Modeling fire ignition probability and frequency using Hurdle models: a cross-regional study in Southern Europe

Abstract

Background Wildfires play a key role in shaping Mediterranean landscapes and ecosystems and in impacting species dynamics. Numerous studies have investigated the wildfire occurrences and the influence of their drivers in many countries of the Mediterranean Basin. However, in this regard, no studies have attempted to compare different Mediterranean regions, which may appear similar under many aspects. In response to this gap, climatic, topographic, anthropic, and landscape drivers were analyzed and compared to assess the patterns of fire ignition points in terms of fire occurrence and frequency in Catalonia (Spain), Sardinia, and Apulia (Italy). Therefore, the objectives of the study were to (1) assess fire ignition occurrence in terms of probability and frequency, (2) compare the main drivers affecting fire occurrence, and (3) produce fire probability and frequency maps for each region. Results In pursuit of the above, the probability of fire ignition occurrence and frequency was mapped using Negative Binomial Hurdle models, while the models’ performances were evaluated using several metrics (AUC, prediction accuracy, RMSE, and the Pearson correlation coefficient). The results showed an inverse correlation between distance from infrastructures (i.e., urban roads and areas) and the occurrence of fires in all three study regions. This relationship became more significant when the frequency of fire ignition points was assessed. Moreover, a positive correlation was found between fire occurrence and landscape drivers according to region. The land cover classes more significantly affected were forest, agriculture, and grassland for Catalonia, Sardinia, and Apulia, respectively. Conclusions Compared to the climatic, topographic, and landscape drivers, anthropic activity significantly influences fire ignition and frequency in all three regions. When the distance from urban roads and areas decreases, the probability of fire ignition occurrence and frequency increases. Consequently, it is essential to implement long- to medium-term intervention plans to reduce the proximity between potential ignition points and fuels. In this perspective, the present study provides an applicable decision-making tool to improve wildfire prevention strategies at the European level in an area like the Mediterranean Basin where a profuse number of wildfires take place.

Combining Methods to Estimate Post-Fire Soil Erosion Using Remote Sensing Data

“…On the contrary, olive groves show lower burnt area rates even when this land use is widespread in the case study. These results are supported by D'Este et al [83].…”

Is Experience the Best Teacher? Knowledge, Perceptions, and Awareness of Wildfire Risk

“…Nevertheless, in our study, surprisingly no significant differences were detected among subgroups on the perception of importance of scientific research and community involvement in improving and spreading awareness of wildfire risk. In fact, previous results have revealed that forest experts consider public awareness, in particular, concerning the impact of human activities, as a crucial element for risk reduction and fire management, especially in view of the ensuing effects of climate change [29][30][31].…”

Machine Learning Techniques for Fine Dead Fuel Load Estimation Using Multi-Source Remote Sensing Data

“…The geomorphological variables (Slope, Elevation, and Easterness) showed lesser importance in estimating the 1-h fuel load, probably due to their relationship to the landscape topography rather than to vegetation. According to D'Este et al [41], fire ignition probability is high at an altitude of about 500 m, which is the mean value of elevation in Apulia. This confirms the poor predictive power of these variables in discriminating the fire occurrence and the fine dead fuel production.…”

“…The fire season coincides with the summer period. Typically, the number of wildfires slightly increases between May and June, reaching a peak in August; these fires are mainly related to human activity [40,41]. Martina Franca represents one of the main towns in the Itria Valley, located in the central-south part of Apulia.…”