FirEUrisk_canopy_fuel_parameters: canopy height, canopy cover and canopy base height

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The dataset of European canopy fuel parameters, at 1 km spatial resolution, encompasses a total of 6 maps including: forest canopy height, canopy cover and canopy base height, along with their associated uncertainties. They have been generated by integrating GEDI with other sensors. Further details about the generation of these maps can be read in Aragoneses, E., García, M., Ruiz-Benito, P., and Chuvieco, E.: Mapping forest canopy fuel parameters at European scale using spaceborne LiDAR and satellite data, Remote Sensing of Environment, 2024 [accepted]. These maps complement the categorical information of the FirEUrisk European fuel type map for the forest fuel types in Aragoneses, E., García, M., Salis, M., Ribeiro, L. M., and Chuvieco, E.: Classification and mapping of European fuels using a hierarchical, multipurpose fuel classification system, Earth System Science Data, 15, 1287–1315, https://doi.org/10.5194/essd-15-1287-2023, 2023.

In-detail description of the dataset and methodology: Spatially explicit data on forest canopy fuel parameters provide critical information for wildfire propagation modelling, emission estimations and risk assessment. We developed a two-step, easily replicable methodology to estimate forest canopy fuel parameters (canopy height, canopy cover and canopy base height) for the entire European territory, based on data from the Global Ecosystem Dynamics Investigation (GEDI) sensor, onboard the International Space Station (ISS). First, we simulated GEDI pseudo-waveforms from discrete ALS data over forest plots. We then used metrics derived from the GEDI pseudo-waveforms to estimate mean canopy height, canopy cover and canopy base height, for which we used national forest inventory and airborne LiDAR as reference data. The second stage was to generate wall-to-wall maps of canopy fuel parameters at 1 km resolution using a spatial interpolation of GEDI-based estimates for polygons with GEDI footprints within. For those polygons for which GEDI observations were not available (mainly Northern latitudes, above 51.6ºN), the parameters were estimated using random forest regression models based on multispectral and SAR imagery and biophysical variables. Uncertainty maps for the estimated parameters were provided at the grid level, considering the propagation of individual errors for each step in the methodology. The final outputs provide a wall-to-wall estimation for the continent of Europe of three critical parameters for modelling crown fire propagation potential and demonstrate the capacity of GEDI observations to improve the characterisation of fuel models.

FirEUrisk project: This project has been granted funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No. 101003890. The FirEUrisk project pretends to harmonize and upgrade current European strategies by including the socio-economic circumstances that affect the occurrence of extreme wildfires as well as the biophysical conditions, such as vegetation and climate. This mix of perspectives allows a better understanding of how vulnerable communities are to wildfires and which are the best practices to adapt.