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Articles containing the keyword 'fire spread'

Category : Research article

article id 26006, category Research article
Aleksi Knaappila, Henrik Lindberg, Heidi Tanskanen, Tuomas Aakala. (2026). Ignition probability and fire size in Finnish boreal forests: a nationwide analysis of 10 years of rescue services data​. Silva Fennica vol. 60 no. 3 article id 26006. https://doi.org/10.14214/sf.26006
Keywords: Finland; spatial analysis; wildfire; lightning; fire spread; human-caused ignitions; official fire records
Highlights: Relative ignition probability was primarily associated with human population density, day of year, and canopy cover; Fire size was most strongly influenced by human population density, distance to nearest road, and ignition cause; Higher human population density increased relative ignition probability but decreased fire size; Relative ignition probability peaked mid-season, whereas fire size was greatest early in the season.
Abstract | Full text in HTML | Full text in PDF | Author Info

Fires are major disturbances in boreal forests, and forest fire risk is projected to increase in Finland. Despite this, comprehensive large-scale analyses evaluating multiple potential drivers of fire ignition and size remain scarce. The aim of this study was to assess how selected environmental and human-related factors influence the relative ignition probability and fire size in Finnish boreal forests. We utilized data on forest fire occurrence and size, the Finnish Forest Fire Index (FFI), and ignition cause, compiled by rescue authorities across mainland Finland during 2014–2023. We supplemented it with spatial data describing environmental factors (site trafficability, slope, canopy cover, and dominant tree species) and human-related factors (human population density and distance to nearest road). The dataset contained 10 284 forest fire observations and an equal number of pseudo-absence observations. We fitted one generalized additive model (GAM) each to explain relative ignition probability and fire size. The relative ignition probability model explained 51.6% of the deviance and achieved a classification accuracy of 83.7%, while the fire size model explained 21.5% of the deviance. Human-related variables were among the most influential in both models, with human presence increasing relative ignition probability but reducing fire size. Seasonality and weather were also significant, suggesting a major influence of weather and vegetation dynamics on fuel moisture, whereas dominant tree species affected only fire size and slope only relative ignition probability. The contrasting effects of humans on forest fires suggest potential for reducing future fire risk through targeted fire management strategies.


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