Special Issue "Advances in Remote Sensing of Post-Fire Environmental Damage and Recovery Dynamics"
Deadline for manuscript submissions: 30 June 2021.
Interests: forestry; wildfire; forest management; remote sensing; LiDAR
Interests: fire damage (burned area, burn severity); multi and hyper-spectral remote sensing; unmixing; classification
Understanding of forest fire regimes involves characterizing spatial distribution, recurrence, intensity, seasonality, size, and severity. In recent years, knowledge of damage levels can be directly related to the environmental impact of fire and, at the same time, it is a valuable estimator of fire intensity, when the data about it are not available. Remote sensing may be seen as a tool to accurately assess burn severity and to predict the potential effects of forest fires on ecosystems, thus making the prediction of the regeneration of the plant community and the effects on ecosystems easier. This information is basic to facilitate decision-making in the post-fire management of fire-prone ecosystems.
Nowadays, there has been intense research activity in relation to burned areas, burn severity, and vegetation regeneration because fires in many areas of the planet are becoming more severe and extensive. The environmental damage of affected ecosystems is also much more important, so their correct evaluation and follow-up pose great challenges to current scientists. The current advances in remote sensing and related sciences will allow us to evaluate the damage with greater precision and to know with greater reliability the dynamics of recovery.
This Special Issue aims at studies covering new remote sensing technologies, new sensors, data collections, and processing methodologies that can be successfully applied in burn severity mapping, vegetation revovery monitoring, and post-fire management of fire-prone ecosystems affected by large fires. We welcome submissions that cover but are not limited to:
- Global trends in mapping burned and burn severity in local and regional areas using the remote sensing approach;
- Wildfire severity evaluation and land monitoring with big data and artificial intelligence classification;
- Remote sensing-based assessment of post-fire forest patterns monitoring successional stages;
- 3D mapping by photogrammetry, LiDAR, and SAR in post-fire studies;
- New hyperspectral sensors applications in post-fire studies;
- Ultra-high spatial resolution using unmanned aerial vehicles (UAV) in post-fire studies;
- Improved methods of modeling image time-series for fire disturbance recovery;
- Understanding wildfire behavior and ecology behavior within and around the wildland–urban interface (WUI);
- Impact of climate change on forest fire severity and consequences for ecosystem recovery;
- Fire severity and recovery dynamics in Reducing Emissions from deforestation and degradation programs (REDD+).
Dr. Alfonso Fernández-Manso
Dr. Carmen Quintano
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 papers will be 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 2200 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.
- Wildfire severity evaluation and land monitoring
- Big data and artificial intelligence
- 3D mapping post-fire Studies
- Hyperspectral sensors post fire Studies
- Ultra-high spatial resolution
- Modeling image time-series for fire disturbance recovery
- Wildland–urban interface (WUI)
- Climate change on forest fire severity