Remote Sensing in Forest Fire Monitoring and Post-fire Damage Analysis

• Other Authors: Fernández-García, Víctor (Editor), Calvo, Leonor (Editor), Suarez-Seoane, Susana (Editor), Marcos, Elena (Editor)
• Format: Electronic Book Chapter
• Language: English
• Published: Basel MDPI - Multidisciplinary Digital Publishing Institute 2023
• Subjects: Research & information: general; Geography; wildfire fuel loadings; sampling-based inventory data; ordinary cokriging method; regression analysis; lidar remote sensing; Mediterranean ecosystems; convergence of evidence; accuracy assessment; wildfire response; multilabel classification; data augmentation; decision support systems; transfer learning; geostationary satellite observations; wildfire regime; biophysical drivers; land surface temperature; land cover type; trends; Sentinel-2; post-fire severity; initial fire assessment; soil burn severity; fire perimeter; image compositing; vegetation phenology; live fuel moisture content; wildfire; MODIS; spectral indices; random forests; elevation; airborne laser scanning; peatland; carbon; accuracy; change detection; disturbance; fractional vegetation cover; MESMA; PROSAIL; recovery; fire impact; post-fire forest recovery; forest landscapes; vegetation indices; orthogonal transformation; fire severity; burn severity; spatial patterns; biomes; continents; climate warming; n/a
• Online Access: DOAB: download the publication; DOAB: description of the publication

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).