Cambium has recently received funding from the Spanish Agency of Research to develop the FUELMAP
Rural abandonment and fire suppression are leading to fuel build-up in the Mediterranean basin, and climate change is facilitating extreme weather conditions that increase the risk of catastrophic wildfires events. Planning preventive actions to reduce wildfire damage requires probabilistic risk assessments. Such assessments are dependent on fire spread simulation analyses that demand spatially explicit information on forest fuels. Unfortunately, current maps for critical fuel descriptors such as crown fuels (i.e., canopy base height (CBH), canopy bulk density (CBD) and canopy fuel load (CFL)) and live fuel moisture content (LFMC) lack the necessary accuracy or update frequency. Cambium research has recently received funding from the Spanish Agency of Research to develop the FUELMAP. This project, lead by Francisco Mauro, combines remote sensing and dendroecology techniques to improve characterizations of both crown fuels and LFMC.
To enhance crown fuel cartographies, crown profile models and biomass adjustment factors will be developed to better estimate available crown fuels. Later, these models and adjustment factors will be applied to field plots from the Spanish national forest inventory to obtain values of CBH, CBD and CFL, that will be used to train models to predict these variables using available remote sensing data (e.g., lidar and optical and radar satellite images).
LFMC is difficult to measure in the field which precludes obtaining data with the necessary frequency to reliably map and monitor this variable that is critical in planning fire prevention. The FUELMAP project proposes investigating the use of dense networks point dendrometers as a way to obtain indirect measurements of LFMC to improve our ability to monitor this important variable. The project will analyze the precision of these proximal sensors in determining LFMC and its changes and to what extent these indirect measurements can be combined with data from automated weather stations and multispectral and radar images to generate dynamic maps of LFMC. The results of this project will provide better inputs to physics-based fire spread simulators which, in turn, will result in more accurate wildfire risk assessment and a better design of preventive fuel management actions.
E-FIRE project (CNS2023-144923) funded by MICIN/AEI and by “European Union NextGenerationEU/PRTR”