A5012066194- Fire effects on ecosystems
- Landslides and related hazards
- Plant Water Relations and Carbon Dynamics
- Ecology and Vegetation Dynamics Studies
- Remote Sensing in Agriculture
- Advanced Chemical Sensor Technologies
- Remote Sensing and LiDAR Applications
- Spectroscopy and Chemometric Analyses
- Flood Risk Assessment and Management
- Wildlife Ecology and Conservation
- Plant and soil sciences
- Rangeland and Wildlife Management
- Fire dynamics and safety research
- Advanced Combustion Engine Technologies
- Climate variability and models
- Fire Detection and Safety Systems
- Soil Science and Environmental Management
- Heavy metals in environment
- Nuclear and radioactivity studies
- Nuclear Materials and Properties
Universitat de Lleida
2019-2025
Remotely sensed vegetation indices have been widely used to estimate live fuel moisture content (LFMC). However, marked differences in structure affect the relationship between field-measured LFMC and reflectance, which limits spatial extrapolation of these indices. To overcome this limitation, we explored potential random forests (RF) at subcontinental scale Mediterranean basin wildland. We built RF models (LFMCRF) using a combination MODIS spectral bands, indices, surface temperature, day...
Dead fine fuel moisture content (FM) is one of the most important determinants fire behavior. Fire scientists have attempted to effectively estimate FM for nearly a century, but we are still lacking broad scale evaluations different approaches prediction. Here tackle this problem by taking advantage or recently compiled global behavior database (BONFIRE) gathering 1603 records 1h (i.e., <6 mm diameter thickness) dead from measurements before experimental fires. We compared results models...
Live Fuel Moisture Content (LFMC) is one of the main factors affecting forest ignitability as it determines availability existing live fuel to burn. Currently, LFMC monitored through spectral vegetation indices or inferred from meteorological drought indices. While useful, neither approach provides mechanistic insights into species-specific variation and they are limited in ability forecast under altered future climates. Here, we developed a semi-mechanistic model predict daily across woody...
Abstract Wildfire is a common phenomenon in Mediterranean countries but the 2022 fire season has been extreme southwest Europe (Portugal, Spain and France). Burned area exceeded 2001-2021 median by factor of 52 some regions large wildfires started to occur June-July, earlier than traditional season. These anomalies were associated with record-breaking values fuel dryness, atmospheric water demand pyrometeorological conditions. For instance, live moisture content was below historical minima...
<title>Abstract</title> The European Union has recently passed the Nature Restoration Law (NRL) which, among others, seeks to increase cover of forest reserves protected for biodiversity and, globally, Kunming-Montreal Global Biodiversity Framework similarly expand areas. Here we test whether a trade-off exists between areas expansion and fire activity, leading higher exposure population in areas, because they often harbour more biomass occur remote We analysed fires affecting 14,892,174 ha,...
Los incendios forestales constituyen una de las mayores perturbaciones a nivel mundial y, en especial, regiones mediterráneas. Este trabajo propone la aplicación espacial un método predicción del contenido humedad combustible fino y muerto (FM), que muestra relación contrastada con el área quemada acumulada tras incendio. El modelo empleado para predecir FM requiere únicamente déficit presión vapor, cuyo valor se obtiene los datos cuadrícula temperatura relativa. Para convertir mediciones...
Live Fuel Moisture Content (LFMC) is one of the main factors affecting forest ignitability as it determines availability existing live fuel to burn. Currently, LFMC monitored through spectral vegetation indices or inferred from meteorological drought indices. While useful, neither approach provides mechanistic insights into species-specific variation and they are limited in forecasting under changing projected climate. Here, we developed a semi-mechanistic model predict daily across woody...