Remote Sensing-Based Assessments in the Forest Fire Disturbance Continuum
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Forest Remote Sensing".
Deadline for manuscript submissions: 30 September 2024 | Viewed by 1577
Special Issue Editor
2. Department of Biodiversity and Environmental Management, Faculty of Biological and Environmental Sciences, University of León, 24071 León, Spain
Interests: wildfires; burned area; fire severity; multi- and hyperspectral remote sensing; LiDAR; SAR; unmanned aerial vehicles; land use/land cover mapping
Special Issue Information
Dear Colleagues,
Wildfires are one of the most important disturbance factors in terrestrial ecosystems worldwide, and have important implications for the regional to global climate system under unprecedented disturbance regimes. At local scales, wildfires play an essential role in shaping the composition, structure and dynamics of plant communities, as well as ecosystem functioning and service provisioning.
In this context, remote sensing data have become an important source for assessing all stages of the fire disturbance continuum for its cost-effectiveness and synoptic nature. The increasing availability of open access, active and passive remotely sensed global data sources, is very promising for this purpose. For instance, unprecedented spaceborne hyperspectral data, such as that provided by recently launched PRISMA and EnMAP spectrometer missions, have been opened new opportunities for assessing fire impacts on vegetation and soils.
We invite scientific contributions to the exploitation of new and/or advanced remote sensing techniques, sensors, data collections, and processing methodologies that can be successfully applied in all stages of the fire disturbance continuum. We welcome submissions that cover but are not limited to:
- Use of space and airborne sensors to assess active fire characteristics;
- Characterization of pre-fire fuel structure and composition for burned area and fire severity prediction;
- Burned area and fire severity mapping at local to global scales through new/advanced algorithms and data fusion approaches;
- Remote-sensing-based assessment of post-fire vegetation recovery trajectories;
- Three-dimensional mapping of fire effects on vegetation structure by SfM photogrammetry, LiDAR and SAR;
- Use of new imaging spectroscopy (hyperspectral) missions in post-fire assessments;
- Estimation of wildfire effects on soils through SAR data and data fusion approaches;
- Leveraging of very high spatial resolution data acquired by unmanned aerial vehicles (UAV);
- Characterization of wildfire regimes through remotely sensed regional/global data sources;
- Use of big data and cloud computing for large scale applications.
Dr. José Manuel Fernández-Guisuraga
Guest Editor
Manuscript Submission Information
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Keywords
- wildfires
- fire severity
- burned area
- multispectral/hyperspectral
- LiDAR
- SAR
- unmanned aerial vehicles
- fuel mapping
- fire impacts on vegetation and soils
- fire regime
