Every year worldwide some extraordinary wildfires occur, overwhelming suppression capabilities, causing substantial damages, and often resulting in fatalities. Given their increasing frequency, there is a debate about how to address these wildfires with significant social impacts, but there is no agreement upon terminology to describe them. The concept of extreme wildfire event (EWE) has emerged to bring some coherence on this kind of events. It is increasingly used, often as a synonym of other terms related to wildfires of high intensity and size, but its definition remains elusive. The goal of this paper is to go beyond drawing on distinct disciplinary perspectives to develop a holistic view of EWE as a social-ecological phenomenon. Based on literature review and using a transdisciplinary approach, this paper proposes a definition of EWE as a process and an outcome. Considering the lack of a consistent “scale of gravity” to leverage extreme wildfire events such as in natural hazards (e.g., tornados, hurricanes and earthquakes) we present a proposal of wildfire classification with seven categories based on measurable fire spread and behavior parameters and suppression difficulty. The categories 5 to 7 are labeled as EWE.

Wildfire fatalities remain a significant problem in Mediterranean Europe. Although there is a strong inter-annual variability with regard to their number, repeated tragic accidents remind us of this grim occurrence, despite the increasing firefighting capacity aimed to improve human safety. In this paper, we present an analysis of the 865 fatalities caused by wildfires in the 1945–2016 period. Data originating from national databases were merged, contextual and weather factors related to the accidents that caused these deaths were documented and analysed to explore probable relationships with the number and type of fatalities. Results show a major rise of fatalities in late 1970s in the four regions of Greece, Sardinia (Italy), Spain and Portugal. Fatalities present a strong seasonality in summer months, as expected. Overall, Spain has the highest absolute numbers of fatalities; however, normalisations by population, and burned and forest area show that annual number of fatalities is comparatively smaller. Certain other factors showed correlation with mortality. Civilians were the most affected group in Greece (65%) and Sardinia (58%), but not in Spain and Portugal. Findings indicate that an in-depth revision of fire-management policies and practices is required, with emphasis on prevention planning in urban areas, and better training of the firefighting resources.

A fuel-type map of a predominantly shrub-land area in central Portugal was generated for a fire research experimental site, by combining airborne light detection and ranging (LiDAR), and simultaneous color infrared ortho imaging. Since the vegetation canopy and the ground are too close together to be easily discerned by LiDAR pulses, standard methods of processing LiDAR data did not provide an accurate estimate of shrub height. It was demonstrated that the standard process to generate the digital ground model (DGM) sometimes contained height values for the top of the shrub canopy rather than from the ground. Improvement of the DGM was based on separating canopy from ground hits using color infrared ortho imaging to detect shrub cover, which was measured simultaneously with the LiDAR data. Potentially erroneous data in the DGM was identified using two criteria: low vegetation height and high Normalized Difference Vegetation Index (NDVI), a commonly used spectral index to identify vegetated areas. Based on the height of surrounding pixels, a second interpolation of the DGM was performed to extract those erroneously identified as ground in the standard method. The estimation of the shrub height improved significantly after this correction, and increased determination coefficients from R2 = 0.48 to 0.65. However, the estimated shrub heights were still less than those observed in the field.

On 17 June 2017, one of the most dramatic and destructive wildfires in Portugal’s History started, formed by a complex of at least five wildfires that merged together burning more than 45,000 hectares. In its aftermath, 66 persons lost their lives, most of them trying to run away from the fire, more than 250 were injured, and over 1000 structures (including 263 residential homes) were damaged or destroyed, with direct losses estimated at around 200 million euros. Shortly after the fire was extinguished, and as part of a larger analysis, the authors performed exhaustive field work to assess the fire impact on all manmade structures in the area of the Pedrógão Grande fire. A specific geodatabase was built, accounting for an extensive set of parameters aimed at characterizing: (i) The structure, (ii) the surroundings of the structure, and (iii) the arrival and impact of the fire. A total of 1043 structures were considered for the analysis, mostly support structures, like sheds or storage (38.6%), but also around 25% of dwellings (13.3% primary and 11.9% secondary). Regarding the ignitions, more than 60% of the structures were ignited due to the deposition of firebrands in different weak points. In addition, more than 60% of these ignitions occurred on the roofs, mainly because of the vulnerability associated with the structures and materials supporting them. Despite these results, and from what we observed on the structures that were not destroyed, we still consider that for the Portuguese reality houses are a good refuge, providing that they and their surroundings are managed and kept in good conditions.

Accurate and spatially explicit information on forest fuels becomes essential to designing an integrated fire risk management strategy, as fuel characteristics are critical for fire danger estimation, fire propagation, and emissions modelling, among other aspects. This paper proposes a new European fuel classification system that can be used for different spatial scales and purposes (propagation, behaviour, and emissions). The proposed classification system is hierarchical and encompasses a total of 85 fuel types, grouped into six main fuel categories (forest, shrubland, grassland, cropland, wet and peat/semi-peat land, and urban), plus a nonfuel category. For the forest cover, fuel types include two vertical strata, overstorey and understorey, to account for both surface and canopy fuels. In addition, this paper presents the methods to map fuel types at the European scale, including the first-level of the classification system. Land cover, biogeographic datasets, and bioclimatic modelling were used. The final map, which is publicly available (https://doi.org/10.21950/YABYCN; Aragoneses et al., 2022a), included 20 fuel categories at 1 km spatial resolution. A first assessment of this map was performed using field information obtained from LUCAS (Land Use and Coverage Area frame Survey), complemented with high-resolution data. This validation exercise provided an overall accuracy of 88 % for the main fuel types and 81 % for all mapped fuel types. To facilitate the use of this fuel dataset in fire behaviour modelling, an assignment of fuel parameters to each fuel type was performed by developing a crosswalk to the standard fuel models defined by Scott and Burgan (2005; FBFMs – Fire Behavior Fuel Models), considering European climate diversity. This work has been developed within the framework of the FirEUrisk project, which aims to create a European-integrated strategy for fire danger assessment, reduction, and adaptation.