A comprehensive survey of research towards AI-enabled unmanned aerial systems in pre-, active-, and post-wildfire management

SPH Boroujeni, A Razi, S Khoshdel, F Afghah… - Information …, 2024 - Elsevier
Wildfires have emerged as one of the most destructive natural disasters worldwide, causing
catastrophic losses. These losses have underscored the urgent need to improve public …

[HTML][HTML] 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 …

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 …

Spatial prediction of wildfire susceptibility using hybrid machine learning models based on support vector regression in Sydney, Australia

AS Nur, YJ Kim, JH Lee, CW Lee - Remote Sensing, 2023 - mdpi.com
Australia has suffered devastating wildfires recently, and is predisposed to them due to
several factors, including topography, meteorology, vegetation, and ignition sources. This …

Improving the prediction of wildfire susceptibility on Hawaiʻi Island, Hawaiʻi, using explainable hybrid machine learning models

TTK Tran, S Janizadeh, SM Bateni, C Jun, D Kim… - Journal of environmental …, 2024 - Elsevier
This study presents a comparative analysis of four Machine Learning (ML) models used to
map wildfire susceptibility on Hawaiʻi Island, Hawaiʻi. Extreme Gradient Boosting …

Assessment of wildfire susceptibility and wildfire threats to ecological environment and urban development based on GIS and multi-source data: A case study of Guilin …

W Yue, C Ren, Y Liang, J Liang, X Lin, A Yin, Z Wei - Remote Sensing, 2023 - mdpi.com
The frequent occurrence and spread of wildfires pose a serious threat to the ecological
environment and urban development. Therefore, assessing regional wildfire susceptibility is …

[HTML][HTML] A forest fire susceptibility modeling approach based on light gradient boosting machine algorithm

Y Sun, F Zhang, H Lin, S Xu - Remote Sensing, 2022 - mdpi.com
A forest fire susceptibility map generated with the fire susceptibility model is the basis of fire
prevention resource allocation. A more reliable susceptibility map helps improve the …

[HTML][HTML] Creation of wildfire susceptibility maps in plumas national forest using InSAR coherence, deep learning, and metaheuristic optimization approaches

AS Nur, YJ Kim, CW Lee - Remote Sensing, 2022 - mdpi.com
Plumas National Forest, located in the Butte and Plumas counties, has experienced
devastating wildfires in recent years, resulting in substantial economic losses and …

RVFR: Random vector forest regression model for integrated & enhanced approach in forest fires predictions

RS Bhadoria, MK Pandey, P Kundu - Ecological Informatics, 2021 - Elsevier
The forest fires is one of the most dangerous disasters to the livelihood planet of earth.
Human intervention into the field of the destruction of nature is another cause of these forest …

[HTML][HTML] Spain on Fire: A novel wildfire risk assessment model based on image satellite processing and atmospheric information

H Liz-López, J Huertas-Tato, J Pérez-Aracil… - Knowledge-Based …, 2024 - Elsevier
Each year, wildfires destroy larger areas of Spain, threatening numerous ecosystems.
Humans cause 90% of them (negligence or provoked) and the behaviour of individuals is …