Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
3.9
2.7
Journals
Fire
Special Issues
Fire Patterns, Driving Factors, and Multidimensional Impacts Under Climate Change...
share announcement

Fire Patterns, Driving Factors, and Multidimensional Impacts Under Climate Change and Human Activities

A special issue of Fire (ISSN 2571-6255). This special issue belongs to the section "Fire Research at the Science–Policy–Practitioner Interface".

Deadline for manuscript submissions: 31 January 2026 | Viewed by 1349

Special Issue Editors

Prof. Dr. Guang Yang

E-Mail Website
Guest Editor
Key Laboratory of Sustainable Forest Ecosystem Management-Ministry of Education, Northern Forest Fire Management Key Laboratory of State Forestry and Grassland Administration, College of Forestry, Northeast Forestry University, Harbin 150040, China
Interests: forest fire prediction and forecast; forest fire ecology; forest fire behavior
Dr. Fengjun Zhao

E-Mail Website
Guest Editor
Key Laboratory of Forest Protection of National Forestry and Grassland Administration, Ecology and Nature Conservation Institute, Chinese Academy of Forestry, National Forestry and Grassland Fire Monitoring, Early Warning and Prevention Engineering Technology Research Center, Beijing 100091, China
Interests: forest fire; forest fuel regulation; lightning fire; fire behavior; fire danger forecast
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Yanlong Shan

E-Mail Website
Guest Editor
Science and Technology Innovation Center of Wildland Fire Prevention and Control of Beihua University, Forestry College, Beihua University, Jilin 132013, China
Interests: forest protection; forest fire ecology; fire management
Prof. Dr. Qiuhua Wang

E-Mail Website
Guest Editor
Yunnan Key Laboratory of Forest Disaster Warning and Control, College of Civil Engineering, Southwest Forestry University, Kunming 650224, China
Interests: forest fire; forest fire ecology; fire management

Special Issue Information

Dear Colleagues,

Forest fires have emerged as a critical global challenge to ecological security due to their characteristics of sudden onset, high randomness, and devastating destructive potential. Under the combined influence of climate change and human activities, both the frequency and intensity of forest fires have risen dramatically. Compounding this issue, the substantial carbon emissions generated by these fires further exacerbate the climate crisis, creating a dangerous feedback loop between forest fires and global warming. A scientific understanding of fire patterns, driving factors, and ecological impacts forms the foundation for effective fire prevention, control strategies, and post-fire recovery management.

Analyzing the dynamic changes in forest fires across temporal scales (annual and fire season variations) provides essential data for fire risk zoning and preventive policymaking. The occurrence of forest fires is driven by complex interactions between multiple factors, including fire management policies, ignition sources, climatic conditions, vegetation types, terrain features, and fuel characteristics. These factors range from stable variables to the semi-stable and highly unstable, all of which collectively influence fire ignition, spread, and behavior. Different factor combinations determine fire severity—low-intensity fires may enhance nutrient cycling, whereas high-intensity fires may cause catastrophic forest loss and irreversible ecological damage. High-intensity forest fires with high concentrations of smoke emissions can also cause surrounding towns to be shrouded in smoke, leading to serious social impacts such as panic among residents.

Presently, due to the impact of global climate change and human activities, forest fire prevention and post-fire management face unprecedented challenges. The comprehensive scientific analysis of spatiotemporal fire distribution patterns, driving factors, and multidimensional impacts (economic, ecological, and societal) can help mitigate fire risks and consequences, and provide important reference for the formulation of forest fire prevention management policies.

In this Special Issue, original research articles and reviews are welcome, and research areas may include, but are not limited to, the following:

  1. Climate change and forest fires;
  2. Lightning-caused fire risk;
  3. Distribution of human fire sources;
  4. The factors driving forest fires;
  5. The spatial and temporal distribution of forest fires;
  6. Forest fire risk assessment and zoning;
  7. The ecological, economic, and social impacts of forest fire;
  8. Forest burning and fire behavior;
  9. Forest fire smoke emissions;
  10. Fuel management and treatment.

