophes that endanger the Australian community is
wildfire. To lessen potential fire threats, it is helpful to recognize fire occurrence patterns and …

Wildfire danger prediction and understanding with deep learning

S Kondylatos, I Prapas, M Ronco… - Geophysical …, 2022 - Wiley Online Library
Climate change exacerbates the occurence of extreme droughts and heatwaves, increasing
the frequency and intensity of large wildfires across the globe. Forecasting wildfire danger …

Machine learning based forest fire susceptibility assessment of Manavgat district (Antalya), Turkey

HA Akıncı, H Akıncı - Earth Science Informatics, 2023 - Springer
This study primarily aims to produce forest fire susceptibility maps for the Manavgat district of
Antalya province in Turkey using different machine learning (ML) techniques. Forest fire …

Deep learning approaches for wildland fires using satellite remote sensing data: Detection, mapping, and prediction

R Ghali, MA Akhloufi - Fire, 2023 - mdpi.com
Wildland fires are one of the most dangerous natural risks, causing significant economic
damage and loss of lives worldwide. Every year, millions of hectares are lost, and experts …

Global wildfire susceptibility mapping based on machine learning models

A Shmuel, E Heifetz - Forests, 2022 - mdpi.com
Wildfires are a major natural hazard that lead to deforestation, carbon emissions, and loss of
human and animal lives every year. Effective predictions of wildfire occurrence and burned …

Shared blocks-based ensemble deep learning for shallow landslide susceptibility mapping

T Kavzoglu, A Teke, EO Yilmaz - Remote Sensing, 2021 - mdpi.com
Natural disaster impact assessment is of the utmost significance for post-disaster recovery,
environmental protection, and hazard mitigation plans. With their recent usage in landslide …

Seasonal differences in the spatial patterns of wildfire drivers and susceptibility in the southwest mountains of China

W Wang, F Zhao, Y Wang, X Huang, J Ye - Science of the Total …, 2023 - Elsevier
Wildfires directly affect global ecosystem stability and severely threaten human life. The
mountainous areas of Southwest China experience frequent wildfires. Mapping the …