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: 31 August 2025 | Viewed by 511

Special Issue Editors

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
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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 100 words) can be sent to the Editorial Office for announcement on this website.

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 (1 paper)

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Research

24 pages, 16643 KiB  
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
Viewed by 260
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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