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Remote Sensing in Forest Fire Monitoring and Post-fire Damage Analysis
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More than half of the land surface on Earth can burn, and thus, fires are one of the most significant disturbances worldwide. Fires affecting forests are of great interest owing to the impacts they have on multiple provisioning and regulating ecosystem services. In this context, in which large portions of the Earth are affected by forest fires, remote sensing tools are essential equipment in fire-related assessments at multiple stages, including (I) the characterization of fire drivers and the development of predictive models, (II) the assessment of burned area, (III) the impact of the fire on soil and vegetation, and (IV) the post-fire recovery monitoring. In this reprint, we have compiled 10 research articles addressing these four topics and employing a wide variety of methodologies and remote sensing platforms (MSG, MODIS, Landsat, Sentinel-2 or airborne LiDAR).
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Keywords
- accuracy
- accuracy assessment
- airborne laser scanning
- biomes
- biophysical drivers
- burn severity
- Carbon
- change detection
- climate warming
- Continents
- convergence of evidence
- data augmentation
- Decision support systems
- Disturbance
- elevation
- fire impact
- fire perimeter
- fire severity
- forest landscapes
- fractional vegetation cover
- Geography
- geostationary satellite observations
- image compositing
- initial fire assessment
- land cover type
- Land surface temperature
- lidar remote sensing
- live fuel moisture content
- Mediterranean ecosystems
- MESMA
- MODIS
- multilabel classification
- n/a
- ordinary cokriging method
- orthogonal transformation
- peatland
- post-fire forest recovery
- post-fire severity
- PROSAIL
- random forests
- Recovery
- Reference, information & interdisciplinary subjects
- Regression analysis
- Research & information: general
- sampling-based inventory data
- Sentinel-2
- soil burn severity
- spatial patterns
- spectral indices
- thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
- transfer learning
- Trends
- vegetation indices
- vegetation phenology
- wildfire
- wildfire fuel loadings
- wildfire regime
- wildfire response