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Forests
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Forest Fire: Landscape Patterns, Risk Prediction and Fuels Management
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Forest Fire: Landscape Patterns, Risk Prediction and Fuels Management

A special issue of Forests (ISSN 1999-4907). This special issue belongs to the section "Natural Hazards and Risk Management".

Deadline for manuscript submissions: closed (10 March 2026) | Viewed by 5726

Special Issue Editors

Dr. Luís Reis

E-Mail Website
Guest Editor
1. ISEC Lisboa—Higher Institute of Education and Sciences, Alameda das Linhas de Torres, 179, 1750-142 Lisbon, Portugal
2. ESTA—Abrantes Higher School of Technology, Polytechnic Institute of Tomar, R. 17 de Agosto de 1808, 2200-370 Abrantes, Portugal
3. RCM2+ Research Centre for Asset Management and Systems Engineering, Polytechnic Institute of Coimbra, R. Pedro Nunes, 3030-199 Coimbra, Portugal
Interests: forest fires; fire safety; fire technology; renewable energy technologies
Special Issues, Collections and Topics in MDPI journals
Dr. Jorge R.N. Raposo

E-Mail Website
Guest Editor
Ci2—Smart Cities Research Center, Polytechnic Institute of Tomar (Abrantes Higher School of Technology), 2300-313 Tomar, Portugal
Interests: forest fires; merging fires; fire safety; fire technology; asset maintenance
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Wildfires are becoming increasingly common worldwide, representing one of the most frequent and highly destructive disasters. They impact forests, ecosystems, human populations, and infrastructure, and cause significant socioeconomic consequences, as financial resources are needed to combat the fire and repair the damage caused. Changes in meteorological conditions have contributed to more frequent droughts and heatwaves, which, in turn, trigger the occurrence of extreme events. Among various societal demands, there is a growing need to enhance knowledge about the role of meteorology in the extreme behavior of such fires. This knowledge can be integrated into decision support tools, influencing operational strategies and ultimately helping to save lives. Understanding wildfires is often directed toward fire operators and decision-makers who require support in forest management to achieve the best possible outcomes.

This Special Issue aims to present advancements in fire control methods, fuel management, fire prediction and behavior, the causes of fires, and strategies for mitigating wildfires.

Dr. Luís Reis
Dr. Jorge R.N. Raposo
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Forests is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • fire behavior
  • fire events
  • forest fires
  • fire management
  • fire safety
  • fire technology
  • moisture fuel
  • climate change
  • fuel management

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Published Papers (5 papers)

