Intelligent Forest Fire Prediction and Detection
A special issue of Fire (ISSN 2571-6255).
Deadline for manuscript submissions: 29 February 2024 | Viewed by 1864
Interests: remote sensing; climate change; forest fires
Interests: data analysis; machine learning; forest fires
In recent years, there has been a discernible escalation in the frequency and severity of global wildfires, which poses a significant peril to the preservation of biodiversity within forested regions. Concurrently with the loss of biodiversity in these areas, wildfires engender deleterious ramifications on the economic sector and contribute to an upsurge in human casualties. Given the recurring nature of forest fires, the mounting atmospheric temperatures, the heightened occurrence of severe weather phenomena, and the extensive human intervention in these domains, forests are experiencing a diminished capacity to withstand and recuperate from fires, thereby resulting in a profound reduction in their expanse.
Gaining a comprehensive understanding of the interconnections between meteorological elements, remote sensing methodologies, and statistical prediction models is pivotal for establishing correlations between the level of fire hazard and these specific regions. Such comprehension assumes paramount significance in comprehending the implications of climate change on these areas. Furthermore, it facilitates the formulation of strategic plans that foster sustainable growth and judicious exploitation of forest resources.
Submitted manuscripts must be original contributions, not previously published or submitted to other journals.
Dr. Demin Gao
Dr. Shuo Zhang
Dr. Cheng He
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.
- novel techniques in wildfires (artificial intelligence, big data, cloud computing, machine learning, data mining, deep learning, and reinforcement learning)
- remote sensing
- Internet of Things
- climate change
- forest fires
- fire models
- fire monitoring
- reviews on wildfire
- prescribed burning
- fire ecology
- fire regime
- fire behavior
- fire Management
- fuel characteristics and management
- fire prediction and fighting techniques
- fire Literature measurement and analysis of research trends