Advanced Technologies for Forest Fire Detection and Monitoring

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

Deadline for manuscript submissions: 20 March 2026 | Viewed by 258

Special Issue Editors


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Guest Editor
School of Technology, Beijing Forestry University, Beijing 100083, China
Interests: forest fire detection; fire danger forecast; fire spread prediction

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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
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Guest Editor
College of Mechanical and Electrical Engineering, Northeast Forestry University, Harbin 150040, China
Interests: forest fire; lstm; fire spread simulation; extreme learning machine; intelligent forest fire prevention and control technology

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Guest Editor
College of Information Science and Technology, Nanjing Forestry University, Nanjing 210037, China
Interests: forestry non-destructive detection; forestry Internet of things technology; microwave and optical technology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Forests, as a crucial ecosystem, play a key role in maintaining global biodiversity and climate stability. However, the increasing frequency and intensity of forest fires pose a huge threat to these precious natural resources. With the rapid development of new technologies such as artificial intelligence and remote sensing, it has become particularly important to apply advanced technologies to forest fire monitoring. Comprehensively applying different new technologies in various development stages of forest fires for the danger forecast, early detection, and spread prediction of fires can provide effective support for curbing the occurrence and development of fires. This Special Issue aims to showcase the cutting-edge research results and innovative practices in the field of forest fire monitoring, aiming to build a platform for researchers, practitioners, and policymakers to exchange knowledge and ideas.  

Prof. Dr. Change Zheng
Dr. Fengjun Zhao
Dr. Xingdong Li
Prof. Dr. Yunfei Liu
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

  • forest fire
  • fire danger forecast
  • early detection
  • spread prediction
  • artificial intelligence
  • remote sensing
  • UAV
  • IoT
  • multi-source data

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Published Papers

This special issue is now open for submission.
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