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Research

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39 pages, 9067 KB  
Article
Danger of Vegetation Fires in the Cerrado-Amazon Transition Region Based on In Situ and Reanalysis Meteorological Data
by Luzinete Scaunichi Barbosa, Daniela Castagna, Rhavel Salviano Dias Paulista, Daniela Roberta Borella and Adilson Pacheco de Souza
Forests 2026, 17(4), 437; https://doi.org/10.3390/f17040437 - 31 Mar 2026
Viewed by 527
Abstract
Fire hazard indices are fundamental for mitigating socioeconomic and environmental damage. This study evaluated the performance of the Ängstrom, FMA, FMA+, EVAP/P, and P-EVAP indices in the Cerrado-Amazon transition region (2010–2022), Brazil, using data from National Institute of Meteorology (INMET) and reanalysis (Copernicus). [...] Read more.
Fire hazard indices are fundamental for mitigating socioeconomic and environmental damage. This study evaluated the performance of the Ängstrom, FMA, FMA+, EVAP/P, and P-EVAP indices in the Cerrado-Amazon transition region (2010–2022), Brazil, using data from National Institute of Meteorology (INMET) and reanalysis (Copernicus). The efficiency of the models was validated by the Skill Score and Percentage of Success methods, correlating them with the hotspots from the DBQueimadas (INPE). The results reveal climatic seasonality typical of tropical regions, with rainy summers and severely dry winters, with minimum relative humidity below 30%. Although the average annual rainfall is 1662.20 mm, spatial heterogeneity and seasonal water reduction drove a 42% increase in the number of fire occurrences, totaling 3.9 million hotspots in the period. The P-EVAP and FMA+ indices showed greater predictive accuracy, with P-EVAP reaching a Skill Score of up to 0.74, especially with reanalysis data. FMA showed intermediate performance, while Ängstrom and EVAP/P were less reliable. Regionally, the highest sensitivity and accuracy of the indices were observed in Maranhão and Tocantins. It is concluded that regional meteorological variability directly influences the risk of wildfires, with P-EVAP and FMA+ being the most effective tools for monitoring and preventing fires in the region. Full article
(This article belongs to the Special Issue Forest Fire: Landscape Patterns, Risk Prediction and Fuels Management)
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17 pages, 2167 KB  
Article
The Effect of Fuel Bed Edges on Fire Dynamics
by Luis Reis, Jorge Raposo, Hugo Raposo and André Rodrigues
Forests 2026, 17(1), 124; https://doi.org/10.3390/f17010124 - 16 Jan 2026
Viewed by 674
Abstract
Wildfires are among the most frequent and destructive natural hazards in Europe, particularly in Portugal. They have severe impacts on forests, ecosystems, human health, and infrastructure, leading to substantial socio-economic losses due to firefighting efforts and post-fire recovery costs. Moreover, wildfires cause numerous [...] Read more.
Wildfires are among the most frequent and destructive natural hazards in Europe, particularly in Portugal. They have severe impacts on forests, ecosystems, human health, and infrastructure, leading to substantial socio-economic losses due to firefighting efforts and post-fire recovery costs. Moreover, wildfires cause numerous casualties each year, highlighting the need for a deeper understanding of fire behaviour to support effective firefighting strategies and ensure the safety of both responders and communities. This study examines the influence of wind flow velocity variation on fire behaviour, both in the presence and absence of an edge wall in the fuel bed, aiming to replicate the characteristics of real wildfire fronts at a laboratory scale. Experimental tests were conducted at the Forest Fire Research Laboratory (LEIF) of the University of Coimbra using a shrub mixture, composed of Ulex europaeus, Baccharis trimera, and Caralluma adscendens, representing one of the most common fine fuels in Portuguese forested landscapes. This research provides novel insights by experimentally analyzing the combined effect of wind velocity variation and fuel bed edge presence on fire behaviour, paving the way for future comparisons with numerical simulations and real wildfire fronts. As expected, increasing wind velocity and the presence of fuel bed edges resulted in higher values of rate of spread, fireline intensity, and fire intensity. Full article
(This article belongs to the Special Issue Forest Fire: Landscape Patterns, Risk Prediction and Fuels Management)
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30 pages, 12889 KB  
Article
Forest Fire Analysis Prediction and Digital Twin Verification: A Trinity Framework and Application
by Wenyan Li, Wenjiao Zai, Wenping Fan and Yao Tang
Forests 2025, 16(10), 1546; https://doi.org/10.3390/f16101546 - 7 Oct 2025
Viewed by 1134
Abstract
In recent years, frequent wildfires have posed significant threats to both the ecological environment and socioeconomic development. Investigating the mechanisms underlying the influencing factors of forest fires and accurately predicting the likelihood of such events are crucial for effective prevention strategies. However, the [...] Read more.
