Forest fires diminish forests’ ecological services, including carbon sequestration, water retention, air cooling, and recreation, while polluting the environment and endangering habitats. Despite considerable economic advancements, firefighting...
Support vector regression (SVR) and the adaptive neuro-fuzzy inference system (ANFIS) are two well-known and powerful artificial intelligence techniques which have been frequently used for hazard mapping. So far, a plethora of hybrid models have been...
Wildfires in the Mediterranean are expected to become increasingly frequent and intense under climate change and increasing drought conditions. Owing to the growing computational capabilities of modern GPUs, deep learning approaches are increasingly...
Fires are one of the most destructive forces in natural ecosystems. This study aims to develop and compare four hybrid models using two well-known machine learning models, support vector regression (SVR) and the adaptive neuro-fuzzy inference system...
Forests fires in northern Iran have always been common, but the number of forest fires has been growing over the last decade. It is believed, but not proven, that this growth can be attributed to the increasing temperatures and droughts. In general,...
This study aimed to prepare forest fire susceptibility mapping (FFSM) using a ubiquitous GIS and an ensemble of adaptive neuro fuzzy interface system (ANFIS) with genetic (GA) and simulated annealing (SA) algorithms (ANFIS-GA-SA) and an ensemble of r...
Forest fire events in coastal eastern Guangdong are strongly associated with human activities and often occur as small-scale, short-lived early-stage fire events. Given uneven thermal monitoring infrastructure, a key challenge is leveraging data-rich...
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 effectiveness of resource allocation. Thus, further improving the...
Forest fires are among the most major causes of global ecosystem degradation. The integration of spatial information from various sources using statistical analyses in the GIS environment is an original tool in managing the spread of forest fires, wh...
The economic and environmental impacts of wildfires have leveraged the development of new technologies to prevent and reduce the occurrence of these devastating events. Indeed, identifying and mapping fire-susceptible areas arise as critical tasks, n...
Wildfires in Mediterranean areas are becoming more frequent, and the fire season is extending toward the spring and autumn months. These alarming findings indicate an urgent need to develop fire susceptibility methods capable of identifying areas vul...
Forest fires are a major environmental concern in Northern Thailand, contributing to ecosystem degradation, biodiversity loss, and seasonal air pollution. This study identified the environmental factors influencing forest fire occurrence and develope...
The main objectives of this paper are to demonstrate the results of an ensemble learning method based on prediction results of support vector machine and random forest methods using Bayesian average. In this study, we generated susceptibility maps of...
In boreal ecosystems, wildfire severity (i.e., the extent of fire-related tree mortality) is affected by environmental conditions and fire intensity. A burned area usually includes tree patches that partially or entirely escaped fire. There are two t...
Recurring forest fires disturb ecological balance, impact socio-economic harmony, and raise global concern. This study implements multiple statistical and weighted modelling approaches to identify forest fire susceptibility zones in Eastern India. Si...
The Cat Ba National Park area (Vietnam) with its tropical forest is recognized as being part of the world biodiversity conservation by the United Nations Educational, Scientific and Cultural Organization (UNESCO) and is a well-known destination for t...
Wildfire susceptibility maps play a crucial role in preemptively identifying regions at risk of future fires and informing decisions related to wildfire management, thereby aiding in mitigating the risks and potential damage posed by wildfires. This...
Wildfire susceptibility mapping (WSM) plays a crucial role in identifying areas with heightened vulnerability to forest fires, allowing for proactive measures in fire prevention, management, and resource allocation, ultimately leading to more effecti...
This study aimed to enhance the accuracy of forest fire susceptibility mapping (FSM) by innovatively applying recursive feature elimination (RFE) with an ensemble of machine learning models, specifically Support Vector Machine (SVM) and Random Forest...
Artificial intelligence (AI) offers several opportunities in wildfire management, particularly for improving short- and long-term fire occurrence forecasting, spread modeling, and decision-making. When properly adapted beyond research into real-world...
Semi-Mediterranean (SM) and semi-arid (SA) regions, exemplified by the Kurdo-Zagrosian forests in western Iran and northern Iraq, have experienced frequent wildfires in recent years. This study proposes a modified Non-Negative Matrix Factorization (N...
Forest fire risk prediction is essential for building a forest fire defense system. Ensemble learning methods can avoid the problem of difficult model selection for disaster susceptibility prediction and can significantly improve modeling accuracy. T...
Forest fire risk assessment methodologies vary considerably, presenting challenges for adaptation to specific local contexts. This study provides a systematic analysis of forest fire assessment approaches across the Mediterranean basin, American, Afr...
The effects of the spatial resolution of remote sensing (RS) data on wildfire susceptibility prediction are not fully understood. In this study, we evaluate the effects of coarse (Landsat 8 and SRTM) and medium (Sentinel-2 and ALOS) spatial resolutio...
Mediterranean European countries, including Portugal, are considered fire-prone regions, being affected by fire events every summer. Nonetheless, Portugal has been recording large burned areas over the last 20 years, which are not only strongly assoc...
Wildland–urban interface (WUI) wildfires pose escalating threats worldwide due to climate change and urban expansion. Gangneung City, South Korea, accounts for approximately 56% of provincial wildfire damage over the past decade, highlighting t...
