Kurbanov, E.; Vorobev, O.; Lezhnin, S.; Dergunov, D.; Wang, J.; Sha, J.; Gubaev, A.; Tarasova, L.; Wang, Y. Temporal and Spatial Analyses of Forest Burnt Area in the Middle Volga Region Based on Satellite Imagery and Climatic Factors. Climate2024, 12, 45.
Kurbanov, E.; Vorobev, O.; Lezhnin, S.; Dergunov, D.; Wang, J.; Sha, J.; Gubaev, A.; Tarasova, L.; Wang, Y. Temporal and Spatial Analyses of Forest Burnt Area in the Middle Volga Region Based on Satellite Imagery and Climatic Factors. Climate 2024, 12, 45.
Kurbanov, E.; Vorobev, O.; Lezhnin, S.; Dergunov, D.; Wang, J.; Sha, J.; Gubaev, A.; Tarasova, L.; Wang, Y. Temporal and Spatial Analyses of Forest Burnt Area in the Middle Volga Region Based on Satellite Imagery and Climatic Factors. Climate2024, 12, 45.
Kurbanov, E.; Vorobev, O.; Lezhnin, S.; Dergunov, D.; Wang, J.; Sha, J.; Gubaev, A.; Tarasova, L.; Wang, Y. Temporal and Spatial Analyses of Forest Burnt Area in the Middle Volga Region Based on Satellite Imagery and Climatic Factors. Climate 2024, 12, 45.
Abstract
Wildfires are important natural drivers of forest stands dynamics, strongly influencing on their natural regeneration and ecosystem services. This paper presents a comprehensive analysis of spatiotemporal burnt area (BA) patterns over the period 2000–2022 in the Middle Volga region of the Russian Federation on the base of remote sensing time series, considering the impact of cli-matic factors on forest fires. The temporal trends were assessed with the Mann-Kendall nonpara-metric statistical test and Theil-Sen’s slope estimator using the LandTrendr algorithm on the Google Earth Platform (GEE). The accuracy assessment indicated a high overall accuracy (> 84%) and F-score value (> 82%) for forest burnt area detection as evaluated against 581 test sites of ref-erence data. The results revealed that the fire occurrences in the region were mainly irregular with the highest frequency of 7.3 over a 22-year period. The total forest BA was about 280 thousand ha, which equals to 1.7% of the land surface area or 4.0% of the total forested area under study in the Middle Volga region. The coniferous forest stands are the most fire-prone ecosystems accounting for 59.0 % of the total BA; deciduous stands accounts for 25.1%; and insignificant fire occurrences were registered in young forests and shrub lands. On a seasonal scale, temperature generally has a greater impact on the BA than precipitation and wind speed.
Keywords
wildfires; forest; climatic factors; monitoring; fire recurrence; remote sensing; machine learning; Landsat; time series; trend analyses
Subject
Environmental and Earth Sciences, Remote Sensing
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.