Mapping the Most Susceptible Regions to Fire in Portugal

Abstract

Mediterranean European countries, including Portugal, are considered fire-prone regions, being affected by fire events every summer. Nonetheless, Portugal has been recording large burned areas over the last 20 years, which are not only strongly associated with hot and dry conditions, but also with high fuel availability in the ecosystems. Due to recent catastrophic fire seasons, Portugal has been implementing preventive policies during the pre-fire season, which, in turn, can optimize combat strategies during the fire season. In this context, our study contributes to fire prevention by identifying the regions with the highest potential to burn. The application of a Principal Component Analysis (PCA) to a range of climatological, ecological, and biophysical variables, either provided by remote sensing or reanalysis products, and known to be linked with diverse fire-vulnerability factors, allows the objective identification of the regions with the highest susceptibility to burn. The central and southernmost areas of Portugal present a stronger signal in the PCA, suggesting a likely high exposure to future fire events. The fuel accumulation over several months, in conjunction with elevation and fire weather conditions, are the terms out of the retained PCs that can explain most of the variability. The quality assessment performed for the burned areas in 2022 showed that they occurred in highly susceptible areas, highlighting the usefulness of the proposed methodology.

Exploring Drivers of Wildfires in Spain

“…A combination of climatic, socioeconomic, and topographic variables has been significantly influencing the occurrence of fires and the extent of burned areas in Spain [23,25,32,[45][46][47] and other Mediterranean countries such as Greece [48], the south-eastern part of France [30], Italy [31], and Portugal [29]. Regions in Spain show a large variability in the wildfire patterns and the extent of burned areas across different land cover types.…”

“…In our study, we used Principal Component Analysis (PCA). Recently, PCA has been applied to investigate the diverse drivers of wildfires, encompassing climatic, socioeconomic, and topographical factors on different eco-biome types around the world [25,29,30,49]. Many studies have compared the patterns of association between wildfires and environmental [17,51] or human-caused [23,52] drivers of wildfires in the EU-MED region.…”

“…Similarly, Jiménez-Ruano et al [28] identified regions of fire activity in Spain using PCA and Ward's hierarchy clustering models based on the spatial-temporal framework of their key fire characteristics. PCA was applied in Portugal [29] to identify the most vulnerable locations for wildfires, revealing that wildfires are more likely to occur in the central and southernmost areas of Portugal in the future. However, while many machine learning algorithm methods like PCA coupled with different mathematical models have been commonly employed to identify wildfire drivers or predict burned areas using climate, socioeconomic, and topographic factors (some of which are listed in this study), few studies have considered these factors combined [53,54].…”

“…Numerous studies have been conducted using PCA to determine the underlying factors influencing fires [25,26]. Indeed, among the many algorithms available, PCA is becoming a powerful tool for predicting the driving factors of wildland fires, the number of fires, and burned areas at all levels [25,[27][28][29][30][31]. Additionally, some authors have demonstrated that the PCA model produces better results as compared to other approaches [29,30,32,33].…”

“…Indeed, among the many algorithms available, PCA is becoming a powerful tool for predicting the driving factors of wildland fires, the number of fires, and burned areas at all levels [25,[27][28][29][30][31]. Additionally, some authors have demonstrated that the PCA model produces better results as compared to other approaches [29,30,32,33]. Consequently, PCA models have been widely employed in identifying wildfire drivers at global and continental scales; however, there has been minimal research at the national and provincial levels.…”