Kotawaringin Barat is a high-risk area for forest and land fires; a total of 564.13 km2 of forest land was burned from 2015 to 2022, the majority of which spread to peatlands. The goal of this contribution is to use the information value method (IVM)...
Predicting and mapping fire susceptibility is a top research priority in fire-prone forests worldwide. This study evaluates the abilities of the Bayes Network (BN), Naïve Bayes (NB), Decision Tree (DT), and Multivariate Logistic Regression (MLP)...
The wildfires of summer 2021 in Greece were among the most severe forest fire events that have occurred in the country over the past decade. The conflagration period lasted for 20 days (i.e., from 27 July to 16 August 2021) and resulted in the devast...
Wildfire susceptibility maps display the spatial probability of an area to burn in the future, based solely on the intrinsic local proprieties of a site. Current studies in this field often rely on statistical models, often improved by expert knowled...
Plumas National Forest, located in the Butte and Plumas counties, has experienced devastating wildfires in recent years, resulting in substantial economic losses and threatening the safety of people. Mapping damaged areas and assessing wildfire susce...
Annually, the oak forests of the Zagros Mountains chains in western Iran and northeastern Iraq face recurring challenges posed by forest fires, particularly in the Kurdo–Zagrosian forests in western Iran and northeastern Iraq. Assessing fire su...
Wildfires cause great losses to the ecological environment, economy, and people’s safety and belongings. As a result, it is crucial to establish wildfire susceptibility models and delineate fire risk levels. It has been proven that the use of r...
Forest fires have significant impacts on economies, cultures, and ecologies worldwide. Developing predictive models for forest fire probability is crucial for preventing and managing these fires. Such models contribute to reducing losses and the freq...
Wildfires pose significant risks to ecosystems, human lives, and infrastructure, necessitating advanced predictive tools to mitigate their impacts. This study presents a machine learning-based framework for wildfire susceptibility mapping (WSM), desi...
The number of forest fires ignitions has decreased worldwide, thus observing increased levels of intensity and destruction, endangering urban areas and causing material damages and deaths (Portugal, 2017). Forest fire hazard mapping supported by the...
Wildfires are occurring throughout the world, causing more damage to plant and animal species, humans, and the environment. Fire danger indices are useful for forecasting fire danger, and these indices involve the integration of both static and dynam...
The layout of a city is complex, and indoor spaces have thousands of aspects that make them susceptible to fire. If a fire breaks out, it is difficult to quell, so a fire in the city will cause great harm. However, the traditional fire detection algo...
As climate change increases the frequency and unpredictability of natural hazards, adapting critical infrastructure is crucial for long-term resilience. Among these hazards, embankment fires pose a growing threat to railway systems, particularly unde...
The uncontrolled spread of fire can have huge effects on ecosystems. In Ecuador, in 2022, wildfires caused a loss of 6566.66 hectares of vegetation cover. Ibarra is an Andean canton that has also been exposed to wildfires and their effects. The aim o...
Wildfire susceptibility mapping supports proactive forest management, and estimated predictive performance may vary with spatial dependence and the control-point sampling strategy. We developed an interpretable random-forest framework to map wildfire...
To prevent or mitigate the negative impact of fires, spatial prediction maps of wildfires are created to identify susceptible locations and key factors that influence the occurrence of fires. This study uses artificial intelligence models, specifical...
The fire susceptibility of the Atlantic Forest has largely increased over the past two decades due to a combination of climate change and anthropogenic factors such as land cover change and human modification. High rates of forest fragmentation have...
Risk mapping is a crucial part of spatial planning, as it optimizes the allocation of resources in its management. It is, therefore, of great interest to build tools that enhance its production. This work focuses on the implementation of a susceptibi...
In recent years, ecosystems in Saudi Arabia have experienced severe degradation due to factors such as hyperaridity, overgrazing, climate change, urban expansion, and an increase in uncontrolled wildfires. Among these, wildfires have emerged as the s...
10 August 2022
INTERMED (Interventions pour gérer et réduire le risque d’incendie à l’interface habitat-espace naturel) deals with the fire risk at Wildland Urban Interface (WUI) and brings together Collectivité de Corse, Uni...
The post-fire debris flow (PFDF) is a commonly destructive hazard that may persist for several years following the wildfires. Susceptibility mapping is an effective method for mitigating hazard risk. Yet, the majority of susceptibility prediction mod...
This study investigates the role of prescribed grazing as a sustainable fire prevention strategy in Mediterranean ecosystems, with a focus on Sardinia, an area highly susceptible to wildfires. Using FlamMap simulation software, we modeled fire behavi...
This study presents a comprehensive analysis of natural hazard susceptibility in the Makedonska Kamenica municipality of North Macedonia, encompassing erosion assessment, landslides, flash floods, and forest fire vulnerability. Employing advanced GIS...
Forest fire susceptibility mapping is an important component of disaster risk reduction, particularly in transitional climatic zones such as Anhui Province, China. Traditional approaches often rely on expert weighting (AHP) or linear assumptions, whi...
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