Remote Sensing for Wildfire Science: Monitoring, Modeling, and Mitigation
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Environmental Remote Sensing".
Deadline for manuscript submissions: 16 March 2026 | Viewed by 46
Special Issue Editors
Interests: quantitative remote sensing; wildfire monitoring and modeling; geospatial analysis
Special Issue Information
Dear Colleagues,
Climate-change-induced intensification and deterioration of extreme weather events, characterized by increased frequency and persistence, has driven a global escalation in wildfire occurrences during recent decades. Enhancing comprehensive wildfire prevention, control, and emergency response capabilities is an urgent priority to mitigate risk and reduce potential losses by using accurate fire modeling and rapid dynamic monitoring of fire situations. Advances in remote sensing technology have revolutionized wildfire science by enabling efficient, regional-scale application throughout all phases of wildfires (pre-fire, during the fire, and post-fire), supporting decision-making for resilient land and fire management.
This Special Issue aims to showcase studies covering the potential uses of various remote sensing data, theories, and methodologies to advance wildfire management. It also welcomes interdisciplinary contributions that integrate remote sensing, geospatial science, computer technology, fire ecology, and related fields. By bringing together research from wildfire science, this Special Issue seeks to provide forward-looking resources for land managers and policymakers, contributing to more resilient communities and ecosystems in the face of increasing wildfire threats.
Topics may cover the various applications of remote sensing in the field of wildfire science, such as in the monitoring, modeling, and analysis of wildfires. Submissions in any form (including research articles, reviews, etc.) are welcome. Potential topics include, but are not limited to, the following:
- Fire disturbance;
- Carbon cycling and wildfire emissions;
- Fuel properties;
- Biomass;
- Forest structure;
- Fuel load;
- Fuel moisture content;
- Fire behavior prediction;
- Wildfire risk modeling;
- Wildfire monitoring and tracking;
- Fire spread simulations;
- Fire and burn severity;
- Fire ecology and management;
- Wildland–urban interface fire dynamics;
- Interdisciplinary applications of wildfire science.
Prof. Dr. Binbin He
Dr. Xingwen Quan
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. Remote Sensing is an international peer-reviewed open access semimonthly 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 2700 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
- fuel
- fire regime
- wildfire monitoring
- wildfire modeling
- fire ecology
- climate change
- carbon cycling
- remote sensing
- multidisciplinary
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