Burn severity evaluation in black pine forests with topographical factors using Sentinel-2 in Kastamonu, Turkiye

Abstract

Background: Forest fires are one of the most important natural disasters all over the world in terms of the damage they cause to the ecosystem. Turkey is also exposed to wildfires damaging large areas of forests every year. Wildfires endanger the sustainability of forest resources and cause significant biological and ecological damage to the forests. It is crucial to estimate fire behaviour characteristics to take effective interventions in the fire events. Obtaining data based on terrestrial measurements is very expensive and very time-consuming to predict fire behaviour characteristics. The use of remote sensing technologies is therefore very useful since the satellite images will be faster, more sensitive, and economical to determine the burning severity and burning areas. Results: In this study, the forest fire that occurred in the Kastamonu-Taşköprü district was analyzed with remote sensing techniques. The fire occurred in 2020 (06.09.2020). The fire satellite image was thus taken from the pre-fire period (26.08.2020) and post-fire period (13.10.2020). First of all, pre-fire and post-fire Sentinel-2 images of fire areas were used to determine the burned area using NBR (Normalized Burn Ratio) and dNBR (Differenced Normalized Burn Ratio) indices. Also, burned area rate and burn severity were evaluated depending on the altitude, aspect, and slope factors. Conclusion: The total burned area was 1504.9 ha. The maps showed that the burned areas were covered by moderate-and high-severity classes. The forest fire was more severe in the altitude range from 1170 to 1370m, at 20-33% slope and northerly aspects in the burned area. The existence of extreme meteorological factors and the horizontal and vertical continuity of the forest fuels have been the main factors in the effect of the fire on large areas. Estimation of forest fire risk, taking into account extreme meteorological conditions and fuel properties, will have an important place in forest ecology and management.