Mapping Long-Term Wildfire Dynamics in Portugal Using Trajectory Analysis (1975–2024)

Bruno Barbosa, Ana Gonçalves, Sandra Oliveira and Cláudia M. Viana ()
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Bruno Barbosa: Centre of Geographical Studies, Institute of Geography and Spatial Planning, University of Lisbon, 1600-276 Lisbon, Portugal
Ana Gonçalves: Centre of Geographical Studies, Institute of Geography and Spatial Planning, University of Lisbon, 1600-276 Lisbon, Portugal
Sandra Oliveira: Centre of Geographical Studies, Institute of Geography and Spatial Planning, University of Lisbon, 1600-276 Lisbon, Portugal
Cláudia M. Viana: Centre of Geographical Studies, Institute of Geography and Spatial Planning, University of Lisbon, 1600-276 Lisbon, Portugal

Land, 2025, vol. 14, issue 9, 1-15

Abstract: Wildfire regimes in Mediterranean landscapes are becoming increasingly unpredictable, driven by the combined effects of climate change, land-use transitions, and socio-economic pressures. Traditional metrics such as burned area or ignition points often fail to capture the complexity of the temporal and spatial recurrence of fire events. To address this gap, we apply, for the first time, a trajectory analysis framework to wildfire occurrence data across mainland Portugal (1975–2024), using pixel-level binary time series at 100 m resolution. Originally developed for land cover change detection, this method classifies each pixel into sequences representing distinct temporal patterns (e.g., stability, gains, losses, or alternations) over defined periods. Results reveal a predominance of stable absence and alternation-type trajectories, particularly “All alternation gain first”, which points to recurrent yet irregular fire activity. Regional differences further highlight the influence of divergent socio-ecological contexts. The findings suggest that fire regimes in Portugal are not only recurrent but structurally dynamic, and that trajectory-based classification offers a novel and valuable tool for long-term monitoring and regionally adapted fire management. Applying this method to wildfire data required specific adjustments to account for the unique temporal and thematic characteristics of fire regimes, ensuring a meaningful interpretation of the results.

Keywords: wildfire occurrence; long-term; trajectory analysis; regional patterns (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2025
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