Satellite-based analysis of the spatial patterns of fire- and storm-related forest disturbances in the Ural region, Russia

Andrey N. Shikhov (), Ekaterina S. Perminova and Sergey I. Perminov
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Andrey N. Shikhov: Perm State University
Ekaterina S. Perminova: SCANEX Group
Sergey I. Perminov: SCANEX Group

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2019, vol. 97, issue 1, No 15, 283-308

Abstract: Abstract Large-scale wildfires and windstorms are the most important disturbance agents for the Russian boreal forests. The paper presents an assessment of fire-related and wind-induced forest losses in the Ural region of Russia for 2000‒2014. The assessment is based on the use of Landsat images, Global Forest Change dataset (Hansen et al. in Science 342:850–853, 2013. https://doi.org/10.1126/science.1244693 ) and other space imagery data. The total area of stand-replacement fires and windthrows in the Ural’s forests was estimated at 1.637 million ha, which is 1.56% of the total forest-covered area. The contribution of wildfires and windthrows is 96.4% and 3.6%, respectively. The highest frequency of large-scale wildfires was observed behind the Northern Ural ridge, where the fire scars of 2000‒2014 covered 10–14% of the forested area. The storm-related forest damage is significant only on the western part of the Ural. A few catastrophic wildfires and windthrows (with an area > 5000 ha) make up 35% of the entire damaged area. The number of wildfires, windthrows and their damaged area vary significantly from year to year. For 2000–2014, it is impossible to find a statistically significant trend of the fire- and storm-damaged area. The seasonal maximum of large-scale wildfires and windthrows was observed in July. Also, we identified the statistically significant relationships of fire- and wind-related forest damage with environmental variables. The occurrence of large-scale wildfires is related mainly to the species composition of forests, and also to the altitude, the mean annual precipitation and the population density. The spatial distribution of massive windthrows has a strong correlation with the species composition of forests, the mean annual precipitation and partially with the wind effect parameter.

Keywords: Forest fires; Windthrows; Long-term data series; Spatio-temporal distribution; Global Forest Change data; Landsat images; Ural region (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s11069-019-03642-z

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