Identification and mapping fire danger zones using modeling

Mediterranean ecosystems face escalating wildfire challenges as climate change intensifies extreme temperature conditions across Southern Europe, making fire danger zone identification increasingly critical for ecosystem management. This research develops a satellite-based modeling framework integrating spatial analysis techniques to comprehensively map fire danger zones across Sicily's Messina province. The study focuses on this fire-prone region where the convergence of fuel availability, multiple ignition sources, and extreme environmental conditions create favorable scenarios for wildfire events. This methodology employed European Forest Fire Information System data spanning the period 2012-2024 (excluding 2015 due to data unavailability) to analyze wildfire patterns across Messina's 326,689 hectares. The research implemented a six-step analytical framework: temporal binary coding for fire occurrence pattern identification, multi-layer spatial union of administrative and burned boundaries, raster conversion with cumulative summation, integrated forest type mapping, coordinate reference system standardization, and comprehensive vegetation-based area calculations. This methodological approach achieved high spatial accuracy while ensuring analytical consistency across heterogeneous landscape types. Results reveal substantial wildfire impact across the study region, with 30,654 hectares affected representing 9.38% of Messina's total area. Fire frequency analysis demonstrated a significant increasing trend, growing from 64 events in 2012 to 382 events in 2023. Spatial analysis identified 1,470 distinct fire events distributed throughout the provincial area. Vegetation impact analysis revealed differential vulnerability patterns, with agricultural lands most affected (34.84% of burned area), followed by Mediterranean maquis (25.88%) and oak forests (19.98%). Mountain pine forests exhibited the highest reburn vulnerability (35.32%), while beech forests demonstrated complete resistance to repeated burning. The modeling approach has so far successfully identified fire danger zones and vulnerability patterns across Messina's diverse ecosystem types, providing valuable data for targeted fire prevention strategies and ecosystem restoration priorities. This research contributes important insights to fire danger zone mapping and establishes a methodology applicable to similar wildfire-prone region across Southern Europe.

Key words: Fire danger zones, Spatial modeling, Mediterranean ecosystems, Burn frequency, Vegetation vulnerability