In recent years, frequent wildfires have posed significant threats to both the ecological environment and socioeconomic development. Investigating the mechanisms underlying the influencing factors of forest fires and accurately predicting the likelihood of such events are crucial for effective prevention strategies. However, the field currently faces challenges, including the unclear characterization of influencing factors, limited accuracy in forest fire predictions, and the absence of models for mountain fire scenarios. To address these issues, this study proposes a research framework of “decoupling analysis-model prediction-scenario validation” and employs Principal Component Analysis (PCA) and Shapley Additive Explanations (SHAP) value quantification to elucidate the significant roles of meteorological as well as combustible state indicators through multifactor coupling. Furthermore, the Attention-based Long Short-Term Memory (ALSTM) network trained on PCA-decoupled data achieved mean accuracy, recall, and area under the precision-recall curve (PR-AUC) values of 97.82%, 94.61%, and 99.45%, respectively, through 10-time cross-validation, significantly outperforming traditional LSTM neural networks and logistic regression (LR) methods. Based on digital twin technology, a three-dimensional mountain fire scenario evolution model is constructed to validate the accuracy of the ALSTM network’s predictions and to quantify the impact of key factors on fire evolution. This approach offers an interpretable solution for predicting forest fires in complex environments and provides theoretical and technical support for the digital transformation of forest fire prevention and management. Full article
(This article belongs to the Special Issue Forest Fire: Landscape Patterns, Risk Prediction and Fuels Management)
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24 pages, 16643 KB  
Article
Seasonal Driving Mechanisms and Spatial Patterns of Danger of Forest Wildfires in the Dongjiang Basin, Southern China
by Xuewen He, Zhiwei Wan, Bin Yuan, Ji Zeng, Lingyue Liu, Keyuan Zhong and Hong Wu
Forests 2025, 16(6), 986; https://doi.org/10.3390/f16060986 - 11 Jun 2025
Cited by 1 | Viewed by 979
Abstract
Global forest wildfires are increasing in both frequency and intensity, resulting in significant ecological degradation and posing substantial threats to human health. This study focused on the Dongjiang River Basin in southern China and investigated the seasonal and spatial distribution patterns of forest [...] Read more.
Global forest wildfires are increasing in both frequency and intensity, resulting in significant ecological degradation and posing substantial threats to human health. This study focused on the Dongjiang River Basin in southern China and investigated the seasonal and spatial distribution patterns of forest wildfires in the research region from 2003 to 2023 using geographic information system technology. This study employed the random forest (RF) model, a machine learning algorithm, to predict the danger level of wildfire across different seasons and quantitatively interpret the seasonal wildfire driving mechanisms using the SHapley Additive exPlanations (SHAP) values. The results indicated that forest wildfires in the Dongjiang Basin were predominantly concentrated in the eastern region of the Dongjiang Basin, with significant seasonal variation in the spatial distribution. The frequency of fire events exhibited distinct seasonal patterns, with higher incidence in spring and winter and relatively lower frequency in summer and autumn. The random forest model demonstrated high predictive accuracy for the wildfire danger in all the seasons. Furthermore, the analysis of the driving factors showed that, despite some seasonal variability, the underlying mechanisms of wildfire occurrence could be effectively quantified using the SHAP values. Notably, the Normalized Difference Vegetation Index and anthropogenic disturbances consistently emerged as the dominant driving forces behind forest wildfires across all the seasons. Full article
(This article belongs to the Special Issue Forest Fire: Landscape Patterns, Risk Prediction and Fuels Management)
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24 pages, 1882 KB  
Systematic Review
Global Shifts in Fire Regimes Under Climate Change: Patterns, Drivers, and Ecological Implications Across Biomes
by Ana Paula Oliveira and Paulo Gil Martins
Forests 2026, 17(1), 104; https://doi.org/10.3390/f17010104 - 13 Jan 2026
Cited by 4 | Viewed by 1586
Abstract
Wildfire regimes are undergoing rapid transformation under anthropogenic climate change, with major implications for biodiversity, carbon cycling, and ecosystem resilience. This systematic review synthesizes findings from 42 studies across global, continental, and regional scales to assess emerging patterns in fire frequency, intensity, and [...] Read more.
Wildfire regimes are undergoing rapid transformation under anthropogenic climate change, with major implications for biodiversity, carbon cycling, and ecosystem resilience. This systematic review synthesizes findings from 42 studies across global, continental, and regional scales to assess emerging patterns in fire frequency, intensity, and seasonality, and to identify climatic, ecological, and anthropogenic drivers shaping these changes. Across biomes, evidence shows increasingly fire-conducive conditions driven by rising temperatures, vapor-pressure deficit, and intensifying drought, with climate model projections indicating amplification of extreme fire weather this century. Boreal ecosystems show heightened fire danger and carbon-cycle vulnerability; Mediterranean and Iberian regions face extended fire seasons and faster spread rates; tropical forests, particularly the Amazon, are shifting toward more flammable states due to drought–fragmentation interactions; and savannas display divergent moisture- and fuel-limited dynamics influenced by climate and land use. These results highlight the emergence of biome-specific fire–climate–fuel feedback that may push certain ecosystems toward alternative stable states. The review underscores the need for improved attribution frameworks, integration of fire–vegetation–carbon feedback into Earth system models, and development of adaptive, regionally tailored fire-management strategies. Full article
(This article belongs to the Special Issue Forest Fire: Landscape Patterns, Risk Prediction and Fuels Management)
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