Prof. Dr. Guang Yang
Dr. Fengjun Zhao
Prof. Dr. Yanlong Shan
Prof. Dr. Qiuhua Wang
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. Fire 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 2400 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

  • wildfires
  • climate change
  • human activity
  • fire prediction and forecasting
  • fire prevention and control
  • fire ecology
  • fuel management
  • fire behavior
  • smoke emissions

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

23 pages, 8920 KB  
Article
All-Weather Forest Fire Automatic Monitoring and Early Warning Application Based on Multi-Source Remote Sensing Data: Case Study of Yunnan
by Boyang Gao, Weiwei Jia, Qiang Wang and Guang Yang
Fire 2025, 8(9), 344; https://doi.org/10.3390/fire8090344 - 27 Aug 2025
Viewed by 500
Abstract
Forest fires pose severe ecological, climatic, and socio-economic threats, destroying habitats and emitting greenhouse gases. Early and timely warning is particularly challenging because fires often originate from small-scale, low-temperature ignition sources. Traditional monitoring approaches primarily rely on single-source satellite imagery and empirical threshold [...] Read more.
Forest fires pose severe ecological, climatic, and socio-economic threats, destroying habitats and emitting greenhouse gases. Early and timely warning is particularly challenging because fires often originate from small-scale, low-temperature ignition sources. Traditional monitoring approaches primarily rely on single-source satellite imagery and empirical threshold algorithms, and most forest fire monitoring tasks remain human-driven. Existing frameworks have yet to effectively integrate multiple data sources and detection algorithms, lacking the capability to provide continuous, automated, and generalizable fire monitoring across diverse fire scenarios. To address these challenges, this study first improves multiple monitoring algorithms for forest fire detection, including a statistically enhanced automatic thresholding method; data augmentation to expand the U-Net deep learning dataset; and the application of a freeze–unfreeze transfer learning strategy to the U-Net transfer model. Multiple algorithms are systematically evaluated across varying fire scales, showing that the improved automatic threshold method achieves the best performance on GF-4 imagery with an F-score of 0.915 (95% CI: 0.8725–0.9524), while the U-Net deep learning algorithm yields the highest F-score of 0.921 (95% CI: 0.8537–0.9739) on Landsat 8 imagery. All methods demonstrate robust performance and generalizability across diverse scenarios. Second, data-driven scheduling technology is developed to automatically initiate preprocessing and fire detection tasks, significantly reducing fire discovery time. Finally, an integrated framework of multi-source remote sensing data, advanced detection algorithms, and a user-friendly visualization interface is proposed. This framework enables all-weather, fully automated forest fire monitoring and early warning, facilitating dynamic tracking of fire evolution and precise fire line localization through the cross-application of heterogeneous data sources. The framework’s effectiveness and practicality are validated through wildfire cases in two regions of Yunnan Province, offering scalable technical support for improving early detection of and rapid response to forest fires. Full article
(This article belongs to the Special Issue Fire Patterns, Driving Factors, and Multidimensional Impacts Under Climate Change and Human Activities)
►▼ Show Figures

Figure 1

7 pages, 1359 KB  
Article
Using Count Regression to Investigate Millennial-Scale Vegetation and Fire Response from Multiple Sites Across the Northern Rocky Mountains, USA
by Jennifer Watt, Brian F. Codding, Jordin Hartley, Carlie Murphy and Andrea Brunelle
Fire 2025, 8(8), 321; https://doi.org/10.3390/fire8080321 - 14 Aug 2025
Viewed by 492
Abstract
The Northern Rocky Mountains, USA contain a vast forested landscape, managed primarily by the federal government. This region contains some of the highest elevations forests and most iconic endangered and threatened species in the contiguous United States. The influence of human impacts and [...] Read more.
The Northern Rocky Mountains, USA contain a vast forested landscape, managed primarily by the federal government. This region contains some of the highest elevations forests and most iconic endangered and threatened species in the contiguous United States. The influence of human impacts and climate change are evident on the landscape today, with larger and more frequent fires impacting vegetation composition and recovery. This project uses paleoecological data from six lake sediment cores to investigate what drives fire across this region over the Holocene. Count regression was used to predict charcoal influx as a function of Pinus pollen accumulation rates (PAR) and percent. The results show that fire activity increases significantly with Pinus pollen, and that baseline fire activity varies significantly across sites, largely following an elevation gradient. The results of this analysis illustrate a novel way to use paleoecological data to provide valuable information to federal agencies as they prepare for future management of these ecologically valuable areas. Full article
(This article belongs to the Special Issue Fire Patterns, Driving Factors, and Multidimensional Impacts Under Climate Change and Human Activities)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-2
Back to